Associate Professor, Department of Computer Science, Virginia Tech.
Director of the Machine Learning Laboratory.
If you are interested in joining my lab, please do not email me. Instead, please apply to VT first then fill out this form.
Prior to joining VT, I worked at the Palo Alto Research Center (aka Xerox PARC), where I led the machine learning research group, managed key client portfolios, and spearheaded machine learning for sensor research.
I received my BE in Computer and Systems Engineering from Alexandria University, Egypt, and my MS and Ph.D. in Computer Science from Purdue University.
- May ‘23 - our paper, Exploring Approaches to Artificial Intelligence Governance: From Ethics to Policy, received Honorable Mention Best Paper Award at IEEE Ethics 2023.
- Apr ‘23 - served as a panelist on Healthcare Technology Governance at the +Policy Symposium on The Governance of New and Emerging Technologies.
- Jan ‘23 - our paper COVID-19 pandemic impacts on traffic system delay, fuel consumption and emissions. received the International Journal of Transportation Science and Technology (IJTST) received the Most Cited Paper Award.
- Apr ‘22 - delivered the opening keynote at the Women in Data Science (WiDS) Blacksburg Conference.
- Mar ‘22 - recognized as Purdue CS celebrates Women’s History Month.
- Apr ‘21 - received the Purdue University College of Science Early Career Scientist Award for the Department of Computer Science.
- Jun ‘23 - Intelligence Advanced Research Projects Activity (IARPA) Pursuing Intelligent Complex Aerosols for Rapid Detection (PICARD) - Size-segregated Particle Odor Chromatographic Kernel (SPOCK). Co-PI
- Aug ‘22 - Department of Energy (DoE) - A data-driven multi-scale phytotechnology framework for identification and remediation of leached-metals-contaminated soil near coal ash impoundments. Co-PI
- May ‘22 - Adobe - Robust Real-time Resource Forecasting for Pricing Scheme Design. PI
- Feb ‘22 - NSF - Natural Language Processing for Teaching and Research in Engineering Education. Co-PI
- Jan ‘22 - Siemens - Multi-agent Reinforcement Learning for Traffic Control. PI
- Oct ‘21 - CCI - Deep Resilience for Multifaceted Federated Learning in Internet-of-Everything. Co-PI
- Oct ‘21 - National Institute of Health (NIH) integrated Translational Health Research Institute of Virginia (iTHRIV) - Reducing Operating Room Waste by Monitoring Single-use Sterile Surgical Supplies with Computer Vision. VT PI
- Jul ‘21 - National Science Foundation (NSF) - Advancing Health Equity using Interactive Condition Assessment and Monitoring. VT PI
- Jan ‘21 - Commonwealth Cyber Initiative (CCI) - Determination of Safety Limits against Cyber Threats in Neuromodulation Devices using Machine Learning, Brain Phantoms, and Neural Pathways. VT PI
- May ‘20 - Adobe - Time-series Prediction for Cloud Demand Forecasting. PI
Recent VT Funding
- Sep ‘22 - VT Policy Destination Area (PDA) - Exploring AI Ethics Policy Concerns and Career Pathways of the AI Professionals with Policy Training Experience. Co-PI
- Apr ‘22 - VT Center for Human-Computer Interaction (CHCI) - Using human-centered AI for designing an intelligent telehealth training system. Co-PI
- Oct ‘21 - VT Institute for Critical Technology and Applied Science (ICTAS) Engineering Faculty Organization (EFO) Opportunity - Intelligent Augmented Reality for the Future of Work. Co-PI
- Apr ‘21 - VT Center for Human-Computer Interaction (CHCI) - Intelligent Augmented Reality for the Future of Work. Co-PI
- Sep ‘22 - patent published: System and method for performing collaborative learning of machine representations for a target concept.
- Mar ‘22 - patent granted: System and method using augmented reality for efficient collection of training data for machine learning.
- Oct ‘21 - patent granted: System and method for coordinating parking enforcement officer patrol in real time with the aid of a digital computer.
- Aug ‘21 - patent granted: Agile video query using ensembles of deep neural networks.
- Jul ‘20 - patent granted: Interactive remote patient monitoring and condition management intervention system.
- Jul ‘20 - patent published: Method and system for similarity-based multi-label learning.
Recent Journal Articles
- Feb ‘23 - paper published in the ACM Transactions on Knowledge Discovery from Data (TKDD): Graph Deep Factors for Probabilistic Time-series Forecasting.
- May ‘22 - paper published in the IEEE Transactions on Knowledge and Data Engineering (TKDE): Role-based graph embeddings.
- Oct ‘21 - paper published in the IEEE Access Journal: Two-Stage Clustering of Household Electricity Load Shapes for Improved Temporal Pattern Representation. – code, data, presentation
- Mar ‘21 - paper published in the Transportation Research Record Journal: Predicting Coordinated Actuated Traffic Signal Change Times using LSTM Neural Networks.
- Dec ‘20 - paper published in the International Journal of Transportation Science and Technology (IJTST): COVID-19 pandemic impacts on traffic system delay, fuel consumption and emissions.
- Mar ‘20 - paper published in the Journal of Machine Learning Research (JMLR): Ensemble Learning for Relational Data.
Recent Conference Papers
- Aug ‘23 - paper accepted for publication in the ACM International Conference on Information and Knowledge Management (CIKM) 2023: Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction.
- Jul ‘23 - paper accepted for publication in the IEEE ASEE Frontiers in Education Conference 2023: A Preliminary Investigation of the Ethics Policy Concerns of Artificial Intelligence: Insights from AI Professionals Working in Policy-Related Roles.
- Jul ‘23 - paper accepted for publication in the IEEE Conference on Decision and Control (CDC) 2023: Trajectory Generation using Activator-Inhibitor Systems.
- May ‘23 - paper published in IEEE Ethics 2023: Exploring Approaches to Artificial Intelligence Governance: From Ethics to Policy. Received Honorable Mention Best Paper Award.
- Mar ‘23 - paper accepted for publication in ECC 2023: Near-Optimal Trajectory Generation for Flexible Motion Systems using Two-Boundary Approach.
- Feb ‘23 - paper accepted for publication in IEEE EMBS Conference on Neural Engineering (NER) 2023: Prediction of Electric Fields Induced by Transcranial Magnetic Stimulation in the Brain using a Deep Encoder-Decoder Convolutional Neural Network.
- Feb ‘23 - paper accepted for publication in ICDE-TKDE 2023: Role-based Graph Embeddings.
- Dec ‘22 - paper published in proceedings of the IEEE International Conference on Big Data 2022: Clustering-based Unsupervised Generative Relation Extraction.
- Jun ‘22 - paper published in proceedings of the American Control Conference (ACC): Singular Perturbation-based Reinforcement Learning of Two-Point Boundary Optimal Control Systems.– code, presentation, poster
- Feb ‘22 - paper published in proceedings of the AAAI Workshop on Reinforcement Learning in Games (AAAI-RLG) 2022: Cooperation Learning in Time-Varying Multi-Agent Networks.– code, presentation, poster
- Jan ‘22 - paper presented at the Transportation Research Board (TRB) Annual Meeting 2022: Assessing the Robustness of LSTM Neural Networks for the Prediction of Actuated-Coordinated Traffic Signal Change Times.
- Dec ‘21 - paper published in proceedings of the IEEE International Conference on Big Data 2021: Context Integrated Relational Spatio-Temporal Resource Forecasting.
- Dec ‘21 - paper published at the International Conference on Neural Information Processing (ICONIP) 2021: Multistage Hybrid Attentive Networks for Knowledge-Driven Stock Movement Prediction. – code, data, presentation
- Nov ‘21 - paper published in proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) 2021: Unsupervised Relation Extraction: A Variational Autoencoder Approach.
- Aug ‘21 - paper published in proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM SIGKDD KDD) 2021: Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation.
- Oct ‘21 - paper published in proceedings of the ACM International Conference on Information and Knowledge Management (CIKM) 2021: Zero-shot Relation Classification from Side Information. – code, data, presentation
- Jun ‘21 - paper published in proceedings of the International Conference on Engineering Applications of Neural Networks (EANN) 2021: Predicting Stock Price Movement Using Financial News Sentiment.
- Jan ‘21 - paper presented at the Transportation Research Board (TRB) Annual Meeting 2021: Predicting Coordinated Actuated Traffic Signal Change Times using LSTM Neural Networks.
Recent Preprints, Technical Reports and Abstracts
- Aug ‘23 - Resource-Efficient Federated Learning for Heterogenous and Resource-Constrained Environments
- Mar ‘23 - Abstract published in the Bulletin of the American Physical Society: Prediction of Stimulation Strength of Transcranial Magnetic Stimulation in the Brain with Deep Encoder-Decoder Convolutional Neural Network
- Oct ‘22 - Prediction of Electric Fields Induced by Transcranial Magnetic Stimulation in the Brain using a Deep Encoder-Decoder Convolutional Neural Network
- Jun ‘22 - Hard Negative Sampling Strategies for Contrastive Representation Learning.
- Nov ‘21 - Report published by the United States Department of Transportation: Estimating Switching Times of Actuated Coordinated Traffic Signals: A Deep Learning Approach.
- Dec ‘21 - Prompt-based Zero-shot Relation Classification with Semantic Knowledge Augmentation.
- Sep ‘20 - Reinforcement Learning-based N-ary Cross-Sentence Relation Extraction.
- Sep ‘20 - Investigating Misinformation in Online Marketplaces: An Audit Study on Amazon.
- Jun ‘22 - Area Chair - AAAI Conference on Artificial Intelligence (AAAI-23)
- Dec ‘21 - Session Chair - Online, Temporal, and Time Series Systems - IEEE International Conference on Big Data 2021.
Journal Editorial Boards
- Mar ‘21 - Associate Editor - IEEE Transactions on Intelligent Transportation Systems (ITS).
- Mar ‘21 - Guest Editor - International Journal of Distributed Sensor Networks (IJDSN) Special Collection on Emerging Trends in Data Science and Cybersecurity in IoT.
Startup Advisory Boards
- Mar ‘21 - panelist - Society of Women Engineers (SWE) - Getting Involved in Undergraduate Research.
- Mar ‘21 - panelist - Association for Women in Computing (AWC) - Research Journey.
- Feb ‘20 - panelist - Association for Women in Computing (AWC) - Internship and Research Panel.