Sajib Acharjee Dip
Welcome!
I am a Computer Science Ph.D. student at Virginia Tech, advised by Professor Liqing Zhang. My research spans large language models, post-training and reinforcement learning, multimodal learning, and agentic AI, with applications in biology, medicine, and scientific discovery.
I build verifier-guided learning methods, tool-using agents, foundation-model systems, and scalable Python/PyTorch pipelines. My recent biological AI work studies computational pathology, single-cell perturbation modeling, multi-omics integration, and reliable scientific agents.
Recent news
Selected published work
CFM-GP: Unified Conditional Flow Matching to Learn Gene Perturbation Across Cell Types
NAR Genomics and Bioinformatics, 2026.LLM4Cell: Taxonomy and Evaluation of LLM and Agentic Models for Single-Cell Biology
ACL 2026, Main Conference.Large Language Model Agents for Biological Intelligence Across Genomics, Proteomics, Spatial Biology, and Biomedicine
Briefings in Bioinformatics, 2026.Cross-species plant single-cell analysis: community challenges and shared solutions
Journal of Experimental Botany, 2026.Patch-Level Tissue Context Improves Learning from Frozen Pathology Foundation Model Embeddings
ACM BCB 2026.PathoLM: Identifying Pathogenicity from the DNA Sequence Through the Genome Foundation Model
19th Machine Learning in Computational Biology Meeting (MLCB 2024).
See the complete curated list on the Publications page.
