Sep 9–12, 2019
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Ankur Taly

Ankur Taly
Head of Data Science, Fiddler


Ankur Taly is the head of data science at Fiddler, where he’s responsible for developing, productionizing, and evangelizing core explainable AI technology. Previously, he was a staff research scientist at Google Brain, where he carried out research in explainable AI and was most well-known for his contribution to developing and applying integrated gradients— a new interpretability algorithm for deep networks. His research in this area has resulted in publications at top-tier machine learning conferences and prestigious journals like the American Academy of Ophthalmology (AAO) and Proceedings of the National Academy of Sciences (PNAS). Besides explainable AI, Ankur has a broad research background and has published 25+ papers in areas including computer security, programming languages, formal verification, and machine learning. He’s served on several academic conference program committees (PLDI, POST, and PLAS), delivered several invited lectures at universities and various industry venues, and instructed short courses at summer schools and conferences. Ankur earned his PhD in computer science from Stanford University and a BTech in CS from IIT Bombay.


2:35pm3:15pm Thursday, September 12, 2019
Location: LL21 A/B
Secondary topics:  Ethics, Security, and Privacy
Ankur Taly (Fiddler)
Average rating: *****
(5.00, 4 ratings)
As machine learning (ML) models get deployed to high-stakes tasks like medical diagnosis, credit scoring, and fraud detection, an overarching question that arises is why the model made its prediction. Ankur Taly explores techniques for answering this question and applications of the techniques in interpreting, debugging, and evaluating machine learning models. Read more.
  • Intel AI
  • O'Reilly
  • Amazon Web Services
  • IBM Watson
  • Dataiku
  • Dell Technologies
  • Intuit
  • Gamalon
  • Hewlett Packard Enterprise
  • MapR Technologies
  • Sisu Data
  • Intuit

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