Find Academic Supervisors

Gerhard SchwabeView profile

Professor

• Collaborative Technologies
• Information Management
• E-Government
• +5 more

Gerhard Schwabe is a Professor in the Department of Informatics at the University of Zurich, Faculty of Business, Economics and Informatics. His research spans collaborative technologies, information management, E-government, blockchain applications, and digital health. He leads the Information Management Research Group and contributes to the university's Digital Society Initiative (DSI). Research Focus: Human-AI collaboration, blockchain systems, crisis informatics, persuasive technologies Key Projects: RefuGPT (refugee support chatbots), Scripted Medicine (health worker assistance), PROMISE (AI prompt orchestration) Technical Expertise: Design Science Research, conversational agents, data-driven governance His recent publications emphasize AI integration in collaborative workflows, blockchain applications for data markets, and digital solutions for crisis management. He explores how generative AI impacts freelance development practices and transforms advisory services through automated systems. Contact: schwabe@ifi.uzh.ch

Georgi GanevView profile

Researcher

• Machine Learning
• Privacy-Preserving Technologies
• Data Synthesis
• +3 more

Georgi Ganev is a PhD Researcher at University College London (UCL) and Principal Research Scientist at SAS, following the acquisition of Hazy, a synthetic data company. He is part of UCL's Information Security Research Group under Professors Emiliano De Cristofaro and David Barber. His research focuses on advancing privacy-preserving synthetic data techniques, particularly in machine learning and differential privacy. Key areas include developing DP generative models, auditing privacy mechanisms, and addressing legal implications of synthetic data. Education: MSc in Computational Statistics and Machine Learning (UCL, supervised by Prof. Sebastian Riedel) and BSc in Business Mathematics and Statistics (LSE, supervised by Prof. Wicher Bergsma). Research Interests: Privacy-preserving synthetic data, differential privacy, privacy auditing, generative models, and regulatory compliance. His work has led to 25+ discovered privacy bugs in open-source libraries and vulnerabilities in deployed systems, with publications in top-tier conferences like IEEE S&P, USENIX Security, and ICML. Notable Achievements: Distinguished Paper Award at IEEE S&P 2025. His research has been integrated into SAS's synthetic data products, impacting industry adoption. Open-source contributions include dpmm and dpart libraries for DP synthetic data generation. Publications: Over 15 peer-reviewed articles, including works on privacy metrics inadequacy, PATE-GAN benchmarking, and synthetic data regulatory challenges. Active in workshops on generative AI and law, and deployment challenges in enterprise settings.

Johes BaterView profile

Assistant Professor

• privacy-preserving analytics
• federated databases
• differential privacy
• +6 more

Johes Bater is an Assistant Professor of Computer Science at Tufts University's School of Engineering. He joined Tufts in 2022 after postdoctoral research at Duke University's Database Group and a Ph.D. in Computer Science at Northwestern University. Education B.Sc. in Electrical Engineering (2011) from Stanford University M.Sc. in Electrical Engineering; Computer Systems (2013) from Stanford University Ph.D. in Computer Science (2020) from Northwestern University Research Focus Bater's research focuses on privacy-preserving analytics , balancing security , privacy , and utility in trustworthy database systems . His work spans differential privacy , secure computation , and data federation to enable robust distributed analytics with provable guarantees. Publications & Trends His publications since 2016 emphasize secure multi-party computation (SMCQL, 2016), differentially private indexing (Longshot, 2023), and privacy-utility trade-offs in federated databases. Key subfields include private data sharing , access pattern security , and incremental computation for outsourced systems. Awards & Grants 2022: Cisco Systems grant for "A Usable and Shareable Tool for Software Threat Modeling" Teaching & Service Bater teaches courses like Database Systems , Dissertation Research , and Special Topics in Data Infrastructure . He served on Tufts' CS PhD Admissions Committee (2022) and as a reviewer for the ACM Conference on Computer and Communications Security (2022).

Sun-ha HongView profile

Assistant Professor

• Critical Data Studies
• Surveillance Studies
• Science and Technology Studies (STS)
• +5 more

Sun-ha Hong is an Assistant Professor in the School of Communication at Simon Fraser University, with affiliations at Stanford’s Humanities Center, SFU’s Digital Democracies Institute, and the VINCI Institute. Her work critically examines data-driven technologies, surveillance practices, and the epistemological shifts in a machine-readable society. Hong holds a PhD from the Annenberg School for Communication (2016), and has held fellowships at MIT and Microsoft Research. Her research focuses on the limits of datafication, exploring how predictive technologies and algorithmic systems reshape knowledge production. Key themes include speculative inequality, the politics of prediction, and the societal implications of AI bias. Hong’s monograph Technologies of Speculation (2020) analyzes state surveillance and self-tracking technologies, arguing that datafication creates gaps between technological promises and social realities. Hong has secured over $280,000 in SSHRC grants and serves on editorial boards for Media Peripheries and Big Data & Society . Her teaching spans AI ethics, surveillance studies, and media historiography, with courses like AI, Algorithms and Power . She advises 11 graduate students researching topics from biopolitical surveillance in China to gendered AI violence. Her recent work explores ‘speculative drama’ in generative AI and the ritualized temporality of technological futures. Hong frequently advises Canadian government bodies on AI policy and digital governance, balancing academic rigor with public engagement.

Francesco GrecoView profile

Research Fellow

• Human-Computer Interaction
• Usable Security
• End-User Development
• +4 more

Francesco Greco is a Research Fellow and Ph.D. student at the University of Bari Aldo Moro's Computer Science Department, actively contributing to the Interaction, Visualization, Usability & UX (IVU) Laboratory under Prof. Maria Francesca Costabile. He completed a visiting research position at King's College London's Cybersecurity (CYS) group from October 2023 to March 2024 under Prof. Luca Viganò's supervision. His academic qualifications include: Master's degree in Computer Science (2022, University of Bari, full marks with honors) Bachelor's degree in Computer Science and Digital Communication (2020, University of Bari - Taranto, full marks with honors) Greco's research centers on Human-Computer Interaction and Usable Security , with specialized expertise in End-User Development , Internet of Things security , Computer Vision , and eXplainable AI for cybersecurity . His work develops human-centered security tools that translate technical findings into actionable user protections, particularly through phishing detection systems that generate intuitive explanations. Analysis of his 15 recent publications (2023-2025) reveals a cohesive research trajectory focused on XAI-driven security interventions . Key themes include timing optimization for phishing warnings, human factors in cybersecurity incidents, and LLM-based educational tools. His work consistently bridges theoretical HCI principles with practical security applications, as demonstrated by tools like APOLLO for phishing email analysis. Greco actively collaborates within the IVU Lab ecosystem and maintains international partnerships, including his recent work at King's College London. His research output demonstrates significant contributions to usable security frameworks and cybersecurity education methodologies.

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

Miao PanView profile

Associate Professor

• Privacy Preserving Deep Learning
• Wireless Networking
• Internet of Things
• +3 more

Dr. Miao Pan is an Associate Professor in the Department of Electrical and Computer Engineering at the Cullen College of Engineering, University of Houston. He directs the PAN Lab (panlab.ece.uh.edu) focusing on wireless networking, security, and IoT applications. His educational background includes a B.S. in Electrical Engineering from Dalian University of Technology (2004), M.S. from Beijing University of Posts and Telecommunications (2007), and Ph.D. from the University of Florida (2012). Dr. Pan's research spans privacy-preserving deep learning, wireless networking, machine learning applications in communications, underwater systems, and cognitive radio networks. His interdisciplinary approach combines theoretical foundations with practical implementations in emerging technologies. Recent publications demonstrate strong focus on federated learning optimizations, wireless sensing innovations, and security mechanisms for next-generation systems. Key trends include energy-efficient mobile AI, robust authentication methods, and adaptive underwater networking solutions. Honors include: NSF CAREER Award (2014) 5 IEEE Best Paper Awards (2015-2019) University of Florida Graduate Fellowship (2007) He leads multiple federally funded projects and advises graduate researchers in wireless systems and security. The PAN Lab collaborates with industry partners to translate research into practical solutions for IoT and 5G/6G networks.

Sang-Hyop LeeView profile

Professor

• Population Economics
• Labor Markets
• Social Welfare Policy
• +3 more

Dr. Sang-Hyop Lee is a Professor in the Department of Economics at the University of Hawaii at Manoa (UHM), where he has held academic positions since 1999, progressing from Assistant Professor (1999-2006) to Associate Professor (2006-2012), and Professor since 2012. He served as Chair of the Department of Economics from 2020 to 2024 and previously as Director of the Center for Korean Studies (2013-2018). His primary affiliations include the University of Hawaii Economic Research Organization (UHERO) and the Center for Korean Studies. Dr. Lee holds a Ph.D. in Economics from Michigan State University (1998), alongside MA and BA degrees in Economics from Seoul National University (1988 and 1986 respectively). His research focuses on population dynamics, labor markets, and social welfare policies, particularly in Asian economies. Key areas include aging societies, demographic dividends, fiscal sustainability, and the economic implications of low fertility. Dr. Lee leads the National Transfer Accounts (NTA) global network, coordinating research in over 100 countries. He has authored or edited over a dozen books, including Aging, Economic Growth, and Old-Age Security in Asia and Social Policies in an Age of Austerity . Notable awards include the 2019 Presidential Personal Commendation from the Republic of Korea. His advisory roles include chairing 24 doctoral committees and serving on numerous boards, including the Center on Aging and the Friends of the Library. He has secured major grants from institutions like the Asian Development Bank, Korea Development Institute, and UN agencies. His work bridges academic research with policy impact, addressing global challenges in aging populations and economic development.

• Autonomous Driving
• Machine Learning
• Wireless Communication
• +11 more

Dr. Tao (Kevin) Huang is a researcher at James Cook University's College of Science and Engineering, with expertise spanning autonomous driving, wireless communication systems, and medical imaging applications. His work integrates machine learning, sensor fusion, and multimodal data analysis to address complex challenges in vehicular networks, environmental monitoring, and healthcare technology. Research Interests: Dr. Huang's research focuses on Autonomous driving perception systems IoT-enabled vehicular networks AI for medical diagnostics and environmental sensing Signal processing and privacy-preserving communication protocols Recent Publications: His 2025 work emphasizes advancements in V2X cooperative perception, radar-LiDAR-camera fusion, and diffusion models for medical imaging. Key trends include cross-modal robustness, real-time processing for autonomous systems, and AI applications in sustainability.

Miao XuView profile

Research Fellow

• Data Science
• Machine Learning
• Time Series Analysis
• +4 more

Dr Miao Xu is a Research Fellow at the University of Queensland (UQ), affiliated with the School of Electrical Engineering and Computer Science within the Faculty of Engineering, Architecture and Information Technology. She holds an Australian Research Council DECRA Fellowship (ARC DECRA), recognizing her early-career research excellence. Her research focuses on machine learning, data science, and time series analysis, with applications in healthcare, materials science, and algorithmic fairness. Dr Xu's work addresses challenges in noisy label handling, unlearning mechanisms, and adaptive modeling for irregular data. Education: She earned a Doctor of Philosophy (PhD) from Nanjing University. She is actively involved in supervising research and contributes to the Centre for Enterprise AI at UQ. Research Interests: Dr Xu’s expertise spans machine learning , time series analysis , deep learning , and unsupervised learning . Her recent work emphasizes robust learning with noisy or incomplete labels, model unlearning, and applications in alloy design and medical informatics. She explores methods like instance-attention GNNs for irregular time series and confidence-guided techniques for adversarial attack detection. Publications: Her recent work includes advancements in GNN-based time series modeling, bias mitigation in text classification, and active learning for alloy design. Key themes include improving generalization, reducing algorithmic bias, and enhancing model transparency. Awards: Her ARC DECRA fellowship (202X–202X) supports her research on data-driven methodologies. Supervision & Grants: Available for PhD supervision in machine learning and data science. Her grants include funding for projects in unlearning mechanisms and spatiotemporal modeling. Labs/Teams: Affiliated with the Centre for Enterprise AI at UQ, collaborating on enterprise-scale AI applications and interdisciplinary research.

• Optical Communications
• Quantum Computing
• Quantum Key Distribution
• +3 more

Professor Dominic O'Brien is a Professor of Engineering Science at the University of Oxford and Senior Research Fellow at Balliol College. He serves as Director of the UK National Hub in Quantum Computing and Simulation. His research focuses on optoelectronics, optical wireless communications, and quantum key distribution. He leads the optical communications group and has authored over 200 publications in these areas. His work emphasizes high-speed free-space optical systems, UV-based secure communication, and beam-steering technologies. Education: MA and PhD from the University of Cambridge, followed by a DPhil from the University of Oxford. His research interests include quantum networks, photonics, and energy-efficient optical systems. Notable projects include handheld low-cost quantum key distribution systems and terabit-per-second fiber-wireless links. He collaborates on initiatives like the WORTECS project for virtual reality applications using optical wireless. Publications span topics from UV solar-blind OWC to liquid crystal beam steering. His work bridges academic and industrial applications, addressing challenges in both classical and quantum communication systems. He contributes to standards for visible light communications and next-generation wireless infrastructure.

Azadeh AnsariView profile

Associate Professor

• Nano/Micro-Electro-Mechanical Systems (N/MEMS)
• RF Applications
• Resonant Devices
• +3 more

Azadeh Ansari is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, holding the Sutterfield Family Early Career Professorship. She received her B.S. from Sharif University of Technology (2010), and M.S. and Ph.D. from the University of Michigan (2013, 2016), followed by a postdoctoral fellowship at Caltech (2016–2017). Her research focuses on nano/micro-electro-mechanical systems (N/MEMS), with emphasis on III-V semiconductors and piezoelectric materials. Key areas include resonant devices for RF applications, nonlinear devices, and integrated microsystems. Ansari leads projects in microscale robotics, phononic frequency combs, and III-V electro-acoustic devices. Research Interests: Resonant devices for timing, sensing, and RF applications III-V mm-wave acoustic filtering Microscale robot design and control Nonlinear resonators and phononic frequency combs III-V electro-acoustic devices and HEMTs Her recent work includes collaborations with NASA JPL on extraterrestrial micro-swimmers and DARPA-funded projects on inertial sensors and high-temperature pressure sensors. Ansari has secured grants from DARPA DSO and presented at IEEE Transducers 2025 with four papers. She advises graduate students such as Zhijian (Chris) Hao, who defended his PhD in 2024. Ansari’s awards include the 2017 ProQuest Distinguished Dissertation Award and the University of Michigan Towner Prize (2016). She serves on the IEEE Sensor’s Young Professional Committee and technical committees for IEEE IFCS 2018. Lab and Collaborations: The Ansari Lab is part of Georgia Tech’s Institute for Electronics and Nanotechnology. Collaborators include Prof. Kimberly Hoang (PBS-featured neurosurgery micro-drillers) and teams at Penn State University. Current projects include DARPA-funded frequency comb inertial sensors and underwater micro-robot sensor development for ICRA 2025.

Judith VerstegenView profile

Assistant Professor

• Geographic Information Science
• Spatial Modelling
• Agent-Based Modelling
• +4 more

Dr. Judith Verstegen is an Assistant Professor in the Department of Human Geography and Spatial Planning at Utrecht University's Faculty of Geosciences. Her research focuses on geosimulation modeling and spatial optimization, with applications in urban planning, environmental vulnerability assessment, and policy analysis. She leads projects such as HEADS 4 Health (2023-2024), which integrates agent-based models into urban digital twins, and coordinates the GeoSIM research group. Her work emphasizes interdisciplinary collaboration, including projects analyzing linguistic diversity in South America and environmental threats to Amazonian indigenous lands. She is the Program Chair of the MSc Geographical Information Management and Applications (GIMA) program and serves as Editor-in-Chief of the Journal of Spatial Information Science. Notable contributions include methodologies for spatial optimization under uncertainty and agent-based modeling of pedestrian behavior in urban environments. Key research areas include applied data science, complex systems analysis, and the PtS - Transforming Cities initiative. She has advised PhD students on topics ranging from fire prevention optimization to indigenous land vulnerability. Her lab at the University of Münster previously focused on spatial modeling frameworks, and she collaborates internationally with institutions like Leiden University and the PBL Netherlands Environmental Assessment Agency. Recent projects highlight innovation in computational methods, such as Python-based open-source tools for land-use modeling (IMAGE-land) and immersive video experiments for behavioral studies. Her work bridges theoretical modeling with practical policy applications, addressing challenges in sustainable urban development and environmental conservation.

Shareq Mohd NazirView profile

Associate Professor

• Greenhouse Gas Mitigation
• Bioenergy Conversion
• Decarbonization of Industry
• +3 more

Shareq Mohd Nazir is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Division of Energy Processes in the Department of Chemical Engineering. He holds a joint appointment within the Digital Futures Faculty, a cross-disciplinary research center addressing societal challenges through digital technology innovation. Nazir earned his PhD in Energy and Process Engineering from NTNU (2018) and holds Master and Bachelor degrees in Chemical Engineering from BITS Pilani. His research focuses on decarbonization strategies including CO2 capture/utilization (CCUS), bioenergy conversion, and methane mitigation. Key methodologies involve techno-economic analysis and process modeling for industrial systems. Nazir leads projects integrating catalytic conversion, waste heat recovery, and gas switching technologies to achieve low-carbon energy systems. He teaches courses on chemical engineering systems, process design, and carbon-neutral energy systems at KTH. Recent publications emphasize multi-gas mitigation strategies, synthetic fuel production via biomass gasification, and cost-effective hydrogen production pathways. His work bridges academia and industry through collaborations with RISE Research Institutes and NTNU. Nazir’s research directly supports Sustainable Development Goals (SDGs), particularly targeting climate action (SDG13) and affordable clean energy (SDG7).

Gregorio IglesiasView profile

Professor

• Marine Renewable Energy
• Coastal Engineering
• Wave Energy Conversion
• +5 more

Prof. Gregorio Iglesias is a Professor of Marine Renewable Energy at University College Cork (UCC) and Honorary Professor of Coastal Engineering at the University of Plymouth. His expertise lies in Marine Renewable Energy and Coastal Engineering, with a focus on wave and tidal energy systems, offshore wind integration, and coastal protection strategies. He has secured over €12M in research funding as Principal Investigator and authored/edited key texts such as Wave and Tidal Energy (Wiley) and Ocean Energy and Coastal Protection (Springer). Education: BEng (Civil Engineering, 1992), MEng (Civil Engineering, 1993), PhD (Engineering, 2001). Research Interests: Advanced modeling of wave energy converters, floating offshore wind turbines, coastal erosion mitigation, and climate change impacts on marine energy resources. His work bridges theoretical advancements and practical applications, including coasts like the Port of Gijón (Spain) and the Shannon Estuary. Recent publications highlight climate-driven renewable energy transitions, multi-hazard coastal resilience frameworks, and techno-economic assessments of offshore systems. He chairs the IEC Standards panel for wave energy device testing and serves as Subject Editor for Energy (Elsevier) . Professional Activities: Lead of Marine Renewable Energy research at MaREI (Ireland), former Head of the COAST Engineering Group at Plymouth (2012–2018), and member of PIANC’s Universities Consortium. His work has generated 5,459 citations with an h-index of 41. Teaching: Delivers modules on Ocean Energy (NE4003/NE6005) and Hydraulics (CE3007).