Prof. Vineeth N Balasubramanian
Professor, IIT Hyderabad
Prof. Vineeth N Balasubramanian is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Hyderabad (IIT-H). His research interests include deep learning, machine learning, and computer vision. His research has resulted in many publications in several top conferences and journals including ICML, CVPR, NeurIPS, ICCV, AAAI, TPAMI, etc. His Ph.D. dissertation at Arizona State University on the Conformal Predictions framework was nominated for the Outstanding Ph.D. Dissertation at the Department of Computer Science.
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Dr. Pratyay Mukherjee
Senior Director of Research,
Supra
Dr. Pratyay Mukherjee is currently a Senior Director of Research at Supra. Previously he worked as a Senior Research Scientist at Swirlds Labs, a Research Scientist (and later a Senior Research Scientist) at Visa. Even before that he has been a Postdoc at EECS, UC Berkeley. He obtained his PhD from Aarhus University in 2015, M Tech in Comp Sc and Eng. from IIT Kharagpur in 2011, and B.E. in Electronic and Telecom. from Jadavpur University in 2008. His primary area of research is theoretical and applied cryptography. His research focuses on analyzing, designing and formalizing practical cryptographic problems using theoretical tools and framework.
Rolling a dice on Blockchain
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Randomness is an important resource in computing. In the blockchain/web3 space, many decentralized finance (DeFi) and particularly gaming applications, such as Lottery, Poker etc. crucially require a good source of randomness. In this setting generating good randomness is particularly non-trivial -- this is because the typical source of randomness relies on (computation on) private source, and it is notoriously hard to support private computation on blockchain. Therefore, off-chain private sources are used. However, one needs to ensure that the off-chain randomness sources perform the task correctly in order to ensure crucial properties, such as unpredictability, unbiasbaility etc. This leads to a new requirement, namely public verifiability, which guarantees that each randomness can be verified publicly. Typically, this is ensured by deploying a cryptographic object, known as verifiable random functions (VRF). While many existing on-chain VRF services satisfy the crucial requirements mentioned above, they often become too expensive to use. In this talk, I am going to mainly speak about a new design for providing on-chain randomness service, known as FlexiRand, in that we show how we can leverage output privacy of VRFs to ensure a flexible design which enables cost amortization, flexibly. At the same time, I plan to also mention a few on-going works on decentralized Poker, a few plausible vulnerabilities in the existing framework, and some new ideas we have for further improvements.
Dr. Shivaram Kalyanakrishnan
Associate Professor, IIT Bombay
Dr. Shivaram Kalyanakrishnan is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay. His research interests include artificial intelligence and machine learning, spanning topics such as sequential decision making, multi-agent learning, and multi-armed bandits. Application areas for his work include various computer games, robot soccer, railway scheduling, and finance. Kalyanakrishnan received a Ph.D. in computer science from the University of Texas at Austin. Subsequently he was a Research Scientist at Yahoo Labs Bangalore and an INSPIRE Faculty Fellow at the Indian Institute of Science.
On Designing a Winning Agent for Reconnaissance Blind Chess
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Reconnaissance Blind Chess (RBC) is a variant of Chess in which playerscan only sense a 3 x 3 grid within the 8 x 8 Chess board before they playtheir move. This restriction makes RBC a game of imperfect information, with many new challenges to address. In this talk, I present Fianchetto, our agent that won the NeurIPS 2021 RBC competition by a large margin, and finished runner-up at NeurIPS 2022. Fianchetto builds on the publicly-available code base of StrangeFish (the 2019 winner), and incorporates changes such as a faster board evaluation module, Bayesian belief updating, and incentives for strategic RBC moves. I discuss how elements of our solution may generalise to other games of imperfect information, and outline topics for future research.
Mr. Shireesh Joshi
Chief Business Officer & President,
Open Network For Digital Commerce (ONDC)
Mr. Shireesh Joshi is Chief Business Officer & President for Open Network For Digital Commerce (ONDC). He is responsible for expanding the network in terms of participants and domains. Previously he held roles with Procter & Gamble, PepsiCo, Airtel and Godrej, where he managed multiple brands, geographies and market positions simultaneously and worked on businesses across India, China and South Asia, working with various cultures and languages and has over 30 years of experience delivering successful results with organisations and teams of varying capability and scale. An industry and function leader, he often speaks at industry conferences, and serves on various marketing award juries. He is an alumnus of IIT Kanpur and IIM Bangalore.
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Dr. Ashutosh Modi
Assistant Professor, IIT Kanpur
Dr. Ashutosh Modi is an Assistant Professor at Computer Science and Engineering (CSE) department, Indian Institute of Technology Kanpur. His main area of research is Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI). Previously, He worked at Disney Research (DR), (erstwhile) Pittsburgh, Los Angeles and Zurich. At DR, He conducted research in multi-modal Affective computing, Conversational Systems and Natural Language Understanding (NLU). He did his Ph.D. at Saarland University, Germany under the supervision of Prof. Dr. Manfred Pinkal and Dr. Ivan Titov, and associated with Department of Computational Lingusitics, MultiModal Cluster Initiative (MMCI) and Department of Computer Science.
Dr. Venkata Vivek Kumar Koppula
Assistant Professor, IIT Delhi
Dr. Venkata Vivek Kumar Koppula is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Delhi (IIT-D). He is interested in the theoretical aspects of cryptography, with a focus on lattice based crypto, and more recently, in quantum cryptography. He did his undergrad at IIT Kanpur, followed by Ph.D. at University of Texas, Austin, advised by Brent Waters, after which he did a postdoc at Weizmann Institute (hosted by Zvika Brakerski).
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Dr. Subhra Mazumdar
Assistant Professor, IIT Indore
Dr. Subhra Mazumdar is an Assistant Professor at the Department of Computer Science & Engineering, Indian Institute of Technology Indore, India. Before this, she worked as a Project Assistant in Prof. Matteo Maffei's group (Security and Privacy) at Vienna University of Technology from August, 2022. She completed her PhD in 2022 from Indian Statistical Institute Kolkata, under the supervision of Prof. Bimal Roy and Dr. Sushmita Ruj. Her research interests are Applied Cryptography, Blockchain and Cryptocurrencies.