Rate My Professor Sunandan Chakraborty

Sunandan Chakraborty is an Associate Professor of Data Science at the Luddy School of Informatics, Computing, and Engineering, Indiana University Indianapolis, where he also serves as Program Director of Undergraduate Artificial Intelligence programs and co-director of the Data To Action Lab. Previously, he was Assistant Professor at the same institution from 2017 to 2024. He earned his Ph.D. in Computer Science from New York University in 2015, with a thesis on Big Data Analytics for Development: Events, Knowledge Graphs and Predictive Models, advised by Lakshminarayanan Subramanian. His M.S. is from the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur, and his B.Tech. in Computer Science & Engineering from the University of Kalyani, India. Earlier in his career, Chakraborty held a Moore-Sloan Postdoctoral Researcher position at the NYU Center for Data Science from 2015 to 2017, working on detecting illegal wildlife trade on the web with Jennifer Jacquet. He also completed research internships at Microsoft Research Labs in Cambridge, Silicon Valley, and India, focusing on projects such as novel evaluation techniques for information retrieval, diagnosing comprehension load in textbooks, and technology-based solutions for microfinance.

Chakraborty's research centers on data science for social good, employing big data analytics, machine learning, information extraction, and time series analysis on diverse datasets from news, social media, and images to tackle issues in computational sustainability, AI for conservation, AI in education, and computational social science. His interests include natural language processing, causality and text mining. He has secured multiple grants, including NSF awards for developing AI approaches for causal knowledge extraction ($174,000 in 2020), addressing causal dynamism ($216,000 in 2022), and a community-inclusive AI chatbot for culturally relevant STEM activities; other funding from Vulcan Inc. for cyber wildlife crime and NASA/INSGC for soil degradation assessment. Key publications encompass "Automated Knowledge Graph Construction using Large Language Models and Sentence Complexity Modelling" (EMNLP 2025), "Prevalence of endangered shark trophies in automated detection of the online wildlife trade" (Biological Conservation 2025), "Predicting Socio-Economic Indicators using News Events" (KDD 2016), and "Using transfer learning-based causality extraction to mine latent factors for Sjögren's syndrome from biomedical literature" (Heliyon 2023). He teaches courses such as Deep Learning Neural Networks (INFO-H 518), Applied Cloud Computing for Data Intensive Sciences (INFO-H 516), and Natural Language Processing with Deep Learning.