- Summer internships: Paid internships are possible for undergraduates at UC Merced (competitive selection). Explore possible project ideas here. Send me an email with your interests, experience, and your CV.
- If you have support from another university/fellowship/thesis program, send me an email with the details.
About Me
I am a tenure-track faculty member in the School of Engineering at the University of California, Merced. Before joining UC Merced, I completed my Ph.D. in Control and Dynamical Systems at Caltech working with Richard M Murray. I am interested in research on control theory and formal system modeling and design with the following goals:
- Can we formally quantify safety and robustness in scenarios where we know that models might fail? Application examples include control of biomolecular networks and autonmous vehicles.
- Can we embed provable guarantees into data-driven methods? For example, is it possible for transformer neural networks to have Lyapunov-like stability, safety, and robustness guarantees in controlling physical systems?
- How does AI impact creative exploration and professional formation in engineering education?
- What educational technologies are most effective in engaging *every* student in a classroom?
For more information on my research: you can browse through the Projects and refer to the Publications page. For more information on my teaching and student feedback: you can browse through the Teaching page.
If any of the above sounds interesting to you, please do not hesitate to email me at ayushpandey at ucmerced dot edu
Short Biography (third person): Ayush Pandey is interested in research on control theory, computational modeling, and artificial intelligence for the formal design of physical and bioengineered systems. Over the past few years, his research has focused on the development of robustness metrics, safety guarantees, and new inference tools for nonlinear dynamical systems in various application areas. He is also actively extending his research on computational modeling to build open-source educational tools that make classroom learning more interactive, engaging, and student-centered. In 2023, Ayush Pandey received his Ph.D. in Control and Dynamical Systems from California Institute of Technology. In 2019, he graduated with a masters in Electrical Engineering at Caltech. Before that, in 2017, he graduated with a bachelors and a masters degree from the Electrical Engineering department at the Indian Institute of Technoloy (IIT) Kharagpur, India.
Group Members
| Jenny Tang | Julio Salgado | Gavin Abrigo |
| Prerana Somarapu | Aizen Baidya | Nelida Salgado |
See the past students page for a list of all students who I have mentored in the past.
Projects
- Parameter robustness in dynamical system models
- Revolutionizing engineering education using collaborative design and integration of sociotechnical modules
- Safety guarantees and robustness quantification in the use of generative AI models for control
- Robust design and analysis of engineered biological systems
- LLM-based personalized grading to enable independent and open-ended summative assessments
Milestones and News
- May 2026: Launched EE 005 robotics showcase and announced students inducted into the EE hall-of-fame
- May 2026: Nature Chemical Engineering research highlight featured our collaborative work, led by Dr. Chelsea Hu's lab, on growth-dependent gene expression modeling.
- Apr 2026: Congratulations to group members on securing internships: Nelida Salgado (LLNL), Prerana Somarapu (LLNL), Aizen Baidya and Julio Salgado (CITRIS WIP), Axel Muniz Tello (MID)
- Apr 2026: Extended abstract on the theoretical work on "Formal specifications for CRNs" accepted for publication in IWBDA 2026. Full preprint coming soon.
- Apr 2026: Senate Committee on Research funded our ongoing research on computational modeling of biological systems.
- Feb 2026: Led by Zoila Jurado, postdoc at NIST, our work on nucleotide-level modeling of genetic circuits in PURE cell-free mixtures is now out on bioRxiv!
- Feb 2026: News feature: NSF award to redesign the UC Merced EE program. Excited to lead the activities under this project.
- Feb 2026: Aizen's extended abstract on "Teach2Learn" now published in ACM TS SIGCSE 2026. Aizen will be at SIGCSE 2026 in St. Louis to present this work.
- Jan 2026: Our paper on "Resolving Emergent Oscillations in Gene Circuits with a Growth-Coupled Model" is now accepted for publication in Science Advances! Read bioRxiv or published version here.
- Dec 2025: Gave a talk at Conference on Decision and Control (CDC) 2026 at Rio De Janeiro, Brazil on robustness of dynamical models under parametric uncertainties. Slides here.
- Dec 2025: Our NSF RED webpage is now live! Check it out here!
- Nov 2025: Two abstracts selected for ASEE 2026 (congratulations, Harshini!) and one poster for SIGCSE 2026 (congratulations, Aizen)!
- Nov 2025: Participated in the Professional Open Source Software Engineering (POSSE) 2025 workshop at University of California, Santa Cruz.
- Oct 2025: Announced this year's EE 021 (intro programming class for EE students that includes hands-on hardware-based validation of computer programs) hall-of-fame winners.
- Sep 2025: Paid undergraduate (UCM) and graduate student researcher (open for all) positions available in the areas of control theory (and intersections with AI), engineering education, and AI for education.
- More news...
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