Find Academic Supervisors

Dan Dongseong KimView profile

Associate Professor

• Cybersecurity
• Cybersecurity Modeling and Analysis
• Moving Target Defense
• +7 more

Associate Professor Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor at The University of Queensland (UQ), Australia. Previously, he held permanent academic positions at The University of Canterbury (UC), New Zealand (2011-2018) as a Senior Lecturer and Lecturer. His research focuses on Cybersecurity and Dependability for AI, IoT, Autonomous Vehicles, Cloud Computing, and Moving Target Defenses (MTD). Doctor of Philosophy in Computer Engineering from Korea Aerospace University Postdoctoral Research at Duke University (2008-2011) Visiting Scholar at University of Maryland (2007) Dan's work explores Graphical Security Models , Moving Target Defense for proactive resilience, and AI-Driven Cybersecurity with emphasis on adversarial robustness and interpretable models. His recent publications (2024-2025) span journals like IEEE Transactions on Dependable and Secure Computing and conferences such as DSN , addressing automated defense, evolving attacks, and hardware-aware security frameworks. He has advised 15 Ph.D. graduates, including researchers now at institutions like RMIT University, La Trobe University, and CSIRO's Data61. Current supervision includes projects on Automated Penetration Testing , AI-Based Intrusion Response , and Moving Target Defense . Dan's research is funded by agencies including the Republic of Korea's Agency for Defence Development and US Army Research Lab . His professional roles include Associate Editor for IEEE Communications Surveys and Tutorials and Steering Committee Chair for IEEE PRDC .

Jennifer DyView profile

Professor

• Machine Learning
• Computer Vision
• Explainable AI
• +2 more

Jennifer Dy is a Distinguished Professor at Northeastern University with joint appointments in Electrical and Computer Engineering and Khoury College of Computer Sciences. As Director of AI Faculty at the Institute for Experiential AI, she leads research in machine learning, computer vision, and explainable AI. Her work spans biomedical applications (COPD phenotyping, neuroimaging) and fundamental algorithms (active learning, continual learning). She holds a PhD from Purdue University and is an AAAI Fellow. Research Focus: Dy develops methodologies for robust and interpretable machine learning, including techniques for model stability in continual learning, dependency-aware active learning, and axiomatic explanation frameworks. Her applied research advances diagnostic tools using Raman spectroscopy, CT imaging, and multi-omics biomarker discovery. Awards: Recognized with the NSF CAREER Award, Faculty Research Team Award, and AAAI Fellowship for contributions to unsupervised learning and medical AI. Publication Trends: Recent articles demonstrate strong cross-disciplinary integration, combining theoretical advances in explainability/robustness with applications in healthcare, wireless systems, and particle physics. Methodological themes include optimal transport theory, probabilistic modeling, and transformer architectures.

• Computer Vision
• Machine Learning
• Biomedical Informatics
• +4 more

Charless Fowlkes is a Professor in the Department of Computer Science at the University of California, Irvine (UCI). His research focuses on computational vision, spanning human visual system understanding, machine vision systems, and applications in biomedical informatics and forensic science. He holds a Ph.D. from UC Berkeley (2005). His work integrates techniques from computer vision, AI, and applied mathematics to address challenges in automated biological data analysis, morphology, and spatial gene expression. Key research areas include forensic science (e.g., shoeprint matching via 3D reconstruction), biomedical applications (e.g., heart function mapping and pollen classification), and AI-driven systems for scene understanding. Recent projects include a $20M forensic science center funded by the National Institute of Justice. His publications emphasize geometric reasoning, 3D reconstruction, and adaptive learning algorithms. Notable contributions include developing algorithms for 3D human pose estimation with scene constraints, automated pollen identification via CNNs, and frameworks for cross-domain forensic analysis. His work bridges theoretical computer vision with real-world applications in forensics, healthcare, and environmental science.

Mahsan NouraniView profile

Academic

• Artificial Intelligence
• Human-Computer Interaction
• Healthcare Informatics
• +3 more

Mahsan Nourani is a Research Assistant Professor at Northeastern University, specializing in intersections of human-computer interaction, artificial intelligence, and healthcare informatics. Their research focuses on explainable AI systems, user behavior in AI partnerships, and design of interactive machine learning tools. Current work explores cognitive biases in human-AI collaboration, predictive analytics in healthcare, and activity recognition in videos. Key research areas include user profiling in AI applications, trust dynamics in intelligent systems, and visual debugging tools for machine learning models. Notable projects include the HEART initiative for real-time healthcare analytics and development of the DETOXER explanation framework for temporal classification systems. Recent publications investigate nudge techniques for behavioral change (Romadoro project), anchoring bias effects in AI system trust, and evaluation of view rotation techniques in virtual reality navigation. Their work consistently bridges technical AI advancements with human-centered design principles. No academic awards are listed in the provided materials. Current affiliations include Northeastern University's research groups in AI ethics, human-computer interaction, and healthcare technology innovation.

Joyoung LeeView profile

Associate Professor

• Connected Vehicle (CV) Systems
• Traffic Management
• Autonomous Vehicle Control
• +5 more

Dr. Joyoung Lee is an Associate Professor in the Department of Civil and Environmental Engineering at New Jersey Institute of Technology (NJIT). He previously served as Laboratory Manager at the Federal Highway Administration's Saxton Transportation Operations Laboratory. His research focuses on Connected Vehicle (CV) systems, including applications in traffic management, signal control optimization, and autonomous vehicle infrastructure integration. Dr. Lee holds a Ph.D. (2010) and M.S. (2007) in Transportation Engineering from the University of Virginia, and a B.S. (2000) in Transportation Engineering from Hanyang University. His work emphasizes CV-based solutions for real-time traffic systems, cooperative vehicle-infrastructure systems (CVIS), and autonomous vehicle integration. Notable achievements include the 2019 IEEE CAVS Best Paper Award and multiple best paper recognitions from PTV User Group Meetings. His research also addresses traffic safety through innovations like the Virtual Guide Dog system for visually impaired pedestrians and advanced traffic monitoring frameworks using LiDAR and computer vision. Education: Ph.D., Transportation Engineering, University of Virginia (2010) M.S., Transportation Engineering, University of Virginia (2007) B.S., Transportation Engineering, Hanyang University (2000) Dr. Lee's research interests span smart city infrastructure, edge computing for traffic systems, and sustainable transportation solutions. He has pioneered algorithms for cooperative intersection management, automated platooning systems, and federated learning-based traffic optimization. His work bridges theoretical models with real-world implementation through partnerships with FHWA and industry stakeholders. Key contributions include development of the Cumulative Travel-Time Responsive (CTR) traffic signal control system, smart arrival notification systems for paratransit services, and advanced microsimulation calibration techniques. His lab focuses on translating CV data into actionable strategies for safer, more efficient transportation networks. Awards: IEEE CAVS Best Paper Award (2019) ASCE Grand Challenge Innovation Contest Honorable Mention (2017) PTV VISSIM Best Paper Awards (2012, 2008) Excellence in Research Award (University of Virginia, 2011) Ongoing projects include semi-decentralized graph neural networks for traffic forecasting and low-cost LiDAR-based traffic monitoring systems. His work addresses critical challenges in autonomous vehicle integration, incident management, and infrastructure resilience through interdisciplinary collaborations.

• Graph Representation Learning
• Graph Neural Networks
• Deep Generative Models
• +5 more

Jian Tang is an Assistant Professor at HEC Montréal and a core member of the Montreal Institute for Learning Algorithms (MILA). His research focuses on graph representation learning, generative models, and their applications in drug discovery and material science. Prior to this, he was a postdoctoral researcher at the University of Michigan and Carnegie Mellon University, and a researcher at Microsoft Research Asia (2014-2016). He has received several prestigious recognitions, including the Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) and best paper nominations at WWW’16. His work on LINE (WWW’15) was recognized as the most cited paper in its year. Tang’s research spans theoretical foundations and practical systems, such as GraphVite for scalable graph embedding and TorchDrug for drug discovery. Key research interests include geometric deep learning for molecular structures, generative models for protein design, and neural-symbolic reasoning for knowledge graphs. He actively collaborates with leading biological labs and leverages industry partnerships for GPU resources. Recent publications emphasize molecular property prediction, 3D conformation generation, and algorithmic reasoning frameworks. He has secured grants from IBM/MILA, Amazon, and the National Research Council Canada, supporting projects like molecular pretraining and geometric representation learning. Tang teaches courses on graph representation learning and deep learning, and mentors a vibrant team of PhD and master’s students. His lab has developed impactful software tools like LINE, PTE, and LargeVis, widely used in the research community.

Ali YaycıoğluView profile

Associate Professor

• Ottoman Empire
• Modern Turkey
• Political Institutions
• +5 more

Ali Yaycıoğlu is an Associate Professor of History at Stanford University, serving as Director of the Abbasi Program in Islamic Studies and Middle Eastern Studies Forum. His work focuses on Ottoman Empire and Modern Turkey, integrating digital tools to analyze political, economic, and legal institutions. He holds affiliations with the Center on Democracy, Development and the Rule of Law, and the Freeman Spogli Institute for International Studies. B.S. in International Relations (Middle East Technical University, 1994) M.A. in History (Bilkent University, 1997) Graduate Studies in Islamic Studies (McGill University, 1998) Ph.D. in History and Middle Eastern Studies (Harvard, 2008) His research explores Ottoman political and financial systems, with current projects examining debt networks (The Order of Debt) and Ottoman political communities. He leads digital initiatives like Charting the Empire and Mapping Ottoman Epirus, using spatial analysis to map fiscal records and power structures. His work bridges historical analysis with digital humanities, producing visualizations of Ottoman networks. Notable publications include Partners of the Empire (2016) and essays on Ottoman global connections. He co-edited a special digital humanities issue of the Journal of Ottoman and Turkish Studies (2023). His research has been supported by grants including the Stanford Data Science Seed Grant (2018). Yaycıoğlu advises the Stanford Ottoman World Series and engages in public scholarship through media commentary on Turkish politics. His artistic projects under 'Critical Imagination' explore historical themes through visual arts, further bridging academic and creative domains.

• Robotics
• Computer Vision
• Sensor Systems
• +3 more

Dr. Olga Vysotska is a Researcher affiliated with the Professorship for Robotic Systems at ETH Zurich's Department of Mechanical and Process Engineering. Her work focuses on advancing robotic systems through research in sensor-based navigation, SLAM (Simultaneous Localization and Mapping), and autonomous systems. She holds a doctoral degree and is based in Zurich, Switzerland. Her email is olga.vysotska@inf.ethz.ch. Research Interests: Olga's research spans robotics, computer vision, and autonomous navigation. She specializes in LiDAR-based place recognition, SLAM algorithms, and cross-modal localization using 3D scene graphs. Her work addresses challenges such as environmental changes, sensor fusion, and data association in dynamic environments like agriculture and underground exploration. Key themes include robust localization, loop closure detection, and adaptive algorithms for real-world robotic applications. Publications Overview: Olga's recent work emphasizes diffusion-based LiDAR place recognition (2025), 4D spatial-temporal mapping for agricultural robots (2023), and SceneGraphLoc for cross-modal localization (2024). Her research trends highlight innovation in sensor integration, algorithmic robustness, and practical applications in challenging environments. Earlier contributions include exploration of catacombs with mobile robots (2013) and SLAM enhancements using public map data (2017). Grants & Advising: While specific grants or student advisement details are not listed, her active publication record suggests involvement in funded research projects. Her work often collaborates with industry and academic partners to advance robotic autonomy in complex scenarios. Labs/Teams: As part of the Robotic Systems Professorship, she likely contributes to ETH Zurich's robotics labs focused on SLAM, sensor systems, and autonomous navigation. Her projects may intersect with the Department's broader initiatives in mechanical and process engineering.

• Computer Network Security
• Mobile Computing
• Cloud Computing
• +4 more

Dr. Dijiang Huang is an Associate Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He joined ASU in 2005 after completing his Ph.D. in Telecommunications and Computer Networking from the University of Missouri-Kansas City (2004). His research focuses on cybersecurity, mobile computing, and cloud computing, supported by grants from the National Science Foundation (NSF), Office of Naval Research (ONR), and industry partners like HP. He has received prestigious awards, including the ONR Young Investigator Award and HP Innovative Research Award. Education: B.E. in Telecommunications, Beijing University of Posts and Telecommunications (1995) M.S. in Computer Science, University of Missouri-Kansas City (2001) Ph.D. in Telecommunications and Computer Networking, University of Missouri-Kansas City (2004) Research Interests: Huang’s work emphasizes secure communication protocols, privacy-preserving techniques, and resilient network architectures. He has pioneered frameworks like Secure Group Communication (SeGCom) and Attribute-Based Cryptography , addressing challenges in VANETs, SDN, and edge computing. His recent projects include developing Waterfall for SDN security and SmartDefense for DDoS mitigation. Grants & Awards: ONR Young Investigator Award (2008) HP Innovative Research Award (2008) NSF grants for secure mobile cloud frameworks and cyber-physical systems Professional Contributions: Huang has served as a reviewer for journals like IEEE Transactions on Wireless Communications and conferences such as ACM MobiArch. He co-developed the Open Human-Robotic Mobile Networking and Security Testbed (OHReST) and the Virtual Laboratory (VLab) for cybersecurity education.

Elaine GerberView profile

Associate Professor

• Medical Anthropology
• Disability Studies
• Food Studies
• +3 more

Elaine Gerber is an Associate Professor of Anthropology at Montclair State University (MSU), affiliated with the College of Humanities and Social Sciences. Her research focuses on the intersection of disability studies, medical anthropology, and food systems, emphasizing disability as a social construct. She holds a PhD from UCLA and has conducted extensive fieldwork on disability culture, accessibility, and food insecurity. Education: PhD, Anthropology, University of California, Los Angeles (1999) MA, Anthropology, University of California, Los Angeles (1999) BA, Anthropology, University of Michigan, Ann Arbor (1989) Research Interests: Disability studies and cultural anthropology Food insecurity among disabled populations Audio description and accessibility Intersection of race, gender, and disability Her work bridges theory and practice, including community-based participatory research projects like the #EatDis initiative examining barriers to food access for disabled individuals. Notable publications explore disability identity, food as a site of resistance, and the built environment's impact on marginalized groups. Awards & Grants: Recipient of the 2018 Society for Applied Anthropology Fellowship, Chateaubriand Fellowship (1996), and Montclair State’s “Best Professor” recognition (2019). Funded projects include a Robert Wood Johnson Foundation grant ($100k) on physical activity barriers for people with disabilities. Teaching & Service: Teaches courses on disability studies, medical anthropology, and food studies. Founded MSU’s Disability Caucus and volunteers with organizations like the Reelabilities Film Festival. Served as President of the Society for Disability Studies (2007–2009). Labs/Teams: Leads the #EatDis research project and collaborates with the World Institute on Disability on food education initiatives.

• Historical Archaeology
• Marginalized Communities
• Community-Engaged Research
• +3 more

Christopher N. Matthews is a historical archaeologist and Professor of Anthropology at Montclair State University, where he serves as Chairperson of the Department of Anthropology within the College of Humanities and Social Sciences. His research focuses on the archaeology and history of marginalized and racialized communities in North America, particularly in the mid-Atlantic region, with an emphasis on community-engaged research and teaching. He has authored and edited influential works such as *The Archaeology of American Capitalism* and *The Archaeology of Race in the Northeast*. Current projects include investigations into historic African American communities in New Jersey, settler/slaveowner sites, and Native American ceremonial landscapes in Sussex County. Education: B.A., George Washington University; M.A., M.Phil., and Ph.D., Columbia University Teaching: Courses on the anthropology of race, Native North Americans, historical archaeology, and public archaeology Research Interests: Intersection of race, labor, and heritage; material culture of marginalized groups; community collaboration in archaeological practice Matthews’ work challenges traditional narratives by centering the voices of historically excluded communities. His recent book, *A Struggle for Heritage*, examines how conflicting histories perpetuate social inequalities. He actively collaborates with the Center for Heritage and Archaeological Studies and advocates for inclusive preservation practices.

Abraham SilberschatzView profile

Professor

• Database Systems
• Operating Systems
• Storage Systems
• +3 more

Abraham Silberschatz is the Sidney J. Weinberg Professor of Computer Science at Yale University. He previously served as Vice President of the Information Sciences Research Center at Bell Laboratories and held a chaired professorship at the University of Texas at Austin. His research focuses on database systems, operating systems, and network management. Silberschatz has advised over a dozen PhD students, many now in academia and industry. Education: Ph.D., Computer Science, Stony Brook University (SUNY) Research Interests: His work spans database systems, operating systems, storage systems, and network management. Notable contributions include foundational textbooks like Operating System Concepts and Database System Concepts , which have become industry standards. He has also developed innovative systems like DataPlay and contributed to projects such as NetInventory. Publications: His 15+ years of research include influential papers on database architecture, network routing, and distributed systems. Recent work explores leveraging non-volatile memory technologies in systems design. Awards: ACM Karl V. Karlstrom Outstanding Educator Award (1998) IEEE Taylor L. Booth Education Award (2002) VLDB Test of Time Award (2019) Multiple Bell Laboratories President's Awards for innovation Grants & Patents: Recipient of over two dozen grants and over four dozen patents, including foundational IP in multimedia storage and distributed systems. His team's HadoopDB project merged MapReduce and DBMS technologies. Labs/Teams: Collaborates with Prof. Robert Soulé on projects in database systems and networking, focusing on next-gen memory technologies. Active in mentoring graduate students and postdocs in their research group.

Joshua NewView profile

Research Professor

• Building Energy Modeling
• Climate Change Science
• Supercomputing
• +5 more

Dr. Joshua New is a Distinguished R&D Staff Member at Oak Ridge National Laboratory (ORNL) and holds a Joint Faculty Position at The University of Tennessee since 2012. He leads research in building energy modeling, climate change science, and supercomputing. His work focuses on urban-scale energy systems, AI-driven analytics, and high-performance computing applications. Education: Ph.D. in Computer Science (University of Tennessee, 2009), M.S. in Computer Systems, B.S. in Computer Science and Mathematics (Jacksonville State University). His research interests include optimizing building energy efficiency, simulating climate impacts on urban infrastructure, and developing tools like AutoBEM and ModelAmerica to model 122.9 million U.S. buildings. He has over 150 peer-reviewed publications and led 45+ projects involving supercomputing, visual analytics, and AI for big data. Awards include the R&D 100 Award (2016), ASHRAE Distinguished Service Award (2018), and Lab-Corps (2015). His teams prioritize utility use cases and validate models against real-world data. He is a Senior IEEE member, Certified Energy Manager (CEM), and holds certifications in project management and energy efficiency. Key contributions include the Roof Savings Calculator Suite, AutoGen/AutoSim tools, and the ModelAmerica initiative. His work addresses national energy policy, heatwave resilience, and sustainable city design through interdisciplinary collaborations.

• Human-Computer Interaction
• Responsible Innovation
• AI Ethics
• +8 more

Helena Webb is a Visiting Lecturer in the Department of Computer Science at the University of Oxford, where she contributes to research and teaching within the Human Centred Computing theme. Her work bridges social science and computer science, focusing on responsible innovation, AI ethics, and user interactions with digital technologies. PhD in Social Sciences, University of Nottingham Bachelor’s in Social and Political Sciences, University of Cambridge Former Senior Researcher, University of Oxford Department of Computer Science Researcher at Work, Interaction and Technology (WIT) Research Centre, King’s College London (2009–2014) Her research interests include human-computer interaction, algorithmic fairness, privacy in smart homes, and ethical design of social robots. She specializes in qualitative research methods and interdisciplinary collaboration to understand how technology shapes and is shaped by social practices. She has led and contributed to major projects such as Digital Wildfire , UnBias , ReEnTrust , and RoboTIPS , all focused on responsible governance and design of digital systems. Her recent publications span topics from algorithmic accountability to ethical black boxes in robotics, reflecting a strong trend toward integrating ethical considerations into the technical design of AI and interactive systems. These works emphasize participatory design, transparency, and societal impact. Scientific Awards and Recognition: Named one of the Brilliant Women working in AI Ethics She actively supervises and co-supervises students, contributes to ethics education, and is involved in outreach and diversity initiatives at Oxford. She has also served on the Departmental Equality and Diversity Committee and the Research Ethics Committee. Helena is a member of the advisory board for the ReEnTrust project and continues to develop the ethical hackathon model with colleagues. Her work exemplifies a deep commitment to interdisciplinary, socially responsible research in computing.

Thomas Michael SattichView profile

Associate Professor

• Geopolitics
• Sustainability Transition
• Energy Policy
• +4 more

Thomas Michael Sattich is an Associate Professor at the University of Stavanger , affiliated with the Faculty of Social Sciences and Department of Media and Social Studies . His research focuses on geopolitical implications of sustainability transitions, particularly energy policy interdependence and EU-China relations. PhD in Political Science and Economics Expertise in qualitative methods, mixed methods (cluster analysis), and data visualization Lead researcher on EU-funded digital climate negotiation simulation projects His recent publications examine renewable energy geopolitics, industrial policy competition, and sustainability education frameworks. Methodologically, he specializes in Qualitative Comparative Analysis (QCA) and network analysis, contributing to debates on energy security and regional cooperation.