Palash Dey

Eminent Speaker

Short CV: Prof. Palash Dey is a faculty member in the Computer Science and Engineering department in IIT Kharagpur. His research focuses on computational social choice, game theory, algorithms, and parameterized algorithms. He has served as member of senior program committees and program committees of some of the top conferences in computer science, for example, AAAI, IJCAI, and AAMAS, etc. He has published more than 40 conference papers and 16 journal papers in reputed venues in computer science. He is a fellow of some reputed bodies like Indian National Academy of Engineers (INAE), West Bengal Academy of Science and Technology, etc. He has served as an invited speaker in many reputed workshops and conferences, including many ACM summer schools.

Title of Talk 1: Computational Social Choice for Making Society Better

Synopsis: Social choice theory refers to the broad set of areas where the goal is to come up with a collective decision from individual preferences, which is good for the society. An important problem in social choice theory is voting. With the use of voting theory into many AI based systems, the computational aspects of voting becomes challenging. In this talk, we will discuss the core challenges that the computational aspects brings to voting theory and how to overcome them.

Title of Talk 2: Election Prediction

Synopsis: Forecasting the result of an election generates significant interest prior to each pivotal vote. Various sources, including news outlets and other platforms, consistently offer their forecasts regarding the potential victor and the expected margin of victory. This presentation aims to delve into the scientific and mathematical principles underpinning such prognostications. Specifically, it will explore the essential considerations such as the necessary sample size of voters, optimal sampling methodologies, and related factors.

Title of Talk 3: Knapsack on Graphs

Synopsis: The knapsack problem is one of the most well-studied computationally intractable problems in computer science, both for its theoretical breakthrough and practical relevance. In this problem, we are given a set of items; each item has a size and a profit, and the goal is to select a subset of items of maximum total profit subject to an upper bound on the total size of the item in the subset. Indeed, this problem is at the core of a variety of applications like allocating advertisements to time slots, selecting investments and portfolios, etc. This talk will discuss various vital generalizations studied, the algorithmic techniques involved, and their practical use cases.

Palash Dey

Qualifications: PhD

Title: Assistant Professor

Affiliation: Indian Institute of Technology Kharagpur

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