19 citations · 43 across the 15 of their papers we have counts for
15 papers
Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
Song Wei, Xiangrui Kong, Alinson Santos Xavier +3
Energy justice is a growing area of interest in interdisciplinary energy research. However, identifying systematic biases in the energy sector remains challenging due to confoundin…
Generalized Hypercube Queueing Models with Overlapping Service Regions
Wenqian Xing, Shixiang Zhu, Yao Xie
Motivated by the operations of the Atlanta Police Department, where heavy workloads and staffing shortages increasingly require units to patrol across overlapping service regions,…
Quantifying Grid Resilience Against Extreme Weather Using Large-Scale Customer Power Outage Data
Shixiang Zhu, Rui Yao, Yao Xie +3
In recent decades, the weather around the world has become more irregular and extreme, often causing large-scale extended power outages. Resilience -- the capability of withstandin…
Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data
Zheng Dong, Shixiang Zhu, Yao Xie +2
Most COVID-19 studies commonly report figures of the overall infection at a state- or county-level. This aggregation tends to miss out on fine details of virus propagation. In this…
Multi-resolution spatio-temporal prediction with application to wind power generation
Zheng Dong, Hanyu Zhang, Shixiang Zhu +2
Wind energy is becoming an increasingly crucial component of a sustainable grid, but its inherent variability and limited predictability present challenges for grid operators. The…
Neural Spectral Marked Point Processes
Shixiang Zhu, Haoyun Wang, Zheng Dong +2
Self- and mutually-exciting point processes are popular models in machine learning and statistics for dependent discrete event data. To date, most existing models assume stationary…
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
Shixiang Zhu, Alexander Bukharin, Liyan Xie +4
Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incid…
Signal Processing Challenges and Examples for {\it in-situ} Transmission Electron Microscopy
Josh Kacher, Yao Xie, Sven P. Voigt +4
Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TE…
Data-Driven Optimization for Atlanta Police Zone Design
Shixiang Zhu, He Wang, Yao Xie
We present a data-driven optimization framework for redesigning police patrol zones in an urban environment. The objectives are to rebalance police workload among geographical area…
Distributionally Robust Weighted -Nearest Neighbors
Shixiang Zhu, Liyan Xie, Minghe Zhang +2
Learning a robust classifier from a few samples remains a key challenge in machine learning. A major thrust of research has been focused on developing -nearest neighbor (-NN)…
Spatio-Temporal Point Processes with Attention for Traffic Congestion Event Modeling
Shixiang Zhu, Ruyi Ding, Minghe Zhang +2
We present a novel framework for modeling traffic congestion events over road networks. Using multi-modal data by combining count data from traffic sensors with police reports that…
Deep Fourier Kernel for Self-Attentive Point Processes
Shixiang Zhu, Minghe Zhang, Ruyi Ding +1
We present a novel attention-based model for discrete event data to capture complex non-linear temporal dependence structures. We borrow the idea from the attention mechanism and i…
Sequential Adversarial Anomaly Detection for One-Class Event Data
Shixiang Zhu, Henry Shaowu Yuchi, Minghe Zhang +1
We consider the sequential anomaly detection problem in the one-class setting when only the anomalous sequences are available and propose an adversarial sequential detector by solv…
Spatial-Temporal-Textual Point Processes for Crime Linkage Detection
Shixiang Zhu, Yao Xie
Crimes emerge out of complex interactions of human behaviors and situations. Linkages between crime incidents are highly complex. Detecting crime linkage given a set of incidents i…
Sequential Adaptive Detection for In-Situ Transmission Electron Microscopy (TEM)
Y. Cao, S. Zhu, Y. Xie +4
We develop new efficient online algorithms for detecting transient sparse signals in TEM video sequences, by adopting the recently developed framework for sequential detection join…