Scholar
Md Osman Gani
Google Scholar ID: _FmDHygAAAAJ
University of Maryland Baltimore County
Citations & Impact
Citations
458
H-index
11
i10-index
13
Publications
20
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'Learning What Matters: Causal Time Series Modeling for Arctic Sea Ice Prediction' accepted at AI for Time Series Analysis Workshop, IJCAI-25 (August 2025)
- Paper 'TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery' accepted at KDD 2025
- Three papers accepted at the 1st Causal AI for Robust Decision Making Workshop, IEEE PerCom 2025
- Paper 'LLM-based Corroborating and Refuting Evidence Retrieval for Scientific Claim Verification' accepted at AAAI-25 Workshop (February 2025)
- Paper on time series classification of supraglacial lakes over Greenland ice sheet accepted at ICMLA 2024
- Research funded by NSF, NIH, NIDILRR, and UMBC
Background
- Assistant Professor of Information Systems at the University of Maryland, Baltimore County (UMBC)
- Director of the Causal AI Lab at UMBC
- Faculty affiliate in Computer Science and Electrical Engineering at UMBC
- Member of the NSF HDR Institute for Harnessing Data and Model Revolution in the Polar Regions (iHARP)
- Research interests lie in machine learning (ML) and artificial intelligence (AI), with a strong focus on moving beyond correlation to uncover causal relationships
- Develops data-driven and knowledge-guided causal AI methods to improve causal discovery and inference from complex and biased observational data
- Applies these methods to healthcare (e.g., treatment effect estimation from EHR data), climate science (e.g., ice sheet melt modeling), natural language processing (e.g., hallucination detection in LLMs), and rehabilitation engineering (e.g., accessible navigation for wheelchair users)
- Integrates causal modeling, statistics, and ML to accelerate scientific discovery, inform policy, and design socially impactful technologies
