Scholar
KHUSHBU PAHWA
Google Scholar ID: k4fsE1YAAAAJ
University of California Los Angeles, Delhi Technological University
Citations & Impact
Citations
154
H-index
6
i10-index
6
Publications
20
Co-authors
8
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- 1 research paper accepted at EMNLP 2023: FACTIFY3M: A benchmark for multimodal fact verification with explainability through 5W Question-Answering; Research Paper: “GnnX-Bench: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking” is live on ArXiv; Awarded the Ken Kennedy Institute Computational Science & Engineering Recruiting Fellowship; Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing accepted for poster presentation at KDD 2023 Federated Learning Workshop; Research Paper “Neural Architecture of Speech” accepted for Oral Presentation at ICASSP 2023.
Research Experience
- During her time at UCLA, she was involved in various research projects including depression detection from speech while preserving speaker identity with Dr. Abeer Alwan; fast and learnable measurement-conditioned undersampled MR image reconstruction using Diffusion models with Dr. Dan Ruan; comprehensively evaluating the adversarial robustness of tiny ML models with Dr. Nader Sehatbaksh; and developing computationally efficient gradient-based white-box adversarial attacks against text transformers with Dr. Cho-Jui Hsieh. Additionally, she has collaborated on research works with Prof. Pengtao Xie (UCSD), Prof. Amitava Das (AI Institute at UoSC), Prof. Sourav Medya (UIC), and Dr. Manish Gupta (Microsoft R&D). In the summer of 2022, she interned as an Applied Scientist Intern at Amazon AWS Machine Learning Solutions Lab.
Education
- Master's degree in Electrical & Computer Engineering from University of California, Los Angeles; Bachelor's degree from Delhi Technological University, awarded the Vice Chancellor Gold Medal for academic and research excellence.
Background
- Research interests include efficient and trustworthy machine learning for foundation models, with a special interest in healthcare applications. Broadly interested in the domain of Multi-Modal Learning, Robust Deep Learning, and Trustworthy AI.
Miscellany
- Personal motto: 'कर्मण्येवाधिकारस्ते मा फलेषु कदाचन। मा कर्मफलहेतुर्भूर्मा ते संगोऽस्त्वकर्मणि॥ - To perform one's duties diligently and with dedication without attachment to the outcomes.'
