activity
20232026
most citedGenerative AI for Software Metadata: Overview of the Information Retrieval in Software Engineering Track at FIRE 2023

5 citations · 7 across the 5 of their papers we have counts for

collaborators

11 papers

cs.MA2026

Argonaut: Interactive Visual Exploration for Distributed Optimization

Srijoni Majumdar, Chuhao Qin, Evangelos Pournaras

Distributed discrete-choice optimization in decentralized settings is often hard to explore and navigate: disentangling what other agents choose, how their choices are interdepende…

cs.CY2026

Democracy in the Era of Artificial Intelligence

Evangelos Pournaras, Srijoni Majumdar, Carina Hausladen +1

Interfacing Artificial Intelligence (AI) with democracy is one of the most profound challenges of our times. On the one hand, AI comes with opportunities to overcome long-standing…

cs.SE2025

Leveraging Design-Aware Context in Large Language Models for Code Comment Generation

Aritra Mitra, Srijoni Majumdar, Anamitra Mukhopadhyay +3

Comments are very useful to the flow of code development. With the increasing commonality of code, novice coders have been creating a significant amount of codebases. Due to lack o…

cs.SI2025

Collective Intelligence Outperforms Individual Talent: A Case Study in League of Legends

Angelo Josey Caldeira, Sajan Maharjan, Srijoni Majumdar +1

Gaming environments are popular testbeds for studying human interactions and behaviors in complex artificial intelligence systems. Particularly, in multiplayer online battle arena…

cs.CY2025

Upgrading Democracies with Fairer Voting Methods

Evangelos Pournaras, Srijoni Majumdar, Thomas Wellings +4

Voting methods are instrumental design elements of democracies. Citizens use them to express and aggregate their preferences to reach a collective decision. However, voting outcome…

cs.AI2024

Generative AI voting: fair collective choice is resilient to LLM biases and inconsistencies

Srijoni Majumdar, Edith Elkind, Evangelos Pournaras

Recent breakthroughs in generative artificial intelligence (AI) and large language models (LLMs) unravel new capabilities for AI personal assistants to overcome cognitive bandwidth…