Sina Barazandeh

CMU SCS PhD student building AI agents and machine-learning systems for autonomous laboratories and scientific discovery.

Sina Barazandeh

I am a PhD student in the School of Computer Science at Carnegie Mellon University (Computational Biology Department), advised by Dr. Jose Lugo-Martinez.

Most recently, I led CMU’s work using the Model Hardware Standard (MHS) in the limited research preview: I built instrument drivers and orchestration so an AI agent could coordinate a liquid handler, plate reader, robotic arm, and cameras for closed-loop dose-response experiments. Nature covered the work on 24 September 2026.

I am seeking Summer 2027 research and applied-science internships in ML systems, reinforcement learning, simulation, generative AI, and AI agents.

[Resume (PDF)] · [Academic CV (PDF)]

Education

Ph.D. Computational Biology — School of Computer Science, Carnegie Mellon University (2024–2029)
Advisor: Dr. Jose Lugo-Martinez
M.Sc. Computer Engineering — Bilkent University (2021–2024, GPA: 3.9/4.0)
Advisor: Dr. A. Ercument Cicek · Thesis: Generative Models for Generating and Optimizing Biological Sequences
B.Sc. Computer Engineering — Shiraz University (2016–2021, GPA: 3.5/4.0)

Research Highlights

Autonomous Laboratories / MHS: Drivers and orchestration for a liquid handler, plate reader, robotic arm, and cameras. Case study
Simulation & Benchmarking: simPCL, a simulator and benchmark generator for planning and fault recovery in programmable cloud laboratories. I am interested in sim-to-real transfer, reinforcement learning in MuJoCo, and 3D world models for laboratory simulation.
Generative Models: Sequence design with GANs and seq2seq models (UTRGAN, RNAtranslator, RNAGEN)
Reinforcement Learning: Policy optimization for biomarker discovery under structure-aware rewards
ML Systems: FlashAttention and PagedAttention in MiniTorch (LLM Systems coursework)

Education

Research Highlights

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