Find Academic Supervisors

Joel WootenView profile

Associate Professor

• Innovation
• Entrepreneurship
• Business Analytics
• +6 more

Joel Wooten is an Associate Professor of Management Science at the University of South Carolina's Darla Moore School of Business. His expertise spans innovation and entrepreneurship, with teaching focus on innovation/design, web-based products, business analytics, and statistics. He holds a Ph.D. and MBA from the Wharton School (University of Pennsylvania) and a B.S. in Industrial Engineering from Georgia Tech. Education: Ph.D., The Wharton School, University of Pennsylvania (2013) MBA, The Wharton School, University of Pennsylvania (2006) B.S., Industrial Engineering, Georgia Tech (2000) His research explores innovation tournaments, procurement auctions, and space industry operations. Notable partnerships include collaborations with XPRIZE and Merck, alongside entrepreneurial support for Fortune 500 firms and local businesses. Before academia, he was a strategy consultant at Bain & Company. Recent work analyzes subsidy efficacy in auctions, visibility impacts in innovation contests, and commercial space travel trends. His articles emphasize strategic procurement, competitive innovation, and emerging industry dynamics. No scientific awards are explicitly mentioned. Advising and grant details are not provided in the text.

Haralambos PanagopoulosView profile

Professor

• Theoretical Elementary Particle Physics
• Quantum Field Theory
• Nonperturbative phenomena in field theories
• +4 more

Haralambos Panagopoulos serves as a Professor in the Department of Physics at the University of Cyprus, Faculty of Pure and Applied Sciences, a position he has held since 2002 after previously serving as Associate Professor from 1992-2002. Harvard University, USA (B.A., magna cum laude in Physics, 1979) Massachusetts Institute of Technology, USA (Ph.D. in Physics, 1984) University of Montreal, Canada (Postdoc, 1984-1985) INFN and University of Pisa, Italy (Postdoc 1985-1987, Research Member 1987-1992) Professor Panagopoulos specializes in Theoretical Elementary Particle Physics and Quantum Field Theory, with particular expertise in nonperturbative phenomena in field theories, magnetic monopoles and catalysis of proton decay, instantons and spontaneous supersymmetry breaking in gauge theories and gravity, analytic and numerical problems in lattice gauge theories, and renormalization of quantum fields. His research represents significant contributions to understanding fundamental aspects of quantum field theories and particle interactions. His publications are cataloged in the SPIRES database, though specific recent works aren't detailed in the available information. Professor Panagopoulos maintains an active research profile within the theoretical physics community. No specific scientific awards mentioned in available information As a faculty member, Professor Panagopoulos contributes to the academic mission of the University of Cyprus through research and likely teaching responsibilities in advanced physics topics, though specific advising relationships aren't documented in the provided text. His office is located in Building FST 02 on the University Campus.

• Cybersecurity
• Machine Learning Applications in Security
• Data Provenance Analysis
• +7 more

Kangkook Jee is an Assistant Professor in the Department of Computer Science at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His work focuses on cybersecurity, machine learning applications in security, data provenance analysis, and graph neural networks. He has developed systems like ProvIoT for IoT security and UTrack for enterprise user tracking. His research addresses challenges in adversarial machine learning, malware detection, and robust graph classification under adversarial conditions. He also explores federated learning, confidential computing, and blockchain-based secure data sharing. Key contributions include techniques for detecting stealthy attacks in IoT, improving graph neural network robustness against adversarial node modifications, and enhancing intrusion detection through provenance-based analysis. His work bridges theoretical advancements in machine learning with practical enterprise security solutions. Notable systems include AIQL for efficient attack investigation and SEAL for storage-efficient causality analysis in enterprise logs. Research trends across his publications emphasize combining provenance tracking with modern ML techniques to address evolving cybersecurity threats. Work in 2024-2025 focuses on decompilation challenges, federated edge-cloud security, and graph abstraction methods for robust classification. No scientific awards are explicitly listed in the provided texts. His grants and advising activities are not detailed here, though his extensive publication record suggests active collaborative research. His lab works on tools like Nodoze for automated threat triage and APTrace for agile causality analysis in enterprise systems.

Cheryl SealsView profile

Professor

• Artificial Intelligence
• Natural Language Processing
• Educational Technology
• +4 more

Cheryl Seals is the Charles W. Barkley Endowed Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. She holds a Ph.D. in Computer Science from Virginia Tech, with additional degrees from Virginia Tech, North Carolina A&T State University, and Grambling State University. Her research focuses on AI ethics, natural language processing (NLP), virtual reality (VR) applications in healthcare and education, and promoting diversity in STEM. She leads initiatives like the NSF-funded AI ethics education project and the Institute for African Americans in Computing Sciences (IAAMCS). Notable awards include the Charles W. Barkley Professorship (2020) and participation in Drexel’s ELATES fellowship program. Her work bridges technology and social impact, including VR-based empathy training for medical students and interventions to mitigate pandemic-induced learning loss. She collaborates on interdisciplinary projects, such as automated grading tools for speech therapy and pavement crack recognition systems. Education: Ph.D. Computer Science, Virginia Tech M.S. Computer Science, Virginia Tech M.S. Software Engineering, North Carolina A&T State University B.S. Computer Science, Grambling State University Research Interests: AI Ethics and STEM Education Reform NLP for Sentiment Analysis and Hate Speech Detection VR Applications in Healthcare Training and Empathy Development Computing Equity and Underrepresented Groups Interdisciplinary Tools for Education and Accessibility Awards and Recognition: Charles W. Barkley Endowed Professor (2020–2025) ELATES Fellowship Participant (2024) Grants and Collaborations: NSF Grant: Integrating AI Ethics into STEM Curricula Collaborative Research: Evolution of IAAMCS National Science Foundation (NSF) AI Ethics Initiative Labs and Affiliations: Center for Artificial Intelligence and Cybersecurity Engineering McCrary Institute for Cyber and Critical Infrastructure Security

Wei ShiView profile

Professor

• Distributed computing
• Cloud computing
• Data center networks
• +6 more

Professor Wei Shi is a faculty member at the School of Computer Science, Carleton University. His research focuses on distributed computing, cloud networks, algorithm design for sensor/actuator systems, big data analytics, and data privacy. Notable projects include federated learning optimizations, blockchain-enabled edge intelligence for IoT/vehicle networks, and AI-driven cybersecurity solutions. His work addresses challenges in dynamic resource allocation, anomaly detection, and privacy-preserving techniques. Research Interests: Distributed Computing: Optimizing federated learning and client selection algorithms for wireless networks. Blockchain & Edge Intelligence: Developing decentralized systems for IoT and vehicular networks using AI large models. Security & Privacy: Innovating methods to detect AI-generated content, combat cyber-physical attacks, and protect user data privacy. Publications: Recent works emphasize federated learning applications, blockchain integration with edge computing, and cybersecurity for vehicular/IoT ecosystems. Key themes include energy-efficient algorithms, dynamic resource allocation, and intrusion detection in constrained environments. Email: wei.shi@carleton.ca

• Ontologies and Terminologies
• Neuroinformatics
• Big Data Analytics
• +3 more

Licong Cui, Ph.D., is an Associate Professor at the McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston (UTHealth). She is also affiliated with the Center for Translational AI Excellence and Applications in Medicine (TEAM-AI) and the Texas Institute for Restorative Neurotechnologies (TIRN). Her research focuses on developing informatics methods to address biomedical data challenges, with expertise in ontologies, neuroinformatics, big data analytics, and clinical text mining. Dr. Cui has authored over 100 peer-reviewed publications and secured grants from NIH and NSF. Her work emphasizes ontology quality assurance, large language model applications in healthcare, and data integration frameworks. Notable contributions include developing the VaxBot-HPV chatbot for vaccine communication and advancing seizure frequency extraction methodologies using LLMs. Her honors include the 2022 AMIA New Investigator Award and 2021 NSF CAREER Award. Current projects involve enhancing NIH Common Data Elements with AI tools and improving EHR-based cohort querying through ontology-driven approaches. She collaborates on initiatives like the National Sleep Research Resource and Vaccine Ontology harmonization efforts.

John GuttagView profile

Professor

• AI for Healthcare and Life Sciences
• Biological and Medical Devices and Systems
• Graphics and Vision
• +3 more

John Guttag is the Dugald C. Jackson Professor in Electrical Engineering and Computer Science at MIT. His work focuses on AI-driven healthcare solutions, biomedical systems, and advanced computer vision applications. He leads research in medical image analysis, machine learning reliability, and healthcare equity. Guttag's contributions include innovative frameworks like MultiMorph and Scale-Space Hypernetworks, addressing challenges in medical imaging and clinical decision-making. Affiliations: MIT Electrical Engineering & Computer Science Department (EECS) Research emphasizes AI for healthcare, particularly in segmentation, predictive analytics, and ethical algorithm design. Notable projects include real-time fraud detection systems and studies on racial disparities in clinical risk scores. His work bridges computer science with clinical practice through tools like Voxelmorph for medical image registration and ScribblePrompt for interactive biomedical segmentation. Recent publications highlight advancements in uncertainty-aware AI, contrastive learning, and scalable medical data processing. Guttag’s methodologies prioritize practical clinical applications, aiming to improve diagnostics and healthcare workflows. His lab develops open-source tools and frameworks that enhance accessibility to advanced medical imaging technologies.

Charles MonroeView profile

Professor

• Electrochemical Engineering
• Energy Storage Systems
• Material Science
• +3 more

Charles Monroe is a Professor of Engineering Science and Alexander Mosley Fellow at St Peter’s College, University of Oxford. He serves as a College Tutor in Engineering Science, Vice-Master, and Fellow for IT and Website. His research focuses on electrochemical devices for energy storage and conversion, particularly batteries and fuel cells. He joined St Peter’s in 2015 after being an Assistant Professor of Chemical Engineering at the University of Michigan. Monroe holds a PhD in Chemical Engineering from UC Berkeley (near Palo Alto, California) and an undergraduate degree from Princeton. Education: Bachelor’s degree from Princeton University PhD in Chemical Engineering from University of California, Berkeley Research Interests: Monroe’s work bridges theoretical and experimental approaches to study electrochemical systems, emphasizing the interplay between material properties and device performance. His group investigates next-generation batteries for electric vehicles, long-lived batteries for renewable energy integration, and degradation mechanisms in lithium-ion batteries. Collaborations with companies like Bosch, Ford, and Procter & Gamble highlight practical applications of his research. Publications: Recent work spans advanced battery technologies, including solid-state systems, flow batteries, and electrolyte transport modeling. Key themes include voltage hysteresis, solvent segregation effects, and membrane fouling in redox flow batteries. Scientific Awards: No specific awards mentioned in the provided text. Advising & Grants: Leads the Monroe Research Group, collaborating with industry partners. His work is funded through partnerships with multinational companies, supporting projects on battery design and energy storage systems. No individual student names are listed, but the group actively engages in graduate research. Labs/Teams: Monroe Research Group focuses on electrochemical engineering, with facilities for experimental and computational studies in energy storage technologies.

Mark WealView profile

Professor

• Digital Health
• Behavioral Interventions
• Semantic Web
• +2 more

Professor Mark Weal is a faculty member in the Department of Electronics and Computer Science at the University of Southampton. He holds roles as Co-Director of the Web Science Institute, Director of the Centre for Doctoral Training in Web Science Innovation, and Web Science Trust Fellow. His research focuses on digital health interventions, behavioral change technologies, and semantic web applications. Notably, he co-leads the LifeGuide project, a £45M initiative developing online health interventions for conditions like diabetes, cancer, and respiratory illnesses. Research interests include social media analytics for disaster management, semantic web infrastructures, and information systems design. He has supervised multiple PhD students in web science and digital health domains. Professor Weal has received significant grant funding from bodies like MRC, EPSRC, and the European Commission. Key achievements include over 45 million pounds in research funding and leadership in interdisciplinary projects. His work spans technical innovation and societal impact, addressing challenges in healthcare accessibility and digital infrastructure governance.

Yeqing KongView profile

Assistant Professor

• Technical Communication
• Risk/Crisis Communication
• Cross-cultural Communication
• +5 more

Yeqing Kong is an Assistant Professor of Technical Communication at Georgia Institute of Technology’s School of Literature, Media, and Communication (Ivan Allen College of Liberal Arts). Her research focuses on transnational risk communication, AI-assisted technologies, and social justice in communication. She holds a Ph.D. in Communication, Rhetoric, and Digital Media from North Carolina State University (2017-2021), an M.A. in Language and Linguistics from Lancaster University (2014-2015), and a B.A. in English from Hunan University (2010-2014). Education: Ph.D. North Carolina State University | M.A. Lancaster University | B.A. Hunan University Her research interests include corpus-assisted discourse analysis, cross-cultural communication strategies for vulnerable communities, and AI ethics in recruitment technologies. Recent work explores global health communication during the pandemic and environmental justice in crises like the Flint Water Crisis. Publications span journals like IEEE Transactions on Professional Communication and ACM conferences, focusing on technical communication, crisis management, and digital rhetoric. Her work emphasizes participatory approaches to promote equitable communication practices. Awards : Over $40,000 in grants (2017-2024), including IAC SODA Award, ACM SIGDOC grants, and HASTAC Scholar recognition. Grants and projects include AI-assisted recruiting tools and pedagogical initiatives like the Information Literacy Faculty Fellowship. She advises on technical writing pedagogy and health communication strategies, with ongoing collaborations in global media studies.

Javier IrizarryView profile

Professor

• Unmanned Aerial Systems (Drones) in Construction
• Construction 4.0
• Reality Capture Technology
• +3 more

Javier Irizarry is a Professor and Interim Chair in the School of Building Construction at Georgia Tech's College of Design. He also serves as Associate Dean for Academic Affairs and Outreach , overseeing academic programs, diversity initiatives, and recruitment efforts. As Director of the CONECTech Lab, he pioneers research in Construction 4.0 and UAV applications for infrastructure challenges. Education : Ph.D. (Civil Engineering), Purdue University Masters in Engineering Management, Polytechnic University of Puerto Rico B.S. (Civil Engineering), University of Puerto Rico, Mayagüez Research Focus : Irizarry’s work integrates cutting-edge technologies into construction, including Unmanned Aerial Systems (UAS), Reality Capture, Virtual/Augmented Reality, and Human Factors in Robotics. His lab develops frameworks for Construction 4.0 , emphasizing technology-driven solutions for safety and efficiency. Lab & Impact : The CONECTech Lab focuses on Construction 4.0 , advancing drone-based inspection systems, digital twins, and safety analytics. His research has led to over 100 publications, with applications in infrastructure monitoring, safety management, and educational tools. Leadership : As Associate Dean, Irizarry drives academic innovation and outreach, including pre-college programs and diversity strategies. He is a licensed Professional Engineer (PE) and FAA-licensed drone pilot, bridging academia and industry.

Tyler DerrView profile

Assistant Professor

• Data Mining
• Social Network Analysis
• Graph Representation Learning
• +5 more

Dr. Tyler Derr is an Assistant Professor in the Department of Computer Science at Vanderbilt University, with affiliate roles in the Data Science Institute and the Frist Center for Autism and Innovation. He holds a PhD from Michigan State University (2020) and focuses on data mining, machine learning, and graph neural networks with applications in drug discovery, ethical AI, and neurodiversity research. Education: PhD in Computer Science, Michigan State University (2020) M.S. in Computer Science, Pennsylvania State University B.S. in Computer Science and Mathematics, Pennsylvania State University His research emphasizes interdisciplinary social good, including drug discovery, education equity, and autism innovation. He directs the Network and Data Science (NDS) Lab, mentoring students who have won 50+ awards. Notable contributions include tools like FairNNV for fairness certification and datasets like WelQrate for drug discovery benchmarking. Awards include the NSF CAREER Award (2023), NVIDIA Academic Grant (2024), and Vanderbilt’s Career Catalyst Impact Award (2025). He co-founded the MLoG workshop series and serves on editorial boards for ACM TKDD and IEEE Transactions on Big Data . Grants & Leadership: NSF Grant for student travel to KDD2024 NVIDIA BioNeMo Platform grant for peptide design DOE Computational Science Fellowship advising His work bridges theory and practice, with tutorials on graph ML at AAAI/KDD and keynotes on ethical AI. The NDS Lab hosts interdisciplinary collaborations in computational biology, transportation, and neurodiversity advocacy.

Mattias VillaniView profile

Professor

• Bayesian Statistics
• Machine Learning
• Computational Methods
• +3 more

Mattias Villani is Professor of Statistics at Stockholm University, specializing in Bayesian statistics and machine learning. He obtained his PhD in Statistics from Stockholm University in 2000 and has held positions at Sveriges Riksbank and Linköping University. Villani develops computationally efficient Bayesian methods for inference, prediction and decision-making with flexible probabilistic models. Research Interests: His work spans Bayesian computation (MCMC, HMC, variational inference), machine learning (Gaussian processes, mixture models), and applications in neuroimaging, transportation, and econometrics. Research focuses on scalable Bayesian methods for large datasets and complex models. Publication Focus: Recent articles concentrate on Bayesian neuroimaging analysis, transportation network modeling, and efficient MCMC algorithms. Methodological innovations in subsampling techniques for large-scale Bayesian computation represent a significant research trend. Student Advising: Supervises PhD students in statistical methodology development and applications. Current research groups focus on spatiotemporal modeling, locally stationary processes, and neuroimaging statistics.

Hamid HezariView profile

Associate Professor

• Analysis
• Partial Differential Equations
• Spectral Geometry
• +3 more

Hamid Hezari is an Associate Professor in the Department of Mathematics at the University of California, Irvine (UCI). He holds a PhD from Johns Hopkins University (2009) and was a CLE Moore Instructor at MIT (2009–2012), with a postdoctoral fellowship at the Mathematical Sciences Research Institute (MSRI) during 2010. His research focuses on analysis and partial differential equations, particularly semiclassical/microlocal analysis and its applications in spectral geometry and quantum chaos. Key research interests include spectral geometry, quantum chaos, inverse problems, and the analysis of eigenfunctions. He has published over 25 peer-reviewed articles in top journals such as the Annals of Mathematics, Journal of Spectral Theory, and Communications in Mathematical Physics. His work explores topics like spectral rigidity of geometric domains, nodal set properties, and Bergman kernel asymptotics. Teaching responsibilities at UCI include courses in analysis, partial differential equations, and graduate-level topics like microlocal analysis. He has been supported by grants and has contributed to collaborative research with leading institutions. No specific awards are highlighted in the provided texts, though his prolific publication record underscores his scholarly impact. Hezari’s research often bridges mathematical physics and pure analysis, with applications to understanding geometric and dynamical systems through spectral methods.

Vasiliki KantereView profile

Professor

• Big Data Management
• Big Data Analytics
• Machine Learning
• +9 more

Dr. Vasiliki Kantere is a Professor at the School of Electrical Engineering and Computer Science within the Faculty of Engineering at the University of Ottawa . She has held previous academic positions, including: Senior Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens Maître d’Enseignement et de Recherche and Maître Assistante at the University of Geneva Junior Assistant Professor at the Department of Electrical Engineering and Information Technology, Cyprus University of Technology Postdoctoral Researcher at the École Polytechnique Fédérale de Lausanne Her research interests span a wide range of interdisciplinary domains, including: Big Data Management: data storage optimization, analytics workflows, and deployment on hybrid infrastructures Big Data Analytics: support for users of varying expertise and large data graphs Machine Learning: applications in resource management and query optimization Cloud Computing: cost-aware data management and service-level agreements P2P Systems: query processing and mobile peer environments Semantic Web: ontology mapping and semantic integration Distributed Systems: federated databases and grid computing Databases: query languages and semi-structured data management General: spatial data, privacy and security, and sensor networks No academic awards, funded grants, or advising roles are explicitly listed in the provided information. Her professional contributions are reflected through her extensive research collaborations and diverse academic experiences. The text does not mention any affiliated research labs or teams.