Who Needs to Know? Minimal Knowledge for Optimal Coordination

N. Lauffer, A. Shah, M. Carroll, M. Dennis, and S. Russell. ICML 2023.

No‑regret Learning in Dynamic Stackelberg Games

N. Lauffer, M. Ghasemi, A. Hashemi, Y. Savas, and U. Topcu. arXiv preprint 2022.

Learning Deterministic Finite Automata Decompositions from Examples and Demonstrations

N. Lauffer*, B. Yalcinkaya*, M. Vazquez-Chanlatte, A Shah, and S. Seshia. FMCAD 2022.

Multiscale Heterogeneous Optimal Lockdown Control for COVID-19 Using Geographic Information

C. Neary, M. Cubuktepe, N. Lauffer, X. Jin, A. Phillips, Z. Xu, D. Tong, and U. Topcu. Scientific Reports 2022.

Reachability Games for Optimal Multi-agent Scheduling of Tasks with Variable Durations

D. Raju, N. Lauffer, U. Topcu. COCOA 2020.

Training classifiers for feedback control

H. Poonawala, N. Lauffer, U. Topcu. ACC 2019.

Human‑understandable explanations of infeasibility for resource‑constrained scheduling problems

N. Lauffer, U. Topcu. ICAPS XAIP Workshop 2019.

Expedited Learning in MDPs with Side Information

M. Ornik, J. Fu, N. Lauffer, K. W. Perera, M. Alshiekh, M. Ono, and U. Topcu. CDC 2018.

Affine multiplexing networks: System analysis, learning, and computation

I. Papusha, U. Topcu, S. Car, N. Lauffer. arXiv preprint 2018.

*equal authorship

More information is available on my Google Scholar profile.