PDF last generated: February 10, 2026
Academic Services
Reviewer of Journal Briefings in Bioinformatics
Reviewer of Computational and Structural Biotechnology Journal
Reviewer of IEEE Transactions on Neural Networks and Learning Systems Journal
Program Committee Member of AAAI Artificial Intelligence for Social Impact 2025 & 2026.
Reviewer of Neurips 2025 (The Thirty-Ninth Annual Conference on Neural Information Processing Systems)
Education
PhD in Computer Science
University of Central Florida
- Thesis: Advancing Drug Discovery with Structural and Representation Learning of Biological Systems [Link](https://stars.library.ucf.edu/etd2024/515/)
- GPA: 3.91/4.0
MS in Computer Science
University of Central Florida
- GPA: 3.9/4.0
MS in Industrial Engineering
Sharif University of Technology
- GPA: 3.88/4.0
Research Experience
Graduate Research Assistant
University of Central Florida, Orlando, FL
- Conducted advanced research in computational drug discovery, focusing on drug-target interaction and algorithmic fairness.
- Developed and implemented machine learning models, including Transformers and Graph Neural Networks, for computer vision applications.
- Collaborated on multiple interdisciplinary projects, contributing to the advancement of AI methodologies in drug discovery.
- Published research findings in reputable journals and presented them at international conferences.
- Utilized tools such as Pytorch, TensorFlow, and Scikit-learn to develop and evaluate innovative algorithms.
- Engaged in data analysis and model optimization to enhance prediction accuracy and computational efficiency.
- Assisted in mentoring undergraduate and graduate students and contributed to the academic community through collaborative efforts and knowledge-sharing sessions.
Research Intern, Bio-LLMs
Microsoft, Redmond, WA
- Built a novel agent orchestration system for planning, tool use, and judgment.
- Explored agentic AI on deidentified clinical datasets with end to end experiments and evaluation.
- Developed a RAG retrieval stack with hybrid dense and sparse search, reranking, and citation attribution.
- Contributed to the development of evaluation metrics and benchmarks for agentic AI systems.
Data Science Intern, AI/ML for Drug Discovery
Johnson & Johnson (Janssen R&D)
- Developed and trained HELM (Hierarchical Encoding for mRNA Language Modeling), the first mRNA antibody language model, achieving up to 8% increase in prediction accuracy and enabling the generation of more diverse and biologically plausible sequences.
- Explored alternative attention architectures such as Mamba and Hyena, enhancing transformer model efficiency and effectiveness in processing mRNA sequences.
- Implemented large-scale distributed training on Kubernetes, resulting in significant reduction in training time for LLMs on extensive datasets, optimizing resource utilization and scalability.
- Collaborated with cross-functional teams to refine and deploy advanced LLM architectures, enhancing model accuracy and efficiency for large-scale data processing tasks.
Selected Publications
Equi-mRNA: Protein Translation Equivariant Encoding for mRNA Language Models
Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Ozlem Ozmen Garibay
Neurips 2025 · 2025 · DOI
BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Ozlem Ozmen Garibay
Advances in Bioinformatics · 2025 · DOI
HELM: Hierarchical Encoding for mRNA Language Modeling
Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi, Artem Moskalev, Rui Liao
ICLR 2025, Neurips 2024 Workshop on AI for New Drug Modalities · 2024 · DOI
Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium
Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, AmirArsalan Rajabi, Aida Tayebi, Ivan Garibay, Ozlem Ozmen Garibay
Neurips 2024 · 2024 · DOI
Learning Fair Representations: Mitigating Statistical Dependencies
Aida Tayebi, Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Niloofar Yousefi, Ozlem Ozmen Garibay
HCII conference 2023 Oral Presentation · 2024 · DOI
FragXsiteDTI: an interpretable transformer-based model for drug-target interaction prediction
Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi, Sina Abdidizaji, Ozlem Ozmen Garibay
Recomb 2024 (Oral), Neurips 2023 Workshop on New Frontiers of AI for Drug Discovery and Development · 2024 · DOI
Controlling the misinformation diffusion in social media by the effect of different classes of agents
Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Sina Abdidizaji, Ivan Garibay, Ozlem Ozmen Garibay
The Computational Social Science Society of the Americas Annual Conference · 2023 · DOI
Agent-Based Modeling of C. Difficile Spread in Hospitals: Assessing Contribution of High-Touch vs. Low-Touch Surfaces and Inoculations' Containment Impact
Sina Abdidizaji, Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Ozlem Ozmen Garibay, Ivan Garibay
The Computational Social Science Society of the Americas Annual Conference · 2023 · DOI
Through a fair looking-glass: on mitigating bias in image datasets
Amirarsalan Rajabi, Mehdi Yazdani-Jahromi, Ozlem Ozmen Garibay, Gita Sukthankar
HCII conference 2023 (Oral), AAAI 2023 Workshop on Representation Learning for Responsible Human-Centric AI · 2023 · DOI
BindingSiteAugmented DTA to enable A Next-Generation Pipeline for Interpretable Prediction Models in Drug-Repurposing
Niloofar Yousefi, Mehdi Yazdani-Jahromi, Aida Tayebi, Elayaraja Kolanthai, Craig J Neal, Tanumoy Banerjee, Agnivo Gosai, Ganesh Balasubramanian, Sudipta Seal, Ozlem Ozmen Garibay
Briefings in Bioinformatics · 2023 · DOI
AttentionSiteDTI: Attention Based Model for Predicting Drug-Target Interaction Using 3D Structure of Protein Binding Sites
Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi, Elayaraja Kolanthai, Craig J Neal, Sudipta Seal, Ozlem Ozmen Garibay
Briefings in Bioinformatics · 2022 · DOI
UnbiasedDTI: Mitigating Real-World Bias of Drug-Target Interaction Prediction
Aida Tayebi, Niloofar Yousefi, Mehdi Yazdani-Jahromi, Elayaraja Kolanthai, Craig J Neal, Sudipta Seal, Ozlem Ozmen Garibay
MDPI Molecules · 2022 · DOI
Skills
Summary
AI research scientist and PhD in Computer Science specializing in representation learning, with primary applications in computational biology and drug discovery. Industry experience at Johnson and Johnson and Microsoft, where I developed language models for mRNA and machine learning systems for large scale biomedical data. Strong programming background in Python, and JavaScript, with deep experience in PyTorch, Transformers and graph neural networks. Published in NeurIPS, ICLR and Briefings in Bioinformatics, with work spanning mRNA modeling, drug target interaction prediction and algorithmic fairness.