AI, Machine Learning & Robotics Research

AI, Machine Learning & Robotics research at Drexel University's College of Computing & Informatics (CCI) explores algorithms, mathematics, and applications of artificial intelligence (AI) through fundamental and applied work in computer vision and pattern recognition, data science, knowledge representation and automatic metadata generation/extraction, logic, cognitive modeling and neural networks, image and signal processing, predictive modeling and statistical learning. In order to include the analyst and human user side, our AI, Machine Learning & Robotics faculty work in areas including explainable AI, fairness in AI, natural language processing and related topics.

Associated Faculty

  • Yuan An: Conceptual modeling, schema and ontology mapping, information integration, knowledge representation, requirements engineering, healthcare information systems, semantic web

  • Pragati Awasthi: Machine Learning and applications

  • Ellen Bass: Human-centered design, human-computer interaction, human factors, human performance modeling , judgment and decision making, medical informatics, systems engineering

  • Karthik Bhat: Human-Centered Computing, Human-Centered AI, Care Work, ICTD

  • David E. Breen: Computer-aided design, biomedical image informatics, geometric modeling and self-organization

  • Andrew Calhoun: Social Engineering, Defensive Cyber Operations, Ethical Hacking, Artificial Intelligence, Security Awareness & Training

  • Preetha Chatterjee: Software engineering, machine learning and natural language processing applications to software engineering, software data analytics, mining software repositories, empirical software engineering

  • Tiffany D. Do: Human-Centered AI, Virtual Avatars, Virtual Reality

  • Michael Ekstrand: Recommender systems, information retrieval, algorithmic fairness, social impact of technology, AI ethics

  • Joseph Alejandro Gallego Mejia: Computer Vision, Remote Sensing, Machine Learning, Quantum Machine Learning, Natural Language Processing. Teaching courses: Programming, Algorithms and Data Structures, Data Science, Machine Learning, GNU/Linux Tools, Natural Language Processing, Non-sqlDatabases, Scrum, Advance Python, Deep Learning, Machine Learning Operations, Large Language Models

  • Vasilis Gkatzelis: Algorithmic mechanism design, multiagent resource allocation, approximation algorithms

  • Jane Greenberg: Metadata, ontological engineering, data science, knowledge organization, information retrieval

  • Xiaohua Tony Hu: Data mining, text mining, Web searching and mining, information retrieval, bioinformatics and healthcare informatics

  • Shahin Jabbari: Machine learning, algorithmic fairness, game theory

  • Weimao Ke: Information retrieval (IR), distributed systems, intelligent filtering/recommendation, information visualization, network science, complex systems, machine learning, text/data mining, multi-agent systems

  • Edward Kim: Computer Vision, Sparse Coding, Neuromorphic Computing, Medical Image Processing, Computer Graphics, Artificial Intelligence, Game Development

  • Feng Liu: AI + X: Education; Healthcare. 3D Computer Vision: 3D object/scene understanding; 3D generation; VR/AR; 3D vision+language understanding. 3D Human Digitization: Modeling, reconstruction and rendering; Biomechanics. Generative AI: Explainability, generalization and controllability in generative models; DeepFake detection. Biometric Recognition: Face and gait recognition; Person re-identification

  • Santiago Ontañón: Game AI, computer games, artificial intelligence, machine learning, case-based reasoning

  • Emmanouil Pountourakis: Algorithmic mechanism design

  • Afsaneh Razi: Human-computer interaction, Social Computing, human-centered AI, Privacy, Ethics, Online Safety, language processing

  • Shadi Rezapour: Computational social science; natural language processing; network analysis; human-centered data science; computational linguistics

  • Dario Salvucci: Cognitive science, cognitive architectures, human-computer interaction, human factors, multitasking and interruptions, applications to driving and driver distraction

  • Aleksandra Sarcevic: Computer-supported cooperative work, human-computer interaction, healthcare informatics; crisis informatics; social analysis of information & communications technology (ICT)

  • Bhupesh Shetty: Process pattern mining, data mining, operations management, sports analytics, information systems, machine learning and applications

  • Ali Shokoufandeh: Theory of algorithms, graph theory, combinatorial optimization, computer vision

  • Lei Wang: Biomedical data science, machine learning, deep learning, neuroimaging processing & analytics, natural language processing, simulation modeling

  • Rosina Weber: Case-based reasoning, explainable artificial intelligence, machine learning, textual analytics, natural language understanding, language models, recommender systems, technological aspects of knowledge management, project management, and requirements engineering.

  • Jake Williams: Data science, scientific programming, computational social science, computational linguistics and natural language processing, mathematics, machine learning, algorithms, and scalability.

  • Kaidi Xu: Deep Learning, Trustworthy Machine Learning

  • Christopher C. Yang: Healthcare informatics, social media analytics, knowledge discovery, Web search and mining, recommendation systems, pharmacovigilance, drug repositioning, electronic commerce, intelligence and security informatics

  • Li Zhang: Natural Language Processing, Large Language Models, Artificial Intelligence, AI and Games, AI and Creativity

Associated PhDs

  • Layla Bouzoubaa: Social computing, natural language processing (NLP), harm reduction

  • John Carter: Cybersecurity, Machine Learning, Network Security, IoT Security

  • Jinhao Duan: Trustworthy Machine Learning

  • Prateek Goel: Explainable Artificial Intelligence (XAI), Interpretable Machine Learning (IML), and Case-Based Reasoning (CBR)

  • Adit Gupta: Human AI Interaction, Teachable AI

  • Jason Lefever: Software Refactoring, Code LLMs

  • Mary Lucas: Health informatics; predictive modeling in medicine; health disparities; AI bias and fairness

  • Sonia Pascua: Information theoretic framework for information representation, knowledge organization and predictive analytics of information retrieval systems

  • Joel Pepper: Computer Graphics, Geometric Modeling, Bio-inspired Computing, Computational Biology

  • Jon Pomeroy: Health Care Artificial Intelligence

  • Christopher Rauch: AI and Ethics

  • Jocelyn Rego: Artificial Intelligence, Biologically-inspired Machine Learning, Sparse Coding, Neuromorphic Computing, Neuroscience

  • Daniel Schwartz: Deep Learning, Convex Optimization, and Graph Neural Networks

  • Liz Sheffield: NLP, Bot Detection, Author Attribution on Social Media

  • Yiwen Shi: Natural Language Processing, Deep Learning, Biomedical Informatics

  • Manil Shrestha: Continual Learning in Multimodal Setting

  • Erica Shusas Racine: Human-Computer Interaction (HCI), Human-Centered AI (HAI), Credibility assessment of online information and AI-generated content

  • Xintong Zhao: Information Extraction‬, Knowledge Discovery‬, Natural Language Processing‬

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