CV

Resume

Education

• Rensselaer Polytechnic Institute (RPI), Troy, NY, 2015-2019
  • Ph.D in Electrical Engineering
• Rensselaer Polytechnic Institute (RPI), Troy, NY, 2017-2019
  • Master in Applied Mathematics
• Harbin Institute of Technology (HIT), Harbin, China, 2009-2013
  • B.Sc. in Electrical Engineering

Work Experience

• Summer Intern in 2018:
  • Los Alamos National Laboratory (LANL), NM
  • Research Topic: Real-time Fault Location through Convolutional Neural Network
  • Duties: Propose a real-time approach to locate faults in a network with high accuracy even only 7% of network nodes are observed, while other methods require 30% of nodes to be observed. Develop a node selection algorithm to determine the measured nodes, increasing 10% location accuracy.
  • Supervisor: Michael Chertkov, Deepjyoti Deka

Skills

• Python, Matlab, R, C, Machine/deep learing, Approximation algorithms, Statistics, Optimization
• Tensorflow, Pytorch, Jupyter Notebook, Latex, Scikit-learn, CVX, AMPL, PSCAD, PSSE
• Language: Chinese (native) and English

Publications

Improved AC fault ride through control strategy for MTDC system with offshore wind farms

W. Li, J. Lv, G. Shi, X. Cai and Y. Chi, "Improved AC fault ride through control strategy for MTDC system with offshore wind farms," 2014 International Conference on Power System Technology, Chengdu, 2014, pp. 2409-2419.

A novel DC voltage control strategy for multiterminal HVDC system with offshore wind farms integration

W. Li, G. Shi, X. Cai and N. Li, "A novel DC voltage control strategy for multiterminal HVDC system with offshore wind farms integration," 2014 International Power Electronics and Application Conference and Exposition, Shanghai, 2014, pp. 1110-1115.

Fast Event Identification through Subspace Characterization of PMU Data in Power Systems

W. Li, M. Wang and J. H. Chow, "Fast event identification through subspace characterization of PMU data in power systems," 2017 IEEE Power & Energy Society General Meeting, Chicago, IL, 2017, pp. 1-5.

Recent Results of PMU Data Analytics by Exploiting Low-dimensional Structures

Wang, Meng, et al. "Recent Results of PMU Data Analytics by Exploiting Low-dimensional Structures." Proc. of the 10th Bulk Power Systems Dynamics and Control Symposium (IREP), Espinho, Portugal. 2017.

Real-Time Event Identification Through Low-Dimensional Subspace Characterization of High-Dimensional Synchrophasor Data

W. Li, M. Wang and J. H. Chow, "Real-Time Event Identification Through Low-Dimensional Subspace Characterization of High-Dimensional Synchrophasor Data," in IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 4937-4947, Sept. 2018.

Identifying Overlapping Successive Events Using a Shallow Convolutional Neural Network

W. Li and M. Wang, "Identifying Overlapping Successive Events Using a Shallow Convolutional Neural Network," in IEEE Transactions on Power Systems.

Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks

W. Li, D. Deka, M. Chertkov and M. Wang, "Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks," in IEEE Transactions on Power Systems.

A Low-rank Framework of PMU Data Recovery and Event Identification

M. Wang et al., "A Low-rank Framework of PMU Data Recovery and Event Identification," 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), College Station, TX, USA, 2019, pp. 1-9.

Real-time Energy Disaggregation at Substations with Behind-the-Meter Solar Generation

W. Li, M. Yi, M. Wang, Y. Wang, D. Shi and Z. Wang, "Real-time Energy Disaggregation at Substations with Behind-the-Meter Solar Generation," in IEEE Transactions on Power Systems, doi: 10.1109/TPWRS.2020.3035639.

Physics-informed Neural Networks for High Impedance Fault Detection

Li W, Deka D. Physics Informed Neural Networks for High Impedance Faults Detection. arXiv preprint arXiv:2008.02364, 2020.

Projects

Fast Event Identification through Subspace Characterization of PMU Data in Power Systems

July 16, 2017

Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks

May 15, 2018

Application of Factorial Hidden Markov Model (FHMM) to Non-intrusive Load Monitoring

December 17, 2018

Course Project at Rensselaer Polytechnics Institute, Troy NY, USA,

Cognitive Web Application based on IBM Watson API

Identifying Overlapping Successive Events Using a Shallow Convolutional Neural Network

April 10, 2019

Personal

Three Minutes Thesis Talk

Rewards and Service

• Founders Award of Excellence, 2018 (top 1%)
• North America Finalist of IBM Watson Build Challenge, 2017
• The excellent new PhD Student Scholarship, 2013 (Top 1%)
• Peoples Scholarship (Top 3%) & National Encouragement Scholarship, 2012 (Top 2%)
• Honorable Mention Award of Mathematical Modeling, 2012
• Member of smart grid publication committee
• Reviewer of Smart Grid Transaction Journal
• Reviewer of Power System Transaction Journal
• Reviewer of Power Energy Scociety General Meeting