Faculty


Brain-computer interfaces could let people control robotic arms by thought alone. Ramana Vinjamuri, CC BY-ND

 

UMBC has more than 50 faculty and senior research staff associated with the UMBC AI Center whose research includes work on AI-related problems and techniques. They come from departments, centers, and institutes across UMBC and represent many disciplines.

  • Tülay Adali (CSEE): machine learning for signal processing and bioinformatics,
  • Justin Brooks (CSEE): computational and behavioral neuroscience, medical applications of AI
  • Chien I. Chang (CSEE): remote sensing, image processing
  • Ansu Chatterjee (Math & Statistics): Foundations of data sciences, ethical AI, Bayesian and conditional inference, digital twins and personalized healthcare, climate analytics
  • Zhiyuan Chen (IS): data mining, adversarial learning, semantic information
  • Lujie (Karen) Chen (IS): multimodal learning analytics, machine learning, data science, medical informatics
  • Jim Clavin (Hilltop): AI for healthcare informatics, byzantine fault tolerance, knowledge graphs, generative AI
  • Mohammad ‘Khash’ Donyaee (CSEE, Lecturer): AI, machine learning
  • Abhijit Dutt (CSEE, Professor of Practice): data science, AI, machine learning
  • Don Engel (CSEE, VP Research): visualization, computer vision, NLP
  • Frank Ferraro (CSEE): natural language understanding (NLP), machine learning
  • Tim Finin (CSEE): Knowledge graphs, knowledge representation and reasoning, human language technology, AI
  • James Foulds (IS): socially conscious machine learning and artificial intelligence
  • Manas Gaur (CSEE): Knowledge graphs and machine learning for NLP, recommender systems, and computational social data science
  • Md Osman Gani (IS): explainable AI, ubiquitous computing, indoor localization, healthcare, and human activity recognition
  • Aryya Gangopadhyay (IS): data mining, healthcare analytics
  • Matthias Gobbert (Math): Machine learning, big data applications in science & engineering, parallel algorithms for computing clusters
  • Ankit Goel (ME): control systems, data-driven learning for complex control systems.
  • Tejas Gokhale (CSEE): computer vision, machine learning, reasoning
  • Milton Halem (CSEE): Big data for climate, quantum computing for AI
  • Morgan Henderson (Hilltop): predictive modeling and causal inference using administrative health data for populations in Maryland
  • Riadul Islam (CSEE): Robust, secured IC design for neuromorphic computing and machine learning applications
  • Vandana Janeja (IS): data science, data mining, anomaly detection
  • Ben Johnson (CSEE, Lecturer): AI, NLP, machine learning
  • Tyler Josephson (CBEE): AI, logic, machine learning, molecular simulation, applications in chemical and environmental engineering
  • Anupam Joshi (CSEE, Dean): AI for cybersecurity & cyber-physical systems, Web/text analysis, semantic web, neural networks
  • Karuna Joshi (IS): data science,  knowledge graphs, regulatory and legal AI, data security and privacy compliance, cloud computing
  • Kostas Kalpakis (CSEE): data science, algorithms for knowledge graphs, machine learning
  • George Karabatis (IS): data science, semantic information integration, machine learning
  • Seung-Jun Kim (CSEE):  machine learning, applications to communications, future power systems, and big data analytics
  • Andrea Kleinsmith (IS): affective computing and human-computer interaction
  • Chenchen Liu (CSEE): high-performance computing for AI, machine learning
  • Christine Mallinson (LLC): identifying linguistic bias and misinformation
  • Christopher Marron (CSEE), Professor of Practice): machine learning, data science
  • Lara Martin (CSEE): Human‑centered AI, computational creativity, language understanding, neuro-symbolic methods, speech processing, affective computing, conversational agents
  • Cynthia Matuszek (CSEE): robotics, human-robot interaction, machine learning, NLP, cybersecurity
  • Eric Millikin (Visual Arts): AI and art, virtual reality
  • Antonio Moreira (CBEE): applications of AI to biopharma manufacturing
  • Charles Nicholas (CSEE): machine learning and data science  for malware detection, intelligent information systems
  • Thu Nguyen (Math): machine learning, stochastic approximation,
  • Tim Oates (CSEE): machine learning, AI
  • Patti Ordóñez (IS): machine learning, data mining, and visualization to multivariate time series analysis, clinical informatics, biomedical data science
  • Shimei Pan (IS): NLP, machine learning, data mining
  • Sanjay Purushotham (IS): machine learning for healthcare
  • Nirmalya Roy (IS): machine learning for mobile, pervasive, and sensor computing, autonomous systems
  • Jinglai Shen (Math): machine learning, optimization
  • John Schumacher (Sociology, Anthropology, and Public Health): generative AI, pedagogy, gerontology, healthcare delivery
  • Ergun Simsek (CSEE): machine learning for applications in photonics and electromagnetics
  • Jennifer Sleeman (CSEE): NLP, document understanding, machine learning
  • Houbing Herbert Song (IS): AI/machine learning/big data analytics for cyber-physical systems/IoT, cybersecurity, and privacy
  • Ramana Vinjamuri (CSEE) brain-computer interfaces, machine learning, signal processing
  • Jianwu Wang (IS): data science for climate and manufacturing
  • Mohamed Younis (CSEE): Machine learning for communications, networks, and embedded systems
  • Meilin Yu (ME): Computational fluid dynamics, scientific machine learning, high-performance computing
  • Roberto Yus (CSEE): knowledge representation and reasoning, knowledge graphs, IoT, privacy, semantic data management
  • Rebecca Williams (CSEE): immersive media, data visualization, computer vision, computer graphics, brain-computer interface, wearable sensor technology, imaging, and remote sensing