Teodor Mihai Moldovan

I am a Ph.D. student in the EECS department at UC Berkeley co-advised by Prof. Pieter Abbeel and Prof. Michael I. Jordan, working in collaboration with the AMPLab and the UC Berkeley Robotics group. I obtained my Masters's (MA) degree in Statistics in 2012 from UC Berkeley and my Bachelor of Science (ScB) degree with triple concentration (computer science, physics, mathematics) in 2009 from Brown University, where my research adviser was Prof. Michael J. Black.

Research interests

When we learn to control dynamical systems, such as a remote-control helicopter or a bicycle, we intuitively construct a mental model for how the system works, we plan under this uncertain model to explore the capabilities of the system and we try to keep ourselves and the device safe. My research focuses mainly on formalizing these notions and developing efficient algorithms for safely learning to control dynamical systems. Based on the methods used, my work lies at the intersection of reinforcement learning, non-parametric Bayesian modelling and optimization.

Publications

Risk Aversion in Markov Decision Processes via Near-Optimal Chernoff Bounds,
Teodor Mihai Moldovan and Pieter Abbeel. In Advances in Neural Information Processing Systems 25, 2012.
[ bib | poster | pdf | Abstract ]

Scaling the mobile millennium system in the cloud,
Timothy Hunter, Teodor Moldovan, Matei Zaharia, Samy Merzgui, Justin Ma, Michael J. Franklin, Pieter Abbeel, and Alexandre M. Bayen. In Proceedings of the 2nd ACM Symposium on Cloud Computing, 2011.
[ bib | pdf | http | Abstract ]

Denoising archival films using a learned bayesian model,
Teodor Mihai Moldovan, Stefan Roth, and Michael J. Black. In Proceedings of the International Conference on Image Processing, 2006.
[ bib | pdf | http | Abstract ]

Contact

University of California, Berkeley
710, Sutardja Dai Hall
Berkeley, CA 94720-1720

moldovan AT cs.berkeley.edu