Find Academic Supervisors

Cristina LopesView profile

Professor

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +5 more

Cristina Lopes is a Professor of Informatics at the Donald Bren School of Information and Computer Sciences , University of California, Irvine. She holds administrative roles including Director of the Master of Software Engineering Program and former Director of the Institute for Software Research . Her research focuses on software engineering, programming languages, and distributed systems, with contributions to open-source projects like OpenSimulator and AspectJ. She has authored the influential book Exercises in Programming Style . Education: PhD from Northeastern University, MS/BS from Instituto Superior Técnico (Portugal). Awards include IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). She co-founded a virtual reality company for urban redevelopment and leads NSF-funded projects, including the prestigious CAREER Award. Research Interests: Large-scale software systems, aspect-oriented programming, code clone detection, and applying AI to programming challenges. Her work bridges theory and practice, with applications in urban simulation and healthcare systems. Awards and Grants: Over 15 awards including national and international distinctions. Grants focus on scalable software tools and environmental sustainability in computing. Labs/Teams: Leads the Software Engineering Research Group and collaborates with industry partners on open-source infrastructure and AI-driven development tools.

Pubali DattaView profile

Assistant Professor

• Security and Privacy
• Networking and Distributed Systems
• Serverless Cloud Security
• +5 more

Pubali Datta is an Assistant Professor at the University of Massachusetts Amherst , affiliated with the Manning College of Information & Computer Sciences. She specializes in system security and privacy research, focusing on emerging technologies like serverless computing, IoT, and cloud architectures. Her work bridges technical security challenges with human factors through user studies. PhD in Computer Science (2023) from University of Illinois Urbana-Champaign ME in Computer Science (2013) from Jadavpur University BTech in Computer Science (2011) from West Bengal University of Technology Her research explores core system vulnerabilities obscured by modern abstractions, developing mechanisms for access control , information flow analysis , and auditing . She combines technical analysis with human-centric studies to address security misconfigurations in smart homes and cloud environments. Recent publications focus on serverless security , endpoint protection , and IoT threat modeling , appearing at top venues like IEEE S&P and USENIX Security. Her work has been recognized with a IEEE S&P Distinguished Paper Award (2023) . IEEE S&P Distinguished Paper Award (2023) She collaborates with the Secure & Transparent Systems Laboratory and works on practical solutions for real-world security challenges.

• Multiagent Systems
• Agent Architecture
• Agent-based Simulation
• +7 more

Julian Padget is a Reader (equivalent to Associate Professor) in the Department of Computer Science at the University of Bath, with extensive affiliations across multiple research centers including the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa), Water Innovation and Research Centre (WIRC), UKRI CDT in Accountable, Responsible and Transparent AI, Centre for Therapeutic Innovation, and Institute for Digital Security and Behaviour (IDSB). His work bridges computer science with energy systems, healthcare, and digital governance through interdisciplinary collaborations. Padget's research centers on multiagent systems , agent architecture , norm representation and reasoning , and fusing symbolic and statistical AI , with significant contributions to distributed ledgers, policy modeling, and narrative models. His fingerprint analysis reveals dominant connections to multi-agent systems (100%), web services (72%), and normative frameworks (48%), reflecting his focus on creating ethically aligned autonomous systems for complex socio-technical environments. Recent work demonstrates increasing integration of AI with energy infrastructure and biomedical applications. Analysis of his 15 most recent publications shows a clear trajectory toward operationalizing AI ethics, particularly in bias management and trust frameworks, while maintaining strong foundations in multiagent coordination. His energy sector research increasingly focuses on digital spine architectures for data sharing, and biomedical collaborations explore molecular imaging techniques for cancer research. The consistent thread across domains is the development of governance frameworks for autonomous systems. Padget actively supervises doctoral students with 23 supervised works documented and serves as Principal Investigator on major grants including EPSRC-funded energy network projects (2025-2026) and Innovate UK collaborations with the BBFC. His policy impact is evidenced by parliamentary testimony in March 2025 that generated coverage across 16 news outlets. Current projects emphasize AI for agile energy networks, value-aware agent architectures, and statutory compliance frameworks for online media. His laboratory ecosystem spans the IAAPS Innovation Bridge and Institute for Digital Security and Behaviour, focusing on translating theoretical agent frameworks into practical applications for energy systems, digital governance, and health interventions. The Water Innovation and Research Centre provides critical infrastructure for his energy-related simulations, while therapeutic innovation collaborations enable biomedical applications of his norm-representation frameworks.

Cathy van DyckView profile

Associate Professor

• Health Care
• Organizational Behavior
• Error Management
• +3 more

Dr. Cathy van Dyck is an Associate Professor at the Vrije Universiteit Amsterdam (VU), holding positions in the Faculty of Social Sciences and Humanities, Department of Organization Sciences, as well as dual appointments at the Network Institute and the Organization & Processes of Organizing in Society (OPOS) research group. Her work focuses on organizational behavior, error management, and patient safety in healthcare settings. She is also the owner of The cat's Eye in Amsterdam since 2013. Her research explores how organizations handle errors, particularly in healthcare environments, emphasizing crew resource management (CRM) training, safety culture, and psychological safety. She has conducted studies in intensive care units (ICUs) and emergency departments, analyzing team dynamics and communication strategies. Her work also addresses professional identity threats and organizational learning mechanisms. Over 15 years, her articles consistently investigate error management frameworks, CRM implementation, and trust dynamics in teams. Recent studies highlight the importance of explicit communication in clinical settings and the mediating role of cognitive focus on task performance. Her research bridges aviation safety practices with healthcare, examining cross-industry applications. While no scientific awards are explicitly mentioned, her contributions to patient safety and organizational learning are recognized through her extensive publication record and collaborative activities. She has supervised 7 PhD theses and actively participates in academic activities such as lectures and editorial work, focusing on error management, trust, and safety culture. Dr. van Dyck is affiliated with multidisciplinary research teams including the Network Institute, which emphasizes innovation in complex societal challenges, and the OPOS group, dedicated to understanding organizational processes. Her teaching includes courses on policy communication and organizational issues, reflecting her expertise in translating research into actionable insights.

Ralph-Günther HolzView profile

Associate Professor

• Computer Science
• Cybersecurity
• Network Security
• +3 more

Ralph-Günther Holz is an Associate Professor at the Digital Society Institute and the Department of Design and Analysis of Communication Systems. His work focuses on cybersecurity, network security, and federated learning. He is recognized for contributions to transport layer security, DNS dependencies, and cloud detection mechanisms. With an h-index of 14 and 886 citations, his research spans from foundational network protocols to applied security solutions. Recent collaborations include studies on Australian DNS dependencies and Dutch critical infrastructure security. His research interests include analyzing network vulnerabilities, optimizing secure communication in federated learning, and leveraging DNS records for cloud detection. Key contributions include work on web crawler security, dependency graph analysis, and threat intelligence. Holz has supervised one documented research project, contributing to applied networking and security domains. His work aligns with UN Sustainable Development Goals related to infrastructure resilience and digital inclusion. He frequently publishes in top venues like PAM, DSN, and CNSM, focusing on practical security solutions for modern communication systems.

Amanda SelwoodView profile

Researcher

• Healthy Brain Ageing
• Twins Research
• Cognitive Science
• +3 more

Dr Amanda Selwood is a Researcher at the Centre for Healthy Brain Ageing (CHeBA) within the School of Psychiatry at UNSW Sydney. She coordinates the Older Australian Twins Study (OATS), focusing on distinguishing genetic and environmental influences on healthy brain aging. Her PhD in Human Cognition and Brain Science from Macquarie University explored collaborative remembering in twins and siblings. Prior roles include health services research at the Australian Institute of Health Innovation and memory research at UNSW Art & Design. Her research interests span healthy brain aging, twin methodologies, cognitive science, and gerontology. Education: PhD in Human Cognition and Brain Science, Macquarie University Research Focus: Dr Selwood’s work examines behavioral and environmental factors influencing cognitive aging, leveraging twin studies to disentangle genetic and social determinants. She investigates memory enhancement technologies for older adults and contributes to improving surgical patient outcomes through health services research. Her interdisciplinary approach bridges cognitive science, clinical psychology, and healthcare policy. Awards & Recognition: No scientific awards explicitly mentioned in available texts. Advising & Grants: No formal advisees listed. Contributions include protocol development for large-scale studies and ethical governance frameworks in healthcare research. Labs & Teams: Core member of the Older Australian Twins Study (OATS), collaborating with CHeBA’s multidisciplinary team to advance dementia research and healthy aging strategies.

Rishee JainView profile

Associate Professor

• Urban Sustainability
• Building Energy Efficiency
• Data Analytics
• +3 more

Rishee Jain is Associate Professor of Civil and Environmental Engineering at Stanford University. His research develops data-driven solutions for urban sustainability challenges at the intersection of civil engineering, data science, and social science. The Stanford Urban Informatics Lab focuses on: (1) Socio-spatial dynamics of commercial building energy use, (2) Data-driven urban building benchmarking, (3) Sustainability planning in built environments, (4) Coupled urban system dynamics using machine learning. Recent projects analyze agricultural expansion impacts on biodiversity and economic valuation in forest-agriculture landscapes. Publications demonstrate a strong focus on urban building energy modeling (UBEM), machine learning applications for sustainability, occupant behavior analytics, and equity dimensions of energy systems. Recent work increasingly incorporates generative AI, wearable sensors, and spatial justice frameworks.

Jat SinghView profile

Research Professor

• Algorithmic Accountability
• AI Governance
• Data Privacy & Protection
• +6 more

Dr. Jat Singh is a Research Professor at the University of Cambridge's Department of Computer Science and Technology (Computer Laboratory), leading the Compliant and Accountable Systems research group. His interdisciplinary work bridges computer science and law, focusing on technology's legal and regulatory compliance, governance of AI/ML systems, and ethical data practices. He co-chairs the Trust & Technology Initiative and is a Fellow of the Alan Turing Institute. Education: PhD in Computer Science (Distributed Systems & Security) from the University of Cambridge, with prior legal studies. Professional background includes roles in IT services, a medical IT startup, and consulting, emphasizing governance-intensive sectors like healthcare and judiciary. Research interests include accountability in AI, IoT compliance, data justice, and ethical algorithmic systems. Notable projects include RAInS (accountability in AI), legally-compliant IoT frameworks, and data governance in modern slavery contexts. His work explores transparency, fairness, and auditability in technology. Scientific Awards: EPSRC Fellowship and Alan Turing Institute Fellowship. Active in tech-policy advising, collaborating with governments, regulators, and civil society. Teaching: Leads the Technology, Law & Society module in the Advanced Computer Science MPhil. Supervises student projects on algorithmic accountability, security, and societal impacts of technology. Labs/Teams: Heads the Compliant & Accountable Systems Group and contributes to the Trust & Technology Initiative, advancing interdisciplinary research on technology's societal implications.

Pramod K. VarshneyView profile

Professor

• Distributed sensor networks
• Data fusion
• Statistical inference
• +4 more

Pramod K. Varshney is a Distinguished Professor at Syracuse University's Department of Electrical Engineering and Computer Science, within the College of Engineering & Computer Science. He also holds adjunct professorships at Upstate Medical University (Radiology) and Xidian University (China). His research focuses on distributed sensor networks, data fusion, machine learning, and signal processing, with applications spanning defense, healthcare, and IoT. Varshney has led over four decades of research funded by major agencies like DoD, NSF, and industry partners. Education: PhD (Electrical Engineering, University of Illinois, 1976), MS (1974), BS (1972). His research interests emphasize foundational aspects of data/information fusion, sensor networks, and AI-driven analytics. Notable contributions include pioneering work in distributed detection theory and secure inference in adversarial environments. Recent publications highlight advancements in federated learning, anomaly detection, and multi-target tracking. Varshney has been honored with prestigious awards such as the IEEE Fellow (1997), Yaakov Bar-Shalom Award (2018), and Syracuse University's Chancellor’s Lifetime Achievement Award (2023). He has advised numerous PhD and Master’s students, contributing to over 350 publications, including seminal books like Distributed Detection and Data Fusion (Springer, 1997). He has directed Syracuse's CASE (Center for Advanced Systems and Engineering) and actively collaborates with global institutions. His work bridges theoretical advancements with real-world applications in healthcare imaging, cybersecurity, and autonomous systems.

Victor AkinwandeView profile

Researcher

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +7 more

Victor Akinwande is a doctoral researcher at Carnegie Mellon University's Computer Science Department under advisor J. Zico Kolter. His research focuses on robust machine learning systems, causal inference for global health applications, and advancing vision-language models through generative modeling techniques. He holds an MSc in Information Technology (CMU, 2016–2018) and a BSc in Computer Science from the University of Ilorin (2011–2015). His work spans key areas including adversarial robustness, generalization bounds for prompt-based learning, and causal effect estimation in public health. Notable contributions include HyperCLIP (2024), AcceleratedLiNGAM (2024), and foundational work on subset scanning for anomaly detection in health data (2020–2022). Victor has been recognized with an Outstanding Paper Award (ICLR 2024 workshop) and a Distinguished Paper Award Nomination (AMIA 2022). His research bridges theoretical machine learning advancements with practical applications in global health systems and AI safety.

William SandersView profile

Professor

• Cybersecurity
• Formal Modeling
• Network Security
• +2 more

Dr. William Sanders is a Professor in the Computer Science Department at Carnegie Mellon University, with affiliated appointments in the Office of the President. His research develops formal methods for cybersecurity, including tools like CyberSAGE for security argument evaluation and techniques for assessing cyber-physical infrastructure vulnerabilities. Research Focus Key areas include: Security metrics and risk assessment frameworks Intrusion detection for software-defined networks Cyber-physical system protection (power grids, IoT) Formal verification of network protocols His work integrates game theory, stochastic modeling, and machine learning for adaptive security. Theoretical Contributions Developed ADVISE meta model formalism for security quantification and ontological frameworks for threat modeling in critical infrastructure.

Liu LeqiView profile

Assistant Professor

• Large Language Models
• Human-Centered Machine Learning
• AI Ethics and Societal Impact
• +3 more

Liu Leqi is an Assistant Professor in use-inspired AI at the University of Texas at Austin (UT Austin), specifically in the Department of Information, Risk, and Operations Management. He is a core member of the Machine Learning Laboratory and serves on the Graduate Studies Committee for both the Computer Science Department and the Oden Institute at UT Austin. His research focuses on controllable machine intelligence, human-centered ML frameworks, and evaluating the societal impacts of AI systems. Education: Ph.D. in Machine Learning, Carnegie Mellon University (2023), advised by Zachary Lipton Postdoctoral Researcher, Princeton Language and Intelligence (2023-2024) Bachelor’s degrees in Computer Science (Bryn Mawr College) and Mathematics (Haverford College), with a semester at AIT-Budapest (Spring 2016) Research Interests: Liu’s work spans three core areas: (1) foundational studies of generative AI systems, (2) designing human-centered ML models for healthcare, education, and recommenders, and (3) auditing the societal implications of large-scale AI. He emphasizes ethical and human-centric approaches to AI development. Awards: Open Philanthropy AI Fellow (2020-2023) Advising & Lab: Liu seeks motivated students to join his lab, focusing on large language model generalization. He advises through the lab website, fostering collaborative research environments.

E. Jin LeeView profile

Assistant Professor

• Data Analytics
• Machine Learning
• Disclosure
• +12 more

Dr. E. Jin Lee is an Assistant Professor of Accounting at Bryant University's College of Business. Her teaching focuses on Financial Accounting, Managerial Accounting, Data Analytics (with Machine Learning), Artificial Intelligence in Accounting, Auditing, and Accounting Information Systems. She earned her Ph.D. in Accounting from Florida International University, where she received the external AGA Fellowship, and an MS in Accountancy from George Washington University, where she was awarded the Hyundai Scholarship. Education Ph.D., Florida International University MS, George Washington University Research Interests Data Analytics, Machine Learning Methods Disclosure, Individual Investors Empirical Capital Markets, Going Concern Opinion Audit Partner, Audit Lag, Financial Distress Financial Reporting, Mergers and Acquisitions Macroeconomic Effects, COVID-19 Impacts, Gender, Social Media Scientific Awards AAA International Accounting Section (IAS) Doctoral Consortium Fellowship (2021, 2020) Top 10% of Authors on SSRN by total new downloads (2020) Association of Government Accountants (AGA) Scholarship Award (2020) AAA Financial Accounting Reporting Section (FARS) Doctoral Consortium Fellowship (2019) AAA Journal of International Accounting Research (JIAR) Doctoral Consortium Fellowship (2019) Her research has been cited in The Wall Street Journal and Compliance Week , with one article published in the Journal of Behavioral Finance (2023). She has served as an editor and co-chair for the Strategic and Emerging Technologies (SET) Workshop at the American Accounting Association (AAA) annual meeting, program organizing co-chair for the Accounting Information Systems (AIS) Summer Doctoral Consortium, and judge for the Data Analytics Case Competition. She actively participates in academic service through reviewing and discussing papers in journals like the Managerial Auditing Journal and Journal of Emerging Technologies in Accounting .

• Operations Management
• Industry 4.0
• Strategic Management
• +7 more

Andrea Chiarini is an Associate Professor at the University of Verona's Department of Management. He holds a PhD in TQM and Business Excellence from Sheffield Hallam University, UK, and has extensive experience in Operations Management, Industry 4.0, and Lean Six Sigma. He previously served as a professor at the University of Modena and Reggio and the University of Ferrara, and currently teaches at Bocconi University and other institutions. His research focuses on strategic operations, sustainability, and the integration of Industry 4.0 technologies. He is the CEO of Qualyco Srl, a spin-off specializing in AI and Industry 4.0 solutions. He serves on editorial boards for journals like Business Strategy and the Environment and has published over 50 articles on topics including supply chain resilience, Lean Six Sigma frameworks, and green HR practices. His work emphasizes operational excellence, digital transformation, and sustainable management practices in manufacturing and healthcare sectors. Research interests span CSR, logistics optimization, and innovation. His recent articles explore frameworks for Lean Six Sigma 4.0 and the impact of automation on employment. He advises on strategic management, performance measurement systems, and risk-based thinking in quality standards. Grants and collaborations include projects with ABB, Ferrari, and Tetrapak. He leads research groups on ICT adoption in healthcare and wine industries. His teaching modules cover business organization, innovation management, and industry 4.0 applications.

• Cloud Computing Security
• IoT Services
• Network Security
• +5 more

Shao Ying Zhu is a Lecturer in Computing at the Department of Electronics, Computing and Mathematics. Their research focuses on network security, cloud computing, IoT systems, and medical image analysis. Key contributions include frameworks for secure IoT service orchestration in multi-cloud environments and comparative studies of IPv6 routing protocols. Publications span areas like SDN security solutions, big data analytics algorithms, and cloud assurance methodologies. Notable work includes a textbook on cloud security assurance and analysis of HEp-2 medical images using machine learning techniques. Research outputs demonstrate expertise in both theoretical frameworks and applied solutions for modern computing challenges, with a focus on security and scalability across distributed systems.