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Short Courses Announcement
![](\"https://www.ashoka.edu.in/wp-content/uploads/2025/02/JaikumarICTS-1-scaled.jpg\")
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.
![\"\"](\"https://www.ashoka.edu.in/wp-content/uploads/2026/02/RohitVaish-298x300.jpg\")
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.
Schedule:
-
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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[post_content] => Eligibility: All Ashoka Students / Faculty
Requirements: Your laptop. It will be a workshop.
Registration : Just match our vibe !
Anand S https://www.linkedin.com/in/sanand0/
Bio: Anand studies how LLMs think. After completing his B Tech from IIT Madras (‘96) he worked at IBM. After his MBA from IIMB (‘01) he worked at BCG, Infosys Consulting and later founded Gramener ( A data visualization and analytics company). He also teaches Data Science at IIT Madras. And most importantly, he has transcribed every single Calvin & Hobbes strip. He codes data stories, blogs at https://s-anand.net, plays Minecraft, and enjoys anime.
[post_title] => Vibe Craft - Code & Build
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[post_date] => 2026-02-20 07:56:18
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[post_content] => Abstract: Code assistants powered by large language models have rapidly gained popularity, demonstrating impressive capability in generating small, well-scoped, greenfield code. However, their effectiveness drops sharply when applied to large, long-lived enterprise applications, where scale, legacy design patterns, and deep business logic pose significant challenges.
In this talk, we share insights from our experience building and evaluating IBM watsonx Code Assistant for Z on real-world, large-scale mainframe applications. We discuss the technical and architectural obstacles that arise in brownfield environments—such as program size, cross-program dependencies, legacy constructs, and domain-specific frameworks—and outline emerging opportunities and directions for making code assistants truly effective for enterprise modernization.
About the Speaker: Yogish Sabharwal is a Distinguished Engineer at IBM Research India, where he spearheads the AI for Code team. His leadership was pivotal in driving the core innovations behind the IBM watsonx Code Assistant for Z. With a career spanning over 25 years, Dr. Sabharwal has made significant contributions across the domains of Artificial Intelligence, High-Performance Computing, and networking.
He holds a Ph. D. from the Indian Institute of Technology (IIT) Delhi, specializing in approximation algorithms for computational geometry. Beyond his corporate leadership, he is a dedicated educator, and has served as adjunct faculty at IIT Delhi and Delhi University.
We look forward to your active participation.
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Short Courses Announcement
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.
Schedule:
-
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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