I attended Machine Learning Summer School (MLSS) held at London, July 15th – July 26th. Glad to know so many interesting minds working in general areas of machine learning. England summer is great!
Great honor to get the 2nd Best Paper award at this year’s E-Energy Conference in Phoenix! Trying to advocate more rigorous analysis when applying machine learning/forecasting techniques in power systems. See our paper here!
Also great to attend FCRC 2019! Learned a lot from other venues other than e-Energy such as Sigmetrics, EC and COLT.
Thanks my previous advisor Prof. Yang-Yu Liu at Harvard for the invitation to give a talk at the Netsci conference satellite symposium “Controlling Complex Networks: When Control Theory Meets Network Science”. I showed our works on convex neural nets for control (slides here!). Summer in Vermont felt pretty good, and it felt good to visit many old friends in New England! Also felt honored to talk to groups at University of Vermont.
Our work Exploiting Vulnerabilities of Load Forecasting Through Adversarial Attacks was accepted at this year’s ACM e-Energy conference. We looked into the overlooked security issues on load forecasting, which is an essential step in power system operations. With only small attack efforts, severe damages could be made upon normal system operations.
Code is available here.
Sincere thanks for the travel grant given by the committee!
I attended the 3rd Grid Science Winter School & Conference held in Santa Fe by Los Alamos National Laboratory. It was a super interesting venue! Great to hear from a lot of inspiring works, gather with old friends during my summer internship, and showed our work on Optimal Control via Neural Networks as a contributed student talk. Also showed one poster on our ongoing work Data-Driven Vulnerabilities of Power Systems Algorithms.
Our work on control via neural network (preprint on Arxiv available): Optimal Control Via Neural Networks: A Convex Approach was accepted to ICLR 2019. Very exciting theoretical results on showing a class of neural networks being input-convex, which are able to achieve excellent learning plus control performances on tasks such as Mujoco locomotion and building energy management.
We presented our work on generative models for renewable generations at this year’s Informs annual meeting conference held in Phoenix on November 4-7. Take a look at our slides and special thanks to Yuanyuan!
I attended the SmartGridComm this year held in Aalborg, Denmark on Oct. 29-31, 2018, and presented our work Is Machine Learning in Power Systems Vulnerable? We are interested in the general security issues of applied ML in power networks and smart grids, and call for more rigorous analysis of algorithmic security threatens. Take a look at our Arxiv preprint!
I passed my qualifying exam by the end of Spring quarter 2018 with works on generative models for renewables [slides]. Special thanks to my committee Radha Poovendran, Sreeram Kannan and Lillian Ratliff!
I will be working as a research intern in Los Alamos National Laboratory from June to September, mainly working with Dr. Misha Chertkov and Dr. Deepjyoti Deka in Center for Nonlinear Studies.