Curriculum Vitae
Bishal Shrestha
Doctoral Researcher in Computer Science, University of Miami
Research
AI for structural biology, structure-centric multimodal foundation models, deep learning for biomolecular structure prediction (proteins, protein-RNA complexes, 3D genome), geometric deep learning and graph transformers, generative models for molecular design, protein function annotation, and translating structural and experimental data into scalable model architectures for biology.
Education
Ph.D. in Computer Science
Aug 2023 - PresentUniversity of Miami · Coral Gables, FL
- Advisor: Dr. Zheng Wang
B.E. in Computer Engineering
Jun 2017 - Jan 2022Tribhuvan University · Nepal
- Undergraduate thesis mentor: Dr. Badri Adhikari (University of Missouri–St. Louis)
Experience
Research Assistant
Aug 2023 - PresentUniversity of Miami · Coral Gables, FL
- Led ARC (first author, under review at PROTEINS): an ensemble of graph neural networks estimating per-residue local accuracy of predicted protein structures, developed for CASP16.
- Applied Geometric Algebra Transformers (GATr) to annotate protein function from 3D structure via E(3)-equivariant geometric deep learning on atomic coordinates.
- Co-developed a graph transformer to assess predicted protein-RNA complex structures, published in Bioinformatics (2026).
- Built HiC4D-SPOT (first author): a ConvLSTM-based autoencoder detecting spatiotemporal anomalies in 3D chromatin (Hi-C) data, published in Briefings in Bioinformatics (2025).
- Built scHiGex (first author): a graph transformer predicting single-cell gene expression from single-cell Hi-C 3D structure, published in NAR Genomics and Bioinformatics (2025).
- Contributed to SCW (BMC Bioinformatics 2026) and the CITED2 study (EMBO Molecular Medicine 2026).
Research Intern
Sep 2021 - Aug 2022University of Missouri–St. Louis · MO
- Researched adversarial sample generation for Nepal's embossed license-plate recognition, using adversarial training to harden models against attacks.
- Designed CNN experiments in PyTorch, including collecting and preprocessing a novel real-world dataset.
Undergraduate Researcher
Apr 2021 - Sep 2021Research and Innovation Unit, Tribhuvan University
- Studied machine-learning techniques for customer-churn prediction with a leading Nepali ISP.
- Presented findings at the Himalaya International Conference on academia-industry partnerships.
Publications
- Shrestha B, Siciliano AJ, Huang G, Bao Y, Wang Z. ARC: Assessment of Interface Residue Conformation using an Ensemble of Graph Neural Networks. PROTEINS: Structure, Function, and Bioinformatics, Manuscript ID 5704351. 2026 (under review).
- Siciliano AJ, Bao Y, Shrestha B, Wang Z. Inferring the qualities of protein-RNA models with graph transformers. Bioinformatics, 2026. 2026.
- Müller F, McLachlan E, Costa A, Qu J, Shrestha B, Wang Z, et al.. CITED2 is a druggable epigenetic switch coupling neuronal maturation to regenerative decline. EMBO Molecular Medicine, 2026. 2026.
- Zhu H, Liu T, Shrestha B, Wang Z. SCW: building the whole-genome 3D structures based on extremely sparse single-cell Hi-C data. BMC Bioinformatics, 27(1), 90. 2026.
- Shrestha B, Wang Z. HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data. Briefings in Bioinformatics, 26(4), bbaf341. 2025.
- Shrestha B, Siciliano AJ, Zhu H, Liu T, Wang Z. scHiGex: predicting single-cell gene expression based on single-cell Hi-C data. NAR Genomics and Bioinformatics, 7(1), lqaf002. 2025.
- Shrestha B, Khakurel G, Simkhada K, Adhikari B. Adversarial sample generation and training using geometric masks for accurate and resilient license plate character recognition. arXiv preprint, cs.CV. 2023.
- Prajapati S, Engelhardt M, Shrestha A, Khakurel G, Shrestha B, Simkhada K. Industry-Academia Collaboration in Nepal, A case study of Customer Churn Prediction for Worldlink. Research and Innovation Unit, 2021.
Teaching
- CSC402, Computer Science Practicum II · Graduate Teaching Assistant · Spring 2024-2025 · Evaluations 4.9/5 and 4.8/5.
- CSC314, Computer Organization & Architecture · Visiting Lecturer (Fall 2024, Spring 2025) and Graduate TA (Spring 2026).
- CSC113/CSC200, Data Science for the World · Graduate Teaching Assistant · Fall 2023.
Service
- Reviewer, ISMB (Intelligent Systems for Molecular Biology)2026
- Participant, CASP16, community-wide blind structural assessment2024-2025
Skills
- Languages
- PythonCC++
- ML frameworks
- PyTorchPyTorch GeometricTensorFlowscikit-learnNumPyPandas
- Deep learning
- Graph Neural Networks · Graph Transformers · E(3)-equivariant / Geometric Algebra Transformers · ConvLSTM · Autoencoders · Generative models
- Structural & computational biology
- Protein structure prediction & quality assessment (CASP) · Protein function annotation from 3D structure · Protein-RNA complex modeling · 3D genome / Hi-C analysis · Single-cell Hi-C & gene-expression integration · Bioinformatics pipelines
- Visualization
- Matplotlib · Seaborn
Presentations
- 2026ARC: Assessment of Interface Residue Conformation using an Ensemble of Graph Neural Networks, Computing Day, University of Miami (May 2026).
- 2025HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data, Computing Day, University of Miami (April 2025).
- 2024Predicting single-cell gene expression from single-cell Hi-C using a graph transformer, Computing Day (April 2024) & Sylvester Comprehensive Cancer Center Annual Retreat (Oct 2024).
Certifications
Mathematics for Machine Learning, Imperial College London · Neural Networks and Deep Learning, Coursera · Qiskit Global Summer School, IBM