Nirav Diwan

I am a 2nd year research-track Master in Computer Science (MS CS) student at the University of Illinois, Urbana-Champaign. I am interested in the real-world applications of Trustworthy Machine Learning (TML), Natural Language Processing (NLP), and Security & Privacy. My work in these areas has been published in ACL, USENIX Security Symposium, ICWSM, and ICDE Workshop.

I am presently working with Prof. Gang Wang on Adversarial Machine Learning with a focus on Foundation Models. Previously, I have worked on watermarking fine-tuned LLM-generated text (ACL Findings’21) with Prof. Zubair Shafiq (UC Davis) and Prof. Tanmoy Chakraborty (IIT Delhi). I am a Graduate Teaching Assistant for CS124: Introduction to Computer Science course this semester (Fall 2023).

Before my MS, I graduated with a B. Tech. degree in Computer Science from IIIT Delhi in June 2021, where I worked in Natural Language Processing (NLP), Graphs and Security & Privacy (S&P). I was an member of LCS2 and the Complex Systems Lab. I worked on identifying anomalies in the YouTube Blackmarket Network using Graphs (ICSWM’22). I also led the information retrieval team for RecipeDB - a worldwide repository of recipes (ICDE Workshop, Oxford University Press).

I was an Applied Science intern at Ema Unlimited in summer (2023). I worked with the Generative AI Team on converting Natural language to SQL Commands. I have also worked as a Natural Language Processing (NLP) Engineer at Prodigal Technologies for a year, where I worked on problems of Dialogue State Tracking (DST), Information Retrieval (IR) and Optimizing Search Queries with a specific focus on finance-related conversations. Additionally, I have interned at TCS Research and Centre de Sciences Humanities (CSH Delhi).