Jay Shah Podcast
Jay Shah
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Interviews with scientists and engineers working in Machine Learning and AI, about their journey, insights, and discussion on latest research topics.
Available episodes
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Jan 17, 2022
Tips & Insights into Program Manager Role | Divy Thakkar, PM at Google Research
Divy is a Program Manager and one of the founding members of Google research in India. He is actively involved and leading strategic programs that connect academia and research at Google, programs that focus on AI-for-Social-Good initiatives, and educational programs for schools in India with a particular focus on building computer science foundations.
00:00:12 Introductions
00:01:12 Background prior to joining Google
00:08:40 Programs you are working on as a Program Manager at Google Research and what are your responsibilities
00:14:35 Lifecycle of a program & various phases
00:17:55 Getting involved in research while being a Program Manager
00:25:55 Learning skills for strategic thinking as a PM
00:35:08 How did you get your PM role at Google and what was the interview like?
00:40:35 Resources people can use to prepare for PM interviews
00:41:58 Difference b/w Product vs Program vs Technical Manager
00:46:10 Previous experiences that helped develop skills for Program Manage role
00:53:58 Tips on being more organized with work
Divy's Homepage: https://sites.google.com/view/divythakkar
Twitter: https://twitter.com/divy93t
LinkedIn: https://www.linkedin.com/in/divythakkar/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#research #programmanager #googleresearch #india #aiforsocialgood #manager
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jan 2, 2022
How do you decide which research problems to work on? Manish Gupta, Director of Google Research, India
Watch the full conversation with Dr. Manish Gupta here: https://youtu.be/-Tl6-DKxEMU
Dr. Manish Gupta is currently the Director of Google Research in India. Prior to that he was the Vice-president and led the Xerox Research Center in India majorly working on data analytics and mobile computing. Before that, he was also at IBM research in India leading the efforts and building a lab focused on high-performance computing and business analytics. He also led the efforts at Goldman Sachs developing technologies relating to cloud, databases, and networking aiding business functions. We also co-founded and was the CEO of an educational technology startup called VideoKen.
Dr. Manish Gupta's Homepage
https://www.iiitb.ac.in/faculty/manish-gupta
https://research.google/people/106704/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#research #ai #machinelearning #googleresearch #india #aiforsocialgood
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Dec 9, 2021
Writing a good Research Thesis | Dr. Hanie Sedghi, Google Research
Check out the full conversation with Hanie here: https://youtu.be/hFJLuqaSakA
Hanie is a senior research scientist at Google Brain working on research problems related to understanding and improving deep learning techniques. She works on designing algorithms with theoretical guarantees such that they work efficiently in real-world applications. Prior to that, she was a research scientist at Allen Institute of AI, and before that she was a Post-Doc fellow at UC Irvine. She graduated from USC with a Ph.D. with minors in Mathematics.
Dr. Hanie Sedghi's links
Twitter: https://twitter.com/haniesedghi?ref_src=twsrc%5Etfw
Homepage: https://haniesedghi.com/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#theoryofmachinelearning #deeplearning #ai #machinelearning #fundamentals
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Nov 11, 2021
Building a research lab from scratch & using AI for Social Good, Manish Gupta Google Research India
Dr. Manish Gupta is currently the Director of Google Research in India. Prior to that he was the Vice-president and led the Xerox Research Center in India majorly working on data analytics and mobile computing. Before that he also at IBM research in India leading the efforts and building a lab focused on high-performance computing and business analytics. He also worked on the IBM Blue Gene supercomputer project in the early 2000s at IBM TJ Watson research center for which IBM received the National Medal of Technology and Innovation from the President of the US. He also led the efforts at Goldman Sachs developing technologies relating to cloud, databases, and networking aiding business functions. We also co-founded and was the CEO of an educational technology startup called VideoKen. He has received many distinguished awards for his efforts and has coauthored many academic papers in the domains of computer science.
Time-Stamps
00:00:00 Introductions
00:01:50 What kind of research projects are you currently spearheading at Google Research and what does your work routine look like?
00:06:30 What was your thought process prior to joining Google Research?
00:13:40 What’s the difference between a Researcher | Senior Researcher | Director of research?
00:23:00 What should robust AI systems look like?
00:33:22 How do you decide which research problems to work on?
00:46:46 What kind of challenges have you encountered while working on AI research problems specific to India?
00:56:15 How do you design and evaluate the impact of these AI projects?
00:59:27 What made you consider shifting back to India after a long streak of a career in the USA? What factors did you consider?
01:03:06 Any skills you would suggest students nurture apart from technical expertise?
01:05:40 There’s always a concern about AI usage and automation. Where do you think the balance lies?
Dr. Manish Gupta's Homepage
https://www.iiitb.ac.in/faculty/manish-gupta
https://research.google/people/106704/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#research #ai #machinelearning #googleresearch #india #aiforsocialgood
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Nov 6, 2021
Benefits of understanding Theory of Deep Learning | Dr. Hanie Sedghi, Google Brain
Hanie is a senior research scientist at Google Brain working on research problems related to understanding and improving deep learning techniques. She works on designing algorithms with theoretical guarantees such that they work efficiently in real-world applications. Prior to that, she was a research scientist at Allen Institute for AI, and before that she was a Post-Doc fellow at UC-Irvine. She graduated from USC with a Ph.D. with minors in Mathematics.
Dr. Hanie Sedghi's links
Twitter: https://twitter.com/haniesedghi?ref_src=twsrc%5Etfw
Homepage: https://haniesedghi.com/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#theoryofmachinelearning #deeplearning #ai #machinelearning #fundamentals
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 29, 2021
CNNs & ViTs (Vision Transfomers) - Comparing the internal structures, Maithra Raghu, Google
Do Vision Transformers work in the same way as CNNs? Do the internal representational structures of ViTs and CNNs differ? An in-depth analysis article: https://arxiv.org/pdf/2108.08810.pdf
Listen to the full conversation here: https://youtu.be/htnJxcwJqeA
Dr. Maithra Raghu is a senior research scientist at Google working on analyzing the internal workings of deep neural networks so that we can deploy them better keeping humans in the loop. She recently graduated from Cornell University with a Ph.D. in CS and previously graduated from Cambridge University with BA and Masters in Mathematics. She has received multiple awards for her research work including the Forbes 30 under 30.
Maithra's Homepage: https://maithraraghu.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#explainableai #reliableai #robustai #machinelearning
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 4, 2021
How to find a Research Topic that interests you?
How to decide and choose a research/thesis to work on that interests you and is also relevant to current research directions.
Full episodes with
Maithra, Google: https://youtu.be/htnJxcwJqeA
Natasha Google: https://youtu.be/8XpCnmvq49s
Milind Google: https://youtu.be/eqwF3NpZFb4
Hima Harvard University: https://youtu.be/8Ym4oYTd8Fo
Ishan Facebook AI: https://youtu.be/Pb5RQAEtznk
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#machinelearning #ai #phd #research #thesis
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Sep 30, 2021
Learning the internals of Machine Learning systems and tips for PhD | Maithra Raghu, Google Brain
Dr. Maithra Raghu is a senior research scientist at Google working on analyzing the internal workings of deep neural networks so that we can deploy them better keeping humans in the loop. She recently graduated from Cornell University with a PhD in CS and previously graduated from Cambridge University with BA and Masters in Mathematics. She has received multiple awards for her research work including the Forbes 30 under 30.
Questions that we cover
00:00:00 Introductions
00:01:00 To understand more about your research interests, can you tell us what kind of research questions you are interested in while working at Google Brain?
00:04:45 What interested you about it and how did you get started?
00:15:00 What is one thing that surprises/puzzles you about deep learning effectiveness to date?
00:22:05 What’s the difference between being a researcher in academia/PhD student vs being a researcher at a big organization (Google)?
00:28:35 In what use cases do you think ViTs might be a good choice to perform image analysis over CNN vs where do you think CNNs still have an undoubted advantage?
00:37:15 Why does ViT perform better than ResNet only on larger datasets and not on mid-sized datasets or smaller?
00:43:55 In regards to medical imaging tasks, would it be theoretically wrong to pre-train the model on dataset A and fine-tune it on dataset B?
00:47:35 Do you think ViT or transformer-based models already have/have the potential to cause a paradigm shift in the way we approach imaging tasks? Why?
00:5:25 Medical datasets are often limited in size, what are your views on tackling these problems in the near future
00:55:55 From an internal representation perspective, do you think deep neural networks can have the ability of reasoning?
00:58:20 How did you decide on your own PhD research topic? Advice you would give to graduate researchers trying to find a research problem for their thesis?
01:04:00 Many times researchers/students feel stuck/overwhelmed with a particular project they are working on, how do you suggest based on experience to tackling that?
01:10:35 How do you now/as a graduate student used to keep up with the latest research in ML/DL?
Maithra's Homepage: https://maithraraghu.com
Blogpost talked about: https://maithraraghu.com/blog/2020/Reflections_on_my_Machine_Learning_PhD_Journey/
Her Twitter: https://twitter.com/maithra_raghu
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#explainableai #reliableai #robustai #machinelearning
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Sep 23, 2021
How can students contribute to Impactful AI projects? | Dr. Milind Tambe, Google Research
How can you students and researchers work on projects using AI that creates a real impact and difference in society?
Watch the full podcast with Dr. Tambe here: https://youtu.be/eqwF3NpZFb4
Dr. Milind Tambe is a Professor of Computer Science at Harvard University and Director of the Center for Research in Computation and Society. He is also the Director of AI for Social Good at Google Research in India. He has been leading and working on projects that are creating an impact, ranging from wildlife conservation, public health, and safety using AI techniques.
Prof. Milind Tambe's Homepage: https://teamcore.seas.harvard.edu/tambe
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#aiforsocialgood #googleai #ai #machinelearning #socialimpact
***Disclaimer: The information contained in this video represents the views and opinions
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Jul 20, 2021
Challenges and beauties of building a Tech Startup | Nasrin Mostafazadeh
Watch the full conversation with Nasrin here: https://youtu.be/59kRUmhA5yI
Nasrin is the co-founder of a deep-tech startup Verneek and has been in the space of AI startups for the past 5 years now. Before that, she was a senior research scientist at Elemental Cognition & BenevolentAI, and prior to which she graduated with a Ph.D. from the University of Rochester and her major research interests are in building intelligent systems that can demonstrate commonsense reasoning & generate causal explanations in order to improve human-AI collaborations. She was featured in Forbes 30u30 for her work in NLU.
Nasrin's LinkedIn Profile: https://www.linkedin.com/in/nasrinm/
Her startup Verneek: https://www.linkedin.com/company/verneek/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming podcasts!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jul 19, 2021
Intuition for research in Social Reinforcement Learning | Natasha Jacques
How can we build intuition for interdisciplinary fields in order to tackle challenges in social reinforcement learning?
Natasha Jaques is currently a Research Scientist at Google Brain and a post-doc fellow at UC Berkeley, where her research interests are in designing multi-agent RL algorithms while focusing on social reinforcement learning. She received her Ph.D. from MIT and has also received multiple awards for her research works submitted to venues like ICML and NeurIPS She has interned at DeepMind, Google Brain, and is an OpenAI Scholars mentor.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent…
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Jul 18, 2021
Challenges of productionizing Machine Learning Research in Industry | Aarti Bagul
Why and where do companies fail at productionizing ML models?
Watch the full podcast with Aarti here: https://youtu.be/VWJXiszQpTU
Aarti is a machine learning engineer at Snorkel AI. Prior to that, she worked closely with Andrew Ng in various capacities. She graduated with a master’s in CS from Stanford, and bachelor's in CS and Computer Engineering from @New York University, and at @Microsoft Research as a research intern for John Langford, where she contributed to Vowpal Wabbit, an open-source project.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It…
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Jul 18, 2021
Doing a PhD & Excelling at Research | Dr. Hima Lakkaraju
Deciding whether to do a Ph.D. or not and things to focus on while writing your research thesis.
Watch the full podcast here: https://youtu.be/8Ym4oYTd8Fo
Dr. Himabindu Lakkaraju is an Assistant Professor at Harvard University and her major research interests are along the lines of explainability, fairness, and robustness in AI systems. Prior to that she graduated with a Ph.D. from @Stanford and has received multiple awards for her research work.
Dr. Lakkaraju's homepage: https://himalakkaraju.github.io/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
#explainableai #reliableai #robustai #machinelearning
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily…
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Jul 2, 2021
Founding a Startup, doing a PhD, Interpretability | Dr. Geneviève Patterson
Dr. Geneviève Patterson is the head of applied research at VSCO. Prior to that, she was the CTO of a video editing company she co-founded called TRASH - later acquired by VSCO. She holds a Ph.D. in CS from Brown University with a focus on research in video understanding. She was also a postdoctoral researcher at Microsoft Research where she worked on interpreting deep neural networks and much more.
Geneviève Homepage: http://genp.github.io/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affi…
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Jul 2, 2021
Using AI for Social Good | Dr. Milind Tambe
Dr. Milind Tambe is a Professor of Computer Science at Harvard University and Director of the Center for Research in Computation and Society. He is also the Director of AI for Social Good at Google Research in India. He has been leading and working on projects that are creating an impact, ranging from wildlife conservation, public health, and safety using AI techniques.
Time Stamps:
00:00 Introductions
01:05 In concrete terms what projects are you currently working on?
03:18 Do you think there is a disconnect between the scientific/tech communities and the social sector while trying to make use of AI? If so, who should be taking more lead for making that gap small?
05:26 Do these applications in any way inspire novelty in the theoretical aspects of Machine Learning research?
08:15 How do you design and evaluate the impact of these projects?
11:20 How do you define Interpretable or Explainable AI, at the intersection of social sciences and AI?
16:50 Concern of AI usage and Automation.…
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Jun 26, 2021
"What got you into AI?" - Answers from 30 different researchers & engineers
“What got you into AI? And what part of it really interests you about it?” — a simple question that I have asked more than 30 researchers from different backgrounds and applications on my podcasts to learn more about their motivation. Thought of compiling them into one; to whosoever, it proves to be insightful with the aim to learn more what drives researchers explore and work in the domain of Machine Learning and what got them started in it!
About the Host:
I am a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
LinkedIn: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming podcasts!
#machinelearning #artificialintelligence #research
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not c…
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Jun 26, 2021
Shreya Shankar, ML Engineer @Viaduct on Applied ML research & more
Shreya is currently a graduate student at Stanford and also working as an ML engineer at Viaduct.ai. She has previously interned at Google-Brain and at Facebook. She talks about her experience as an applied ML engineer and making ML models work in the real world.
Shreya's homepage: https://www.shreya-shankar.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jun 26, 2021
How did I get into Machine Learning research? | Sara Hooker, Azalia Mirhoseini & Natasha Jacques - Google
Three research scientists from Google share their journey about interest in Machine Learning research and how they got started with it.
Watch full podcasts with each of these speakers:
Azalia Mirhoseini: https://youtu.be/5LCfH8YiOv4
Sara Hooker: https://youtu.be/MHtbZls2uts
Natasha Jacques: https://youtu.be/8XpCnmvq49s
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jun 26, 2021
Machine Learning Engineer vs Data Scientist | Jineet Doshi, Data Scientist @Intuit
Full episode available here: https://youtu.be/V1mDR4x_JY0
Jineet, a Data Scientist at Intuit and a graduate of Carnegie Mellon University shares some amazing insights about data science and machine learning probing his experiences.
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jun 26, 2021
Choosing to build an AI startup instead of Corporate Jobs | Nasrin Mostafazadeh
Read more about this here in her Twitter thread: https://twitter.com/nasrinmmm/status/1374372131207806976
Nasrin is the co-founder of a deep-tech startup Verneek and has been in the space of AI startups for the past 5 years now. Before that, she was a senior research scientist at Elemental Cognition & BenevolentAI, and prior to which she graduated with a Ph.D. from the University of Rochester and her major research interests are in building intelligent systems that can demonstrate commonsense reasoning & generate causal explanations in order to improve human-AI collaborations. She was featured in Forbes 30u30 for her work in NLU.
We talk about her background and story in AI, some details of her research work, and insights about being in the AI startup space.
Nasrin's LinkedIn Profile: https://www.linkedin.com/in/nasrinm/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www…
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Jun 22, 2021
What drives Research: Pursuit of Theory or Application? | Ishan & Michal, Facebook AI
What really drives the innovation in research projects? Is it a pure pursuit of theory or application-oriented?
Ishan is a Research Scientist at @Facebook AI. Much of his recent research work revolves around self-supervised learning is known for this works like including SwAV and PIRL and,
Michal Drozdzal is also a Research Scientist at @Facebook AI with major research interests in computer vision, Machine Learning, and medical image analysis.
The full conversation with Ishan: https://youtu.be/uOVxndMyasc
And Michal: https://youtu.be/9gKwux0r0KY
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming podcasts!
#artificialintelligence #machinelearning #aiinhealthcare #medicalimaging
***Disclaimer: The information contained in this video represents the…
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Jun 10, 2021
Game & Network Theory to stop coronavirus spread, Math in AI & more | Po-Shen Loh
Po-Shen Loh is a Professor of Mathematics at Carnegie Mellon University with research interests in combinatorics, probability theory, and computer science. He is also the coach of the United States International Math Olympiad team and it was under his guidance he led his teams to secure first place in 2015, 16, 18, and 19. He is also the founder of Expii, an online platform that teaches young students basic concepts of math and science. He is also the founder of the NOVID app that has an innovative way of contact tracing in order to reduce the spread of coronavirus.
NOVID App: https://www.novid.org/
More about Po: https://www.poshenloh.com/
About the Host:
I am a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
LinkedIn: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming podcasts!
#mathematics #research #coronavirus #covid
***Di…
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May 14, 2021
Applications & Challenges of AI in Healthcare | Michal Drozdzal
Michal Drozdzal is a Research Scientist at Facebook AI with major research interests in computer vision. Machine Learning and medical image analysis. He received a Ph.D. in Computer Science from the University of Barcelona. We talk about his journey into research, some open research questions, how research projects look at the intersection of AI and medical research, and more about the democratization of AI research.
Michal's LinkedIn account: https://www.linkedin.com/in/michal-drozdzal-a36b9b42/?originalSubdomain=ca
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming podcasts!
#artificialintelligence #machinelearning #aiinhealthcare #medicalimaging
***Disclaimer: The information contained in this video represents the views and opinions of the spe…
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May 6, 2021
Transitioning from Academia to Startups, Natural Language Understanding & more | Nasrin Mostafazadeh
Nasrin is the co-founder of a deep-tech startup Verneek and has been in the space of AI startups for the past 5 years now. Before that, she was a senior research scientist at Elemental Cognition & BenevolentAI, and prior to which she graduated with a Ph.D. from the University of Rochester and her major research interests are in building intelligent systems that can demonstrate commonsense reasoning & generate causal explanations in order to improve human-AI collaborations. She was featured in Forbes 30u30 for her work in NLU.
We talk about her background and story in AI, some details of her research work, and insights about being in the AI-startup space.
Nasrin's LinkedIn Profile: https://www.linkedin.com/in/nasrinm/
Her startup Verneek: https://www.linkedin.com/company/verneek/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach o…
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Apr 28, 2021
Failures & developing Gut feeling in Research | Ishan Mishra, Research Scientist @Facebook AI
How to deal and Interpret failures in research? Developing guts for which research will work out and which will not over course of time, from being a researcher in academia as a Ph.D. student to now being a research scientist at Facebook.
Check out the whole podcast here: https://youtu.be/Pb5RQAEtznk
Ishan is a Research Scientist at @Facebook AI. Much of his recent research work revolves around self-supervised learning is known for this works like including SwAV and PIRL. He completed his Ph.D. from @Carnegie Mellon University with Martial Hebert and Abhinav Gupta. and his thesis was titled “Visual Learning with Minimal Human Supervision”
Also check out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ f…
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Apr 9, 2021
Solving Dark Matter of Intelligence, Self-Supervised Learning | Ishan Mishra, Facebook AI
Ishan is a Research Scientist at Facebook AI. Much of his recent research work revolves around self-supervised learning is known for this works like including SwAV and PIRL. He completed his Ph.D. from CMU with Martial Hebert and Abhinav Gupta. and his thesis was titled “Visual Learning with Minimal Human Supervision”
Ishan's homepage: http://imisra.github.io/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Apr 2, 2021
Basics about Product Management and starting you career as PM | Linda Zhang
Linda is Product Lead at FAIRE and has in the past interned at Snap Inc., Microsft, BAIN, and graduate from Harvard University. She has a tremendous amount of experience in Product Management and openly shares her insights through newsletters here https://www.productlessons.xyz/ for people to get started with it.
You can reach out to her and follow more of her updates at https://twitter.com/thelindazhang
Also check out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not…
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Mar 30, 2021
Making AI models work for real-world applications | Aarti Bagul, ML Engineer
Aarti is a machine learning engineer at Snorkel AI. Prior to that, she worked closely with Andrew Ng in various capacities - at AI Fund helping build ML companies from scratch internally, as well as investing in ML companies, as a machine learning engineer at his startup Landing AI, as head TA for his deep learning class at Stanford University (CS230), and in his research lab at Stanford. She graduated with a master’s in CS from Stanford, and with bachelors in CS and Computer Engineering from New York University where she worked in David Sontag’s lab on applications of machine learning to clinical medicine, and at Microsoft Research as a research intern for John Langford, where she contributed to Vowpal Wabbit, an open-source project.
Reach out to her at
LinkedIn: https://www.linkedin.com/in/aartibagul
Twitter: https://twitter.com/aarti_bagul
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Ar…
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Mar 25, 2021
What no one tells you about being a Machine Learning Engineer? Aarti Bagul
What kind of challenges have you noticed while working with ML applications in production, that most newbies don't know as students or fresh graduates? And what ML applications production pipeline look like?
Watch the full podcast here: https://youtu.be/VWJXiszQpTU
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Mar 20, 2021
Working at DeepMind vs Google-Brain
Watch the full podcast with Natasha here: https://youtu.be/8XpCnmvq49s
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Mar 19, 2021
Why I turned down a 375K $ PM offer at Instagram? | Linda Zhang
Watch the full podcast with Linda here: https://youtu.be/0Yrt2lBzsNk
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Mar 11, 2021
Doing a PhD and Deciding thesis topic | Natasha Jacques, Research Scientist @Google
Watch the full podcast here: https://youtu.be/8XpCnmvq49s
Natasha Jaques is currently a Research Scientist at @Google Brain and a post-doc fellow at @UC Berkeley, where her research interests are in designing multi-agent RL algorithms while focusing on social reinforcement learning, that can improve generalization, coordination between agents, and collaboration between human and AI agents. She received her PhD from the @Massachusetts Institute of Technology (MIT) where she focused on Affective Computing and other techniques for deep/reinforcement learning. She has also received multiple awards for her research works submitted to venues like ICML and NeurIPS She has interned at @DeepMind, Google Brain, and is an @OpenAI Scholars mentor.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https:/…
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Mar 6, 2021
Deep Reinforcement Learning for Social Learning & Fun Chat | Natasha Jacques,@Google
Natasha Jaques is currently a Research Scientist at Google Brain and a post-doc fellow at UC-Berkeley, where her research interests are in designing multi-agent RL algorithms while focusing on social reinforcement learning, that can improve generalization, coordination between agents, and collaboration between human and AI agents. She received her Ph.D. from MIT where she focused on Affective Computing and other techniques for deep/reinforcement learning. She has also received multiple awards for her research works submitted to venues like ICML and NeurIPS She has interned at DeepMind, Google Brain, and is an OpenAI Scholars mentor.
00:00 Introductions
01:25 Can you tell us a bit about what projects you are working on at Google currently? And what does the work routine look like as a Research Scientist?
06:25 You have worked as a researcher at many diverse backgrounds who are leading in the domain of machine learning: MIT, Google Brain, DeepMind - what are the key differences you have…
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Mar 3, 2021
Preparing & nailing Product Management Interview | Renee Yao @NVIDIA
Learn more about what product management really is and the skills required for the role with Renee Yao, who leads global healthcare AI startups at @NVIDIA, managing 1000+ healthcare startups. Prior to that, she worked as a senior PM and product marketing manager for AI Systems at NVIDIA. She graduated from Haas School of Business at @UC Berkeley with a focus in Economics and IT.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement b…
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Feb 28, 2021
Ethics in AI, Role of Big Tech Companies & Bitcoin | @The New York Times reporter, Cade Metz
Cade Metz is a reporter at The New York Times where he frequently covers emerging areas of artificial intelligence, from self-driving cars to virtual reality and much more. Prior to that, he was also a senior staff writer at the WIRED magazine covering stories about big tech companies, bitcoins, and AI. He has a strong background in reporting and is also coming out with his own book called “Genius Makers” on March 16th.
Slate Star Codex, NYT: https://www.nytimes.com/2021/02/13/technology/slate-star-codex-rationalists.html
Book Genius Makers: https://cademetzauthor.com/order/
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer:…
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Feb 21, 2021
Bias in ML models can be Good & Bad | Akshay Chaudhari, @Stanford AIMI
Check out the full podcast here: https://youtu.be/t8YCzcWSUrg
Akshay is an Assistant Professor at @Stanford University in the Radiology department. He has a strong background in bioengineering with a bachelor's from @UC San Diego and Ph.D. from Stanford followed by a Postdoctoral experience in radiology at Stanford. We discuss more how machine learning is leveraged for faster medical image acquisition and post-processing methods.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any…
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Feb 9, 2021
Machine Learning in Medical Imaging | Dr. Akshay Chaudhari @Stanford
Akshay is an Assistant Professor at Stanford University in the Radiology department. He has a strong background in bioengineering with a bachelor's from UC San Diego and Ph.D. from Stanford followed by a Postdoctoral experience in radiology at Stanford. We discuss more how machine learning is leveraged for faster medical image acquisition and post-processing methods.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Instit…
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Feb 6, 2021
Building a profile for Product Management Roles (Machine Learning) | Sharon Zhou @Stanford
Sharon is a Stanford Computer Science Ph.D. student advised by Andrew Ng and Michael Bernstein working on generative models. Popularly known for her Coursera course on building GANs, she talks more about the use of AI in medicine, what product management is about, some philosophical fun chat and interpretability, and the future of AI in healthcare.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affil…
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Feb 5, 2021
What is Product Management? | Renee Yao @NVIDIA
Learn more about what product management really is and the skills required for the role with Renee Yao, who leads global healthcare AI startups at @NIVIDIA, managing 1000+ healthcare startups. Prior to that, she worked as a senior PM and product marketing manager for AI Systems at NVIDIA. She graduated from Haas School of Business at @UCBerkley with a focus in Economics and IT.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement b…
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Jan 31, 2021
Using Deep Reinforcement Learning for System Optimization & more | Dr. Azalia Mirhoseini, Google
Azalia is a Research scientist at the Google Brain team, where she leads machine learning for systems moonshot projects. Her research interests include and not limited to exploring deep reinforcement learning for optimizing computer systems. She has a Ph.D. in Electrical and Computer Engineering from Rice University and has received many awards for her contributions including the MIT Technology Review 35 under 35.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.…
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Jan 26, 2021
How to learn Machine Learning? Self-started ML researcher @Google Brain, Sara Hooker
Sara Hooker on getting started with learning machine learning, best resources and learning to implement models from scratch.
Watch the full episode with Sara here: https://youtu.be/MHtbZls2uts
Sara is a research scholar at the @Google-Brain team working on building interpretable machine learning models for reliability and robustness. We talk about how she transitioned from economics to now pure research at the Brain team. We also talk in detail about what interpretability means, what are the state-of-art techniques and what are some of the most important things any machine learning researcher must know.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming…
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Jan 22, 2021
Things I learned during my PhD that I did not expect! - Geneviève Patterson, Head of Research @VSCO
Things that I learned apart from research, non-technical traits I did not know you would but I am glad now I did.
Full podcast with Geneviève here: https://youtu.be/AA1Co0XBcKg
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jan 16, 2021
Role of Machine Learning in Healthcare | Dr. Matthew Lungren, @Stanford
How do medical professionals see ML fitting into medical research - Biomarker discovery? Confirming hypothesis with accuracy? A tool to manage much data?
Check out the full podcast here: https://youtu.be/qnOvXrkt7zE
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jan 15, 2021
State of AI in Radiology and its future | Prof. Matthew Lungren, @Stanford
Dr. Lungren is the Co-Director of the Stanford Center for Artificial Intelligence in Medicine and Imaging, @Stanford AIMI and an Associate Professor at @Stanford Medical Center. His research interest is in the field of AI and deep learning in medical imaging, precision medicine, and predictive health outcomes.
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Jan 7, 2021
Why I left my job at @Google - Debarghya Das
Check the full podcast with Debarghya Das: https://youtu.be/Vn79br3mKZM
Debarghya (Deedy), currently a Founding Engineer at a Stealth Startup is a computer science graduate from Cornell University. He has previously worked and interned at Google, Facebook and Coursera. In this podcast we talk about various computer science roles in industry: research, software engineering, product management, and doing a PhD or not.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It…
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Jan 2, 2021
Debarghya Das, Working at Big companies vs Small, and more - Ex-@Google
Debarghya (Deedy), currently a Founding Engineer at a Stealth Startup is a computer science graduate from Cornell University. He has previously worked and interned at Google, Facebook and Coursera. In this podcast we talk about various computer science roles in industry: research, software engineering, product management, and doing a PhD or not.
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Dec 28, 2020
Applying for Google Residency & role of a Resident | Sara Hooker @Google -Brain
Watch the full episode with Sara here: https://youtu.be/MHtbZls2uts
Sara is a research scholar at @Google-Brain team working on building interpretable machine learning models for reliability and robustness. We talk about how she transitioned from economics to now pure research at the Brain team. We also talk in detail about what interpretability means, what are the state-of-art techniques, and what are some of the most important things any machine learning researcher must know.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not n…
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Dec 16, 2020
Using Artificial Intelligence for Climate Change | Sharon Zhou @Stanford
Sharon is a Stanford Computer Science Ph.D. student advised by Andrew Ng and Michael Bernstein working on generative models. Popularly known for her Coursera course on building GANs, she talks more about the use of AI in medicine, what product management is about, some philosophical fun chat and interpretability, and the future of AI in healthcare.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Dec 12, 2020
AI for Medicine & Climate Change GANs, Product & Time Management | Sharon Zhou @Stanford
Sharon is a Stanford Computer Science Ph.D. student advised by Andrew Ng and Michael Bernstein working on generative models. Popularly known for her Coursera course on building GANs, she talks more about the use of AI in medicine, what product management is about, some philosophical fun chat, and interpretability, and the future of AI in healthcare.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Dec 4, 2020
Self taught ML Researcher @Google -Brain, on Interpretability & more | Sara Hooker
Sara is a research scholar at the Google-Brain team working on building interpretable machine learning models for reliability and robustness. We talk about how she transitioned from economics to now pure research at the Brain team. We also talk in detail about what interpretability means, what are the state-of-art techniques, and what are some of the most important things any machine learning researcher must know.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.*…
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Nov 22, 2020
Siddha Ganju, Forbes 30 Under 30 and Self-Driving Architect @NVIDIA
Siddha is a self-driving architect at NVIDIA and she also guides teams at NASA as an AI domain expert . She was featured on the Forbes 30 under 30 list in 2019.
Previously, she developed deep learning models for resource-constrained edge devices at DeepVision. She earned her Master's degree from Carnegie Mellon University, and her work ranges from visual question answering to generative adversarial networks to gathering insights from CERN’s petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS.
In this interview she shares her insights on:
1. How she got started with the domain ML and Computer Vision.
2. How graduate study and internships helped her gain a perspective of theoretical and practical knowledge in AI.
3. How she keeps herself updated to this every-day changing research domain.
4. What her book, she recently wrote, is about and who should read it.
5. What are the new trends to look for in AI in 2020 and forward.
6. General advice t…
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Nov 18, 2020
A day in the life on an Applied ML Researcher | Shreya Shankar @Stanford
Full podcast with Shreya available here: https://www.youtube.com/watch?v=LojomxFnjBY&t=439s
Shreya is currently a graduate student @Stanford and also working as an ML engineer @Viaduct.ai. She has previously interned at @Google -Brain and @Facebook . She talks about her experience as an applied ML engineer and making ML models work in the real-world.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affil…
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Nov 16, 2020
Barkha Bhojak, SDE @LinkedIn - Getting Jobs/Internships in States
Barkha shares her experience and useful tips for landing good jobs and internships in the CS domain in the states, starting from being a Deputy Convener of Student Placement Cell in DAIICT, India to being an intern at Intuit and an SDE at LinkedIn.
Learn more about her: https://www.linkedin.com/in/barkhabhojak/
Our aim of these webinars is to connect you with the brightest minds in the field of CS/Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Nov 5, 2020
Best resources to remain updated to Machine Learning Research | Siddha Ganju, @NVIDIA
Siddha is a self-driving architect at NVIDIA and she also guides teams at NASA as an AI domain expert. She was featured on the Forbes 30 under 30 list in 2019.
Previously, she developed deep learning models for resource-constrained edge devices at DeepVision. She earned her Master's degree from Carnegie Mellon University, and her work ranges from visual question answering to generative adversarial networks to gathering insights from CERN’s petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS.
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 31, 2020
Vidhan Agarwal, AI & ML Research @Microsoft
Vidhan shares what intrigued him about Machine Learning as a student at CMU and how he built up his profile learning from experiences and exploring landing him a job in research at Microsoft.
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 29, 2020
Interviewing for Machine Learning roles in 2020 | Debarghya Das (Deedy) Ex- @Google
Full episode with Deedy available here: https://youtu.be/Vn79br3mKZM
Debarghya (Deedy) currently a Founding Engineer at a Stealth Startup is a computer science graduate from Cornell University. He has previously worked and interned at Google, Facebook and Coursera. In this podcast we talk about various computer science roles in industry: research, software engineering, product management, and doing a PhD or not.
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 26, 2020
Machine Learning in Academic Research vs Industry | Shashank Bhushan @Google
Full episode with Shashank available here: https://youtu.be/jysvEYGggFE
About the Speaker:
Shashank works with several other Machine Learning Engineers at @Google on Computer Vision and Perception projects. He graduated from@Arizona State University in 2018 and has a great experience working in various domains of Machine Learning and Data Science.
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.*…
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Oct 1, 2020
Ajinkya Kolhe, Data Engineering & ML Instructor @Google Cloud
As a Machine Learning Instructor, Ajinkya talks about how building applications and complementing your engineering skills with creativity and interest is more important than merely focusing on the mathematics of algorithms. And that is what the new every day changing ML industry might demand!
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 1, 2020
Ganesh Iyer, AI Engg@MGH & BWH Center for Clinical Data Science
Ganesh works at MGH and BWH Center for Clinical Data Science, revolutionizing healthcare using Artificial Intelligence. He has experience working with Deep Learning algorithms, Data Visualizations and scalable distributed systems.
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 1, 2020
Jineet Doshi, Data Scientist @Intuit
Jineet, a Data Scientist at Intuit and a graduate from Carnegie Mellon University shares some amazing insights about data science and machine learning probing his experiences.
LinkedIn: https://www.linkedin.com/in/jineetdoshi/
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Oct 1, 2020
Shraddha Patel, AI Consultant @Servian
Why being a Tech-God is not enough. Thoughts from Shraddha Patel, CMU Grad, and a Business Analytics Consultant at Servian, Australia.
Our aim of these webinars is to connect you with the brightest minds in the field of Machine Learning/Data Science so that you can learn how to break into the field and build an incredible career!
About the Speaker:
Shraddha is a recent graduate of CMU with a focus on Business Intelligence and Data Analytics. She has work experience as a Software Development Engineer and Machine Learning Engineer and shared with us some of the insights as she paved her way to being a consultant.
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an…
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Sep 29, 2020
Shashank Bhushan, Software Engineer(ML) @Google
Shashank works with several other Machine Learning Engineers at Google on Computer Vision and Perception projects. He graduated from Arizona State University in 2018 and has great experience working in various domains of Machine Learning and Data Science.
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Sep 28, 2020
Vaibhavi Desai, Community Manager@Google
Vaibhavi Desai, Community Manager, Developer Relations Southeast Asia at Google. She designs programs on Machine Learning and Data Science at Google, working with several Machine Learning Engineers and nurturing communities around various other developer programs.
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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Sep 17, 2020
Devanshu Jain, Software Engineer@YouTube
Interview with Devanshu Jain, Software Engineer at YouTube, on our first episode of Machine Learning for Beginners!
Our aim of these webinars is to connect you with the brightest minds in the field of ML/DS so that you can learn how to break into the field and build an incredible career!
Speaker:
Devanshu works on Home Page recommendations at YouTube and has held experience working in Uber and Amazon before.
Hosted by:
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
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