SangWoo Park
I am an Assistant Professor at New Jersey Institute of Technology (NJIT). I received my Ph.D. from the department of Industrial Engineering and Operations Research (IEOR), University of California, Berkeley (UC Berkeley). My research focuses on designing and analyzing algorithms for complex and large scale optimization problems, mainly related to electric power systems.
Email: sangwoo.park@njit.edu
I am looking for motivated students with a strong Math/CS/Stat/EE background or hands-on experience in mathematical modeling and numerical simulations. We have two fully-funded Ph.D. positions at NJIT. Highly motivated Masters students are also welcome to participate in our research. If you are interested in working with me, please contact me at sangwoo.park@njit.edu.
News
- September 2023: New paper “Anomaly Detection in Power Grids via Context-Agnostic Learning.”
- September 2023: New paper “Boosting Efficiency in Power System State Estimation by Leveraging Attention Mechanism.”
- June 2023: Our paper “Modeling Post-disruption Equilibrium for Circular Supply Chains and New Measures for Resilience” has been accepted and presented at the International Material Handling Research Colloquium (IMHRC).
- April 2023: I gave a talk at Temple University on “Computational Methods for the Design and Operations of Electric Power Systems.”
- November 2022: Our paper “An Efficient Homotopy Method for Solving the Post-contingency Optimal Power Flow to Global Optimality” has been published in IEEE Access.
- I have joined the New Jersey Institute of Technology as an Assistant Professor.
- September 2022: Our paper “Dynamic Regret Bounds for Constrained Online Nonconvex Optimization Based on Polyak-Lojasiewicz Regions” to appear in IEEE Transactions on Control of Networks Systems.
- August 2022: Our paper “Distributed Power System State Estimation Using Graph Convolutional Neural Networks” to appear in 56th Hawaii International Conference on System Sciences (HICSS).
- I have successfully defended my dissertation and received my Ph.D. from UC Berkeley IEOR.
- November 2021: New paper titled “Distributed Power System State Estimation Using Graph Convolutional Neural Networks.”
- November 2021: Our paper “Uniqueness of Power Flow Solutions Using Graph-theoretic Notions” to appear in IEEE Transactions on Control of Networks Systems.
- October 2021: Our paper “Nonlinear Least Absolute Value Estimator for Topology Error Detection and Robust State Estimation” has been published in IEEE Access.
- September 2021: Our paper “Nonlinear Least Absolute Value Estimator for Topology Error Detection and Robust State Estimation” to appear in IEEE Access.
- August 2021: I gave a talk at Seoul National University (SNU) on “Tackling Non-convexity in Power Systems: Power Flow Problem, State Estimation, Optimal Power Flow”
- August 2021: I gave a talk at Korea Advanced Institute of Science and Technology (KAIST) on “Tackling Non-convexity in Power Systems: Power Flow Problem, State Estimation, Optimal Power Flow”
- November 2020: New paper titled “Uniqueness of Power Flow Solutions Using Graph-theoretic Notions.”
- November 2020: Our paper “Uniqueness of Power Flow Solutions Using Monotonicity and Network Topology” has been published in IEEE Transactions on Control of Network Systems.
- July 2020: Our paper “Homotopy Method for Finding the Global Solution of Post-contingency Optimal Power Flow” has won the Best Student Paper Award of 2020 American Control Conference (ACC).
- February 2020: Our paper “Homotopy Method for Finding the Global Solution of Post-contingency Optimal Power Flow” has been selected as one of the finalists for 2020 American Control Conference (ACC) Best Paper Award.
- July 2019: I gave a talk on “Topology Error Detection and Robust State Estimation Using Nonlinear Least Absolute Value” in the 2019 American Control Conference (ACC).
- April 2019: I received the Marshall Oliver-Rosenberger Fellowship from the Department of IEOR, UC Berkeley.
- March 2019: I was nominated by the Department of IEOR, UC Berkeley to receive the 2018-2019 Outstanding Graduate Student Instructor Award.
- January 2019: Our paper “Comparing Scenario Reduction Methods for Stochastic Transmission Planning” to appear in IET Generation, Transmission & Distribution.
- January 2019: I gave a talk on “Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions” in the 52nd Hawaii International Conference on System Sciences (HICSS).
- September 2018: I successfully passed the Doctoral Qualifying Examination and advanced to candidacy.
- August 2018: Our paper “Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions” to appear in 52nd Hawaii International Conference on System Sciences (HICSS).
- July 2018: I will give a talk on ‘‘ Joint State Estimation and Sparse Topology Error Detection for Nonlinear Power Systems’’ at 2018 INFORMS Annual Meeting.
- May 2018: I successfully passed the Doctoral Preliminary Examination.
- March 2018: New paper on joint state estimation and topology error detection: “Nonlinear Least Absolute Value Estimator for Power Systems State Estimation and Topological Error Detection.”
- November 2016: I joined Professor Javad Lavaei’s group at UC Berkeley as a PhD student.
- May 2016: I graduated from Johns Hopkins University with a B.S. in Environmental Engineering