1.7k citations · 1.8k across the 13 of their papers we have counts for
13 papers
Spatial Computing Opportunities in Biomedical Decision Support: The Atlas-EHR Vision
Majid Farhadloo, Arun Sharma, Shashi Shekhar +1
We consider the problem of reducing the time needed by healthcare professionals to understand patient medical history via the next generation of biomedical decision support. This p…
Spatiotemporal Data Mining: A Survey
Arun Sharma, Zhe Jiang, Shashi Shekhar
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such a…
Understanding COVID-19 Effects on Mobility: A Community-Engaged Approach
Arun Sharma, Majid Farhadloo, Yan Li +3
Given aggregated mobile device data, the goal is to understand the impact of COVID-19 policy interventions on mobility. This problem is vital due to important societal use cases, s…
SAMCNet for Spatial-configuration-based Classification: A Summary of Results
Majid Farhadloo, Carl Molnar, Gaoxiang Luo +6
The goal of spatial-configuration-based classification is to build a classifier to distinguish two classes (e.g., responder, non-responder) based on the spatial arrangements (e.g.,…
Towards Comparative Physical Interpretation of Spatial Variability Aware Neural Networks: A Summary of Results
Jayant Gupta, Carl Molnar, Gaoxiang Luo +2
Given Spatial Variability Aware Neural Networks (SVANNs), the goal is to investigate mathematical (or computational) models for comparative physical interpretation towards their tr…
Vehicle Emissions Prediction with Physics-Aware AI Models: Preliminary Results
Harish Panneer Selvam, Yan Li, Pengyue Wang +2
Given an on-board diagnostics (OBD) dataset and a physics-based emissions prediction model, this paper aims to develop an accurate and computational-efficient AI (Artificial Intell…
Statistically-Robust Clustering Techniques for Mapping Spatial Hotspots: A Survey
Yiqun Xie, Shashi Shekhar, Yan Li
Mapping of spatial hotspots, i.e., regions with significantly higher rates of generating cases of certain events (e.g., disease or crime cases), is an important task in diverse soc…
Spatially correlated rotational dynamics reveals strain dependence in amorphous particle packings
Dong Wang, Nima Nejadsadeghi, Yan Li +3
Microstructural dynamics in amorphous particle packings is commonly probed by quantifying particle displacements. While rigidity in particle packings emerges when displacement of p…
Towards Spatial Variability Aware Deep Neural Networks (SVANN): A Summary of Results
Jayant Gupta, Yiqun Xie, Shashi Shekhar
Spatial variability has been observed in many geo-phenomena including climatic zones, USDA plant hardiness zones, and terrestrial habitat types (e.g., forest, grasslands, wetlands,…
Adversarial Attacks on Reinforcement Learning based Energy Management Systems of Extended Range Electric Delivery Vehicles
Pengyue Wang, Yan Li, Shashi Shekhar +1
Adversarial examples are firstly investigated in the area of computer vision: by adding some carefully designed ''noise'' to the original input image, the perturbed image that cann…
A Physics Model-Guided Online Bayesian Framework for Energy Management of Extended Range Electric Delivery Vehicles
Pengyue Wang, Yan Li, Shashi Shekhar +1
Increasing the fuel economy of hybrid electric vehicles (HEVs) and extended range electric vehicles (EREVs) through optimization-based energy management strategies (EMS) has been a…
Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data
Anuj Karpatne, Gowtham Atluri, James Faghmous +6
Data science models, although successful in a number of commercial domains, have had limited applicability in scientific problems involving complex physical phenomena. Theory-guide…
Minimum Spanning Tree on Spatio-Temporal Networks
Viswanath Gunturi, Shashi Shekhar, Arnab Bhattacharya
Given a spatio-temporal network (ST network) where edge properties vary with time, a time-sub-interval minimum spanning tree (TSMST) is a collection of minimum spanning trees of th…