Research Experience
| 2023 – Present |
Graduate Student Researcher
University of California, Riverside — Dept. of Computer Science & Engineering
Conduct research on ML, representation learning, and generative modeling applied to protein
and antibody systems. Designed and fine-tuned protein language models and contrastive representation
learning frameworks to capture binding behavior and mutation-driven effects across antibody–antigen pairs.
Developed structure-aware learning approaches integrating sequence and 3D structural information.
Built generative and discriminative ML pipelines for antibody interaction modeling across large-scale
datasets (500K+ samples). Created SPICE,
a production-grade web platform for structural protein–protein interaction analysis (published in NAR, 2026).
Published in JCIM, PLOS ONE, Heliyon, AAAI, NeurIPS workshops.
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| Jun – Sep 2025 |
Machine Learning Intern — Bioinformatics R&D
Exact Sciences — San Diego, CA
Fine-tuned nucleotide transformer models to predict probe performance in hybrid-capture-based
cancer detection workflows. Analyzed large-scale experimental sequencing and assay data.
Implemented sensitivity- and specificity-aware evaluation metrics.
Trained predictive models achieving ~80% accuracy. Collaborated with interdisciplinary teams
spanning ML, experimental biology, and applied research.
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Teaching
| Jan – Mar 2024 |
Graduate Teaching Assistant
University of California, Riverside — Dept. of Computer Science & Engineering
Supported instruction for undergraduate courses in Database Systems and
Algorithmic Techniques in Bioinformatics. Led discussion sections, held office hours,
and provided project guidance.
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| 2018 – 2022 |
Lecturer — Dept. of Computer Science & Engineering
Brac University & Uttara University — Dhaka, Bangladesh
Independently taught core undergraduate CS courses for 4+ years.
Courses: Programming Language I & II, Discrete Mathematics, Data Structures,
Algorithms, Database Management Systems, Operating Systems, Artificial Intelligence.
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Academic Service
| 2026 | Reviewer — ACM BCB '26 |
| 2025–26 | Sub-reviewer — RECOMB '26 |
| 2024–25 | Sub-reviewer — ISMB 2025 |
| 2024 | Sub-reviewer — ISMB 2024 |
| 2023 | Sub-reviewer — ISMB 2023 |
| 2022–23 | Sub-reviewer — RECOMB '23 |
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Skills
| Core Research | Protein Language Models · Structure-Aware Learning · Ab–Ag Binding Prediction · Generative Modeling · Mutation Effect Modeling |
| ML & AI | Transformers · LLMs · GNNs · Contrastive Learning · Representation Learning |
| Frameworks | PyTorch · HuggingFace · PyTorch Geometric · TensorFlow · scikit-learn |
| Bio & Structure | AlphaFold · ESMFold · Biopython · PyMOL · PDB tools |
| Languages | Python · C/C++ · Java · Bash · SQL |
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