Kavya Gupta

Postdoc, Saarland University

kavya.jpeg

Postdoctoral Researcher at Saarland University with Prof. Isabel Valera, working on Society-Aware Machine learning.

Ph.D. Graduate specializing in the Robustness of neural networks from Ecole CentraleSupelec, University of Paris-Saclay and funded by Thales LAS France. I was advised by Prof. Jean-Christophe Pesquet. My thesis revolves around Lipschitz Constant Analysis of Neural Networks for certified Robustness and adversarial machine learning. I am interested in the Robustness, trustworthiness, and reliability of neural networks.

Before moving to France, I worked at Tata Consultancy Services Research and Innovation (2016-2019), Kolkata, India. I worked in Robotics and Vision Group. I worked on 2D and 3D human pose estimation from monocular videos, object detection and classification, inverse problems for removing blur in images captured from fast-moving drones, and rendering personalized realistic facial animation of an avatar using 3D Face meshes synced with audio.

I completed my M.Tech in Electronics and Communication Engineering with specialization in Communication and Signal Processing from IIIT-Delhi and was a member of SALSA Research Lab (Batch 2014-2016). I did my master’s thesis on Regularized Autoencoders under the guidance of Dr. Angshul Majumdar. I also worked on compressive sensing and collaborative filtering.

Research Interests

  • Society-Centered AI, Robust and Interpretable AI

  • Causality-driven Decision-Making

  • Multi-objective Optimization

  • Formal guarantees of robustness of neural networks

news

Nov 13, 2024 Will be attending the Transform4Europe Matching Event in St-Etienne France.
Jul 1, 2024 New paper Fairness Beyond Binary Decisions: A Case Study on German Credit, EWAF, 2024.
Mar 1, 2024 Started as a Postdoctoral reseacher at Saarland University with Prof. Isabel Valera.
Jul 31, 2023 Our paper won “Most innovative Solution” award in ChaBuD Competition ECML-PKDD 2023.
Jul 20, 2023 Presenting two papers on Certified Robustness in Frontiers in Adversarial Machine learning (AdvML) at ICML 2023.