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Information Theory and its applications in communication, combinatorics, computer science, and statistics
Jaikumar Radhakrishnan
Distinguished Professor International Centre for Theoretical Sciences (ICTS-TIFR), Bengaluru
Abstract: We will begin by discussing the problem of information transmission and the main theorems of Shannon. We will introduce fundamental information theoretic quantities such as entropy, conditional entropy, relative entropy and mutual information and review the inequalities relating these quantities. Finally, we will present applications of the standard information theoretic inequalities in combinatorics, computer science and statistics. We will assume some familiarity with the basics of probability, but otherwise our discussion will be self-contained.
Bio: Jaikumar Radhakrishnan is a theoretical computer scientist with research interests in complexity theory, randomness and computation, quantum information and computation, combinatorics, and information theory. Radhakrishnan obtained his BTech in Computer Science and Engineering from IIT Kharagpur in 1985, and his PhD in Computer Science from Rutgers University, NJ, USA, in 1991. He joined the Tata Institute of Fundamental Research in 1991; in 2024 he moved to the International Centre for Theoretical Sciences (ICTS-TIFR), Bengaluru.
A Short Course on Economics and Computation
Rohit Vaish
Assistant Professor Department of Computer Science and Engineering, Indian Institute of Technology Delhi
Abstract: The course will provide an introduction to algorithmic game theory, which focuses on the design and analysis of algorithms in strategic environments. We will start by examining various types of "real-life" games, understanding the role that algorithms play in these situations, and exploring how incorrect incentives can lead to suboptimal outcomes. Following that, we will discuss some fun problems in the related area of computational social choice, including how computer science can prevent strategic manipulation in elections, and how to set up dates that are provably free of breakups.
Bio: Rohit Vaish is an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Delhi. His research is at the interface of computer science and economics, specifically in the area of computational social choice. He explores collective decision-making scenarios, including voting, matching, and fair division, through a computational lens.
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- March 13, 2026:
- Jaikumar Radhakrishnan: 10:00 AM - 11:00 AM, 11:30 AM to 12:30 PM (Information Theory)
- Rohit Vaish: 2:30 PM-3:30 PM, 4:00 PM-5:00 PM (Algorithmic Game Theory)
- March 14, 2026:
- Rohit Vaish: 10:00 AM - 11:00 AM, 11:30 AM to 12:30 PM (Algorithmic Game Theory)
- Jaikumar Radhakrishnan: 2:30 PM-3:30 PM, 4:00 PM-5:00 PM (Information Theory)
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Information Theory and its applications in communication, combinatorics, computer science, and statistics
Jaikumar Radhakrishnan
Distinguished Professor International Centre for Theoretical Sciences (ICTS-TIFR), Bengaluru
Abstract: We will begin by discussing the problem of information transmission and the main theorems of Shannon. We will introduce fundamental information theoretic quantities such as entropy, conditional entropy, relative entropy and mutual information and review the inequalities relating these quantities. Finally, we will present applications of the standard information theoretic inequalities in combinatorics, computer science and statistics. We will assume some familiarity with the basics of probability, but otherwise our discussion will be self-contained.
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A Short Course on Economics and Computation
Rohit Vaish
Assistant Professor Department of Computer Science and Engineering, Indian Institute of Technology Delhi
Abstract: The course will provide an introduction to algorithmic game theory, which focuses on the design and analysis of algorithms in strategic environments. We will start by examining various types of "real-life" games, understanding the role that algorithms play in these situations, and exploring how incorrect incentives can lead to suboptimal outcomes. Following that, we will discuss some fun problems in the related area of computational social choice, including how computer science can prevent strategic manipulation in elections, and how to set up dates that are provably free of breakups.
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Schedule:
- March 13, 2026:
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- Rohit Vaish: 2:30 PM-3:30 PM, 4:00 PM-5:00 PM (Algorithmic Game Theory)
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- Jaikumar Radhakrishnan: 2:30 PM-3:30 PM, 4:00 PM-5:00 PM (Information Theory)
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