Md Hasebul Hasan
Scholar

Md Hasebul Hasan

Google Scholar ID: f8HAI_MAAAAJ
Department of Computer Science and Engineering, BUET
AI in HealthNLPCOMPUTER VISIONHCI
Citations & Impact
All-time
Citations
8
 
H-index
2
 
i10-index
0
 
Publications
5
 
Co-authors
9
list available
Resume (English only)
Academic Achievements
  • 1. Co-authored a paper accepted at ICML 2025 titled 'MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models'
  • 2. Published a paper at COMPSAC 2024 titled 'GuardFL: Detection and Removal of Malicious Clients Through Majority Consensus'
  • 3. Two preprints under review
  • 4. Master's thesis: 'AN EFFICIENT COMPOSITIONAL REASONING APPROACH FOR SOLVING GEOSPATIAL QUERIES USING LLMS', Supervisor: Dr. Mohammed Eunus Ali
  • 5. Bachelor's thesis: 'A MULTI-MODAL DEEP LEARNING BASED APPROACH FOR HOUSE PRICE PREDICTION'
Research Experience
  • 1. Co-authored a paper accepted at ICML 2025 titled 'MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models'
  • 2. Working with several professors for research purposes
  • 3. Served as a Machine Learning Engineer at IQVIA
  • 4. Worked as a part-time lecturer at Bangladesh University of Engineering and Technology
Education
  • 1. University of Texas at Arlington, Ph.D. in Computer Science and Engineering, August 2025 - August 2029
  • 2. Bangladesh University of Engineering and Technology, Master of Science in Computer Science and Engineering, June 2022 - August 2025, Supervisor: Dr. Mohammed Eunus Ali
  • 3. Bangladesh University of Engineering and Technology, Bachelor of Science in Computer Science and Engineering, February 2017 - May 2022
Background
  • Research interests include Human AI Interaction, NLP (focus on LLM), Agentic System, Applied Machine Learning (focus on health), and Computer Vision. Currently pursuing a Ph.D. in Computer Science and Engineering at the University of Texas at Arlington. Previously worked as a Machine Learning Engineer at IQVIA and served as a part-time lecturer at Bangladesh University of Engineering and Technology.