Rate My Professor Sunandan Chakraborty

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.