I am an Assistant Professor in the Computer Science Department with the School of Computer Science at Carnegie Mellon University. I am also a member of the Societal Computing Program, and I am an affiliated member of the Machine Learning Department, the Robotics Institute, and the Electrical and Computer Engineering Department.
My work focuses on machine learning, optimization, and control. I work on core algorithmic methods as well as applications, focusing specifically on application in smart energy and sustainability domains.
In addition, I serve as Chief Data Scientist for C3 Iot, where we develop machine learning approaches to problems in predictive maintenance, supply chain optimization, fraud detection, and many other industrial internet of things applications.
- 12/17: Vaishnavh Nagarajan presents Gradient descent GAN optimization is locally stable as a oral presentation at NIPS 2017.
- 12/17: Priya Donti presents Task-based End-to-end Model Learning in Stochastic Optimization as a poster at NIPS 2017.
- 8/17: Brandon Amos presents Input Convex Neural Networks and OptNet: Differentiable Optimization as a Layer in Neural Networks at ICML.
- 8/17: Alnur Ali and Eric Wong present A Semismooth Newton Method for Fast, Generic Convex Programming at ICML.
- 4/17: Zico Kolter receives DARPA Young Faculty Award in 2017 class.
- 2/17: Po-wei Wang presents Polynomial optimization methods for matrix factorization at AAAI 2017.
- 12/16: Alnur Ali presents The Multiple Quantile Graphical Model at NIPS 2016 main conference.
- 12/16: Brandon Amos presents work on input convex neural networks for reinforcement learning at NIPS 2016 workshop on deep reinforcement learning.
- 12/16: Po-wei Wang presents work on the mixing method for fast MAXCUT-SDP solutions at NIPS 2016 workshop on Learning in high dimensions with structure.
- 11/16: Received DARPA SAGA seed project to investigate fast methods for stochastic programming.
- 9/16: Our preprint Input Convex Neural Networks is available on Arxiv.
- 8/16: Received DARPA RADICS award (with NRECA) to develop machine learning approaches to cybersecurity in electrical grid networks.
- 7/16: Xiao Zhang presents Model Predictive Control of Industrial Loads and Energy Storage for Demand Response, recipient of best paper award, at PES General meeting.
- The beginning of time (or this redesigned website, rather).