- NEW (Jan 2026): Multiple Ph.D. positions available in control theory and engineering education research with Fall 2026 start date. Send me an email with your CV if you are interested.
- NEW (Jan 2026): Postdoc positions: If you are a recent PhD graduate, please email your CV to discuss potential fellowship opportunities.
- 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
| Harshini Nujella | Julio Salgado | Gavin Abrigo | Kathy Chau |
| Axel Muniz Tello | Prerana Somarapu | Aizen Baidya | Nelida Salgado |
| Kiara Cuntapay |
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
- 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 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.
- Aug 2025: Invited to give a talk at the AI for Power Systems workshop at the Lawrence Livermore National Lab
- Jul 2025: My paper on "Parameter Robustness in Data-Driven Estimation of Dynamical Systems" was accepted for publication in the 64th IEEE Conference on Decision and Control (CDC 2025) at Rio De Janeiro, Brazil. Read the paper here: arXiv 2509:06534
- Jun 2025: Our team won a $1mn NSF RED grant on "Adapting Design Thinking to Transform the Professional Development of Electrical Engineers in California's Central Valley". I will be leading all project activities. If you are interested in collaborating, please reach out!
- Jun 2025: Our abstract on compartment-based modeling of biological systems using BioCRNpyler was accepted as a poster presentation at the Synthetic Biology: Engineering, Evolution, and Design (SEED 2025) conference. Read about the work here: BioCRNpyler
- More news...
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