Curriculum Vitae

Mehdi Yazdani-Jahromi

Updated October 2026
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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 & 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 extensive 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.

Research Experience

Senior Research Scientist2026-01 – Present
DeepBio Scientific, Orlando, FL
  • Lead computational biology and drug discovery research by developing machine learning models and algorithms to analyze complex biomedical data.
  • Collaborate with cross-functional teams to translate research findings into scalable bioinformatics and computational drug discovery workflows.
  • Design and implement a state-of-the-art agentic AI system for retrieval and multi-step reasoning across biomedical datasets, enabling faster and more accurate analysis.
  • Develop benchmark datasets, evaluation metrics, and testing frameworks to assess model retrieval, reasoning, and predictive performance.
Research Intern, Bio-LLMs2025-06 – 2025-09
Microsoft, Redmond, WA
  • Built a novel agent orchestration system for planning, tool use, and judgment.
  • Explored agentic AI using de-identified clinical datasets through end-to-end experiments and evaluation.
  • Developed a Retrieval-Augmented Generation (RAG) stack integrating 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 Discovery2024-05 – 2024-11
Johnson & Johnson (Janssen R&D)
  • Developed and trained HELM (Hierarchical Encoding for mRNA Language Modeling), the first mRNA antibody language model, achieving up to an 8% increase in prediction accuracy and enabling the generation of more diverse and biologically plausible sequences.
  • Explored alternative to Attention architectures including Mamba and Hyena, to improve the efficiency and effectiveness of models processing mRNA sequences.
  • Implemented large-scale distributed training on Kubernetes, significantly reducing LLM training time on extensive datasets while improving 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.
Graduate Research Assistant2021-08 – 2025-12
University of Central Florida, Orlando
  • Developed Equi-mRNA (NeurIPS 2025), the first codon-level equivariant mRNA language model. It encodes synonymous-codon symmetries as SO(2) cyclic subgroups. It improved accuracy by up to ~10% on expression, stability and riboswitch prediction, and generated mRNA sequences ~4× more realistic than the baseline.
  • Proposed FairBiNN (NeurIPS 2024), which balances fairness and accuracy as a Stackelberg game solved with bilevel optimization. Contributed to fair representation learning work (HCII 2023 and 2024, both orals).
  • Built interpretable drug–target interaction models based on 3D protein binding sites: AttentionSiteDTI (Briefings in Bioinformatics 2022, first author): 5 of 7 predictions were confirmed in SARS-CoV-2 binding-inhibition assays with experimental collaborators. BindingSite-AugmentedDTA (Briefings in Bioinformatics 2023) and FragXsiteDTI (RECOMB 2024, oral): co-first author on both.
  • Lead inventor on a patent application for Equi-mRNA, filed in September 2025 through the UCF Office of Technology Transfer.
  • Entrepreneurial Lead, NSF I-Corps (UCF, Fall 2025 Health cohort), team GeneAI Therapeutics, commercializing Equi-mRNA as an AI platform for designing mRNA therapeutics.
  • Won a $30K Amazon Research Credit award (2023) and contributed technical content to NIH and NSF proposals.
  • Mentored undergraduate and junior graduate researchers in research methods, experimental design and software engineering. Guided lab members through projects that became co-authored papers: FragXsiteDTI, BoKDiff and two CSSSA 2023 papers.

Education

Ph.D. in Computer Science2021-01 – 2025-10
University of Central Florida
  • Thesis: Advancing Drug Discovery with Structural and Representation Learning of Biological Systems Link
  • GPA: 3.91/4.0
M.S. in Computer Science2021-01 – 2023-08
University of Central Florida
  • GPA: 3.9/4.0
M.S. in Industrial Engineering2017-09 – 2019-12
Sharif University of Technology
  • GPA: 3.88/4.0

Selected Publications

Equi-mRNA: Protein Translation Equivariant Encoding for mRNA Language Models2025
Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Ozlem Ozmen Garibay · Advances in Neural Information Processing Systems 38
HELM: Hierarchical Encoding for mRNA Language Modeling2025
Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi, Artem Moskalev, Rui Liao · International Conference on Learning Representations (ICLR 2025)
Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium2024
Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, AmirArsalan Rajabi, Aida Tayebi, Ivan Garibay, Ozlem Garibay · Advances in Neural Information Processing Systems 37
Learning Fair Representations: Mitigating Statistical Dependencies2024
Aida Tayebi, Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Niloofar Yousefi, Ozlem Ozmen Garibay · International Conference on Human-Computer Interaction
FragXsiteDTI: Revealing Responsible Segments in Drug-Target Interaction with Transformer-Driven Interpretation2024
Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi, Sina Abdidizaji, Ozlem Ozmen Garibay · International Conference on Research in Computational Molecular Biology
BindingSite-AugmentedDTA: enabling a next-generation pipeline for interpretable prediction models in drug repurposing2023
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
AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification2022
Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi, Elayaraja Kolanthai, Craig J Neal, Sudipta Seal, Ozlem Ozmen Garibay · Briefings in Bioinformatics

Awards

Nominated for Best Dissertation Award at the University of Central Florida
2025
Top Reviewer Award, NeurIPS 2025
2025
Received $30,000 Amazon Research Credits Award
2023
Nominated for the Order of Pegasus Award
2023
Outstanding Graduate Fellowship, University of Central Florida
2021
Ranked 1st among 25,000 candidates in Iran's national entrance exam for the M.Sc. of Industrial Engineering
2017
Ranked 2nd in the “Kharazmi” National Programming Competition
2012

Teaching Experience

Teaching Assistant | PHI 6679: Digital Ethics2025-08 – 2025-12
University of Central Florida, Orlando, FL
Teaching Assistant | STA 5206: Statistical Analysis2025-05 – 2025-08
University of Central Florida, Orlando, FL
Teaching Assistant | CAP 6737: Interactive Data Visualization2025-01 – 2025-05
University of Central Florida, Orlando, FL
Teaching Assistant | CAP 5610: Machine Learning2024-08 – 2024-12
University of Central Florida, Orlando, FL
Teaching Assistant | STA 6714: Data Preparation2023-08 – 2023-12
University of Central Florida, Orlando, FL
Teaching Assistant | STA 5206: Statistical Analysis2023-05 – 2023-08
University of Central Florida, Orlando, FL
Guest Lecturer (Projects in Data Analytics)2022-08 – 2022-12
University of Central Florida, Orlando, FL
Teaching Assistant | Data Mining2018-09 – 2019-12
Sharif University of Technology, Tehran, Iran

Development Experience

Blockchain Developer2020-06 – 2020-12
ZTech Team
  • Developed blockchain applications on the Ethereum network using Solidity, including implementing ERC20 token standards and smart contracts for Initial Coin Offering (ICOs).
Lead Software Developer2019-01 – 2020-12
BerimCafe
  • Developed cafè and restaurant management software using Django and Flutter.
Lead Software Developer2019-01 – 2020-03
TAEPO
  • Created TAEPO (TOEFL Online Practice and Exam Platform) using Django, Vue.js, and Electron.js.
Lead Software Developer2018-02 – 2019-12
MrZoro.ir
  • Developed a Django-based to automate university meal reservations.

Projects

DeepDrugDomain: Easy-to-use drug-target affinity and interaction prediction package for architecture design
  • Developed an open-source Python package for drug-target affinity and interaction prediction using deep learning models, including Transformers and graph neural networks.
  • Implemented a user-friendly API for drug-target affinity and interaction prediction.
  • Published on GitHub
COVID-19 Data Collection and Screening Project
  • Initiated and led an open-source project for COVID-19 data collection and screening, utilizing technologies such as Python, Django, and PostgreSQL for backend development link, and JavaScript, Vue js for frontend development link, to support public health efforts during the pandemic.

Pattents

Protein Translation Equivariant Encoding for mRNA Language Models2025
U.S. Non-Provisional Patent Application No. 19/727,645

Academic Services

Reviewer, Briefings in Bioinformatics
Reviewer, Computational and Structural Biotechnology Journal
Reviewer, IEEE Transactions on Neural Networks and Learning Systems Journal
Program Committee Member, AAAI Conference on Artificial Intelligence, Special Track on AI for Social Impact (2025, 2026)
Reviewer, Neurips The Thirty-Ninth Annual Conference on Neural Information Processing Systems (2025, 2026)

Skills

Programming Languages
Python, Dart, JavaScript, C++, C#, SQL, Solidity, MATLAB
Python Packages
Pytorch, Numpy, Pandas, Keras, TensorFlow, Scikit-learn, Scipy, Networkx, iGraph, DGL, Matplotlib, seaborn
JavaScript Frameworks
Vue.js, Electron, NativeScript
Tools
Kubernetes, Docker, Git, HTML, CSS, LATEX, AWS, Azure, Slurm
Quantitative Research
Machine Learning, Artificial Intelligence, Large Language Models, Generative AI, Genomic Sequence Modeling, Drug Discovery, Graph Neural Networks, Transformers, Recurrent Neural Networks, LSTMs, Mathematical Optimization, Mathematical Modeling
Soft Skills
Research team coordination, student mentoring, technical writing, conference presentations, resource allocation, strategic planning, analytical thinking, complex problem resolution, international team collaboration, multicultural communication, self-directed learning, professional networking

Certificates

Machine Learning Specialization2024
Python Fundamentals2018
Advanced Python2018

References

Dr. Ozlem Ozmen (Advisor)
  • Assistant Professor, University of Central Florida Email
Dr. Mangal Prakash
  • Senior Scientist, AI/ML at Johnson & Johnson (Janssen R&D) Email
Dr. Artem Moskalev
  • Research Scientist, Johnson & Johnson (Janssen R&D) Email
Dr. Ivan Garibay
  • Associate Professor, University of Central Florida Email