CV
You can download my current CV as a PDF and view a short summary here.
Current Position
PhD student, Carnegie Mellon University
School of Computer Science, Computational Biology Department
Advisor: Dr. Jose Lugo-Martinez
Research Focus
Machine-learning systems, reinforcement learning, generative and foundation models, and AI agents, with applications in scientific discovery, simulation, and autonomous laboratories.
Selected Research Experience
- Model Hardware Standard research preview (2026): Led CMU’s work using MHS; built drivers and orchestration for an AI agent to coordinate a liquid handler, plate reader, robotic arm, and cameras in closed-loop dose-response experiments. Case study. Covered in Nature News (24 September 2026).
- simPCL: Developing a simulator and benchmark generator for planning and fault recovery in programmable cloud laboratories.
- Agentic Fault Recovery for Orchestration of Programmable Cloud Laboratories: Work in progress. Project
- AI Scientist Summer Workshop (2026): Contributed talk on agentic fault recovery for autonomous orchestration of programmable cloud laboratories.
- Predictive Phenomics (2026): Poster, Agentic Recovery for Orchestration of Programmable Cloud Laboratories, Washington, DC. Agenda.
Education
- PhD, Computational Biology — Carnegie Mellon University (2024–2029)
- MSc, Computer Engineering — Bilkent University (2021–2024, GPA: 3.9/4.0)
- BSc, Computer Engineering — Shiraz University (2016–2021, GPA: 3.5/4.0)
Selected news coverage
Glickman, K. (24 September 2026). AI system helps lab devices ‘talk’ with each other — streamlining research. Nature. The article opens with our lab’s MHS experiments at CMU.
Selected Publications
- Ozden, F., Barazandeh, S., et al. (2026). RNAGEN: A generative adversarial network-based model to generate synthetic RNA sequences to target proteins. ChemBioChem, 27(13): e202500445.
- Barazandeh, S., et al. (2025). UTRGAN: Learning to generate 5’ UTR sequences for optimized translation efficiency and gene expression. Bioinformatics Advances, 5(1): vbaf134.
- Tabrizi, S.S., Barazandeh, S., et al. (2025). RNAtranslator: Modeling protein-conditional RNA design as sequence-to-sequence natural language translation. PLOS Computational Biology, 21(10): e1013541.
Seeking
Summer 2027 research and applied-science internships in ML systems, reinforcement learning, simulation, generative AI, and AI agents.