Find Academic Supervisors

• Policing
• Private Security
• Security Governance
• +4 more

Dr. Adam Aitken is a Lecturer at the School of Health and Society, University of Salford, Manchester, UK. His career spans over a decade in criminology and security studies, with prior roles as a Criminology Lecturer at De Montfort University (2017-2021) and Assistant Lecturer at the University of Glasgow (2013-2017). Education: Postgraduate Certificate in Academic Practice (2023-2024), University of Salford PhD in Criminology (2013-2017), University of Glasgow MSc in Applied Social Research in Criminology (2011-2012), University of Stirling BSc (Hons) in Criminological Studies (2004-2008), Abertay University Research Interests: Adam's work focuses on security governance , police legitimacy , private security dynamics , and community resilience , particularly in contexts like sporting mega-events and environmental disasters. His current BA/Leverhulme-funded project examines placemaking and rural resilience to UK flooding. Publication Trends: His recent articles (2024-2025) address digital policing, community resilience, and semiotic approaches to security signals. Earlier works analyze mega-event security, democratic governance, and environmental harms. Scientific Awards: Shortlisted 2nd Place (2015) for poster on mega-event policing at SIPR Postgraduate Student Symposium PhD Supervision: Adam has supervised PhD completions (Michael Mathura, 2020) and is primary supervisor for Brian Roberts' ongoing work on AI in UK policing. He contributes to the Centre for Research on Inclusive Society and aligns with UN SDGs for health, urban sustainability, and climate action.

M. Hadi AminiView profile

Assistant Professor

• Distributed Machine Learning
• Federated Learning
• Interdependent Networks
• +7 more

M. Hadi Amini is an Assistant Professor at Florida International University's Knight Foundation School of Computing and Information Sciences. He founded and directs the Sustainability, Optimization, and Learning for InterDependent networks (SOLID) laboratory, focusing on cyber-physical-social systems and distributed AI applications. Ph.D., Electrical and Computer Engineering (2019), Carnegie Mellon University M.Sc., Electrical and Computer Engineering (2015), Carnegie Mellon University M.Sc. (2013), Tarbiat Modares University B.Sc. (2011), Sharif University of Technology His research spans federated learning, interdependent network optimization, and AI applications in smart cities , energy systems , and healthcare . Recent work emphasizes privacy-preserving techniques, quantum encryption, and blockchain integration for secure distributed learning. The 15 most recent publications highlight trends in large language models , edge computing , medical imaging security , and infrastructure resilience , with interdisciplinary emphasis across computer science, systems engineering, and urban planning. Best Paper Award, IEEE Conference on Computational Science & Computational Intelligence (2019) Best Journal Paper Award, Springer Nature Operations Research Forum (2021) Excellence in Teaching Award, FIU (2020) Multiple Best Reviewer Awards, IEEE Transactions NSF Travel Awards (2019) As Associate Editor for Frontiers in Communications and Networks and book series editor for Sustainable Interdependent Networks , he actively shapes research discourse. His lab has secured $3.6M in federal/state funding for AI-driven infrastructure projects.

Daniel HarrisonView profile

Assistant Professor

• Human-Computer Interaction (HCI)
• Digital Health
• Inclusive Technology Design
• +3 more

Dr. Daniel Harrison is an Assistant Professor in the School of Design, Arts, and Creative Industries at Northumbria University, where he serves as EDI and Athena SWAN Co-Lead and leads the HCI+Design Research Group. His academic journey includes a PhD from UCL's Interaction Centre (UCLIC) and research at Georgia Institute of Technology and Microsoft Research Cambridge. His work focuses on Human-Computer Interaction (HCI), digital health, and inclusive technology design, particularly in sports and wellbeing. Education: PhD in Human-Computer Interaction, UCL Interaction Centre (2020) MSc (2012), BSc (Hons) (2010) Research Interests: Intersection of technology, inclusivity, and sports (SportsHCI) Participatory methods (co-design, ethnography) Developing inclusive technologies for underrepresented groups Recent Projects: Co-authored Grand Challenges in SportsHCI Initiatives for inclusive sports technology Design of wellbeing-focused digital tools Advising: Mentors three PhD students researching topics such as neurodivergent workers, financial technology for international students, and gamified sports participation. Labs/Teams: HCI+Design Research Group at Northumbria University.

• Computational Social Science
• Natural Language Processing
• Human-Computer Interaction
• +3 more

Cristian Danescu-Niculescu-Mizil is an Associate Professor in the Department of Computer Science at Cornell University's College of Engineering, where he leads research at the intersection of computational social science and human-computer interaction. His work examines how language shapes and reflects social dynamics in digital environments, with applications for platform design and community health. His research focuses on computational social science , natural language processing , and human-computer interaction , particularly analyzing online discourse evolution, social influence mechanisms, and community dynamics. Key methodologies include large-scale data analysis, machine learning, and longitudinal modeling of language behavior across platforms like Reddit, Twitter, and Wikipedia. Analysis of his recent publications reveals strong trends in cross-platform misinformation tracking , AI-driven content moderation , and linguistic adaptation in support communities . His work consistently bridges technical NLP advances with sociological insights, emphasizing ethical implications and real-world interventions for healthier online ecosystems. Scientific recognition includes: NSF CAREER Award for foundational work in computational social science Multiple industry research awards from Google and Facebook ACM SIGCHI Best Paper Award for community health research He actively mentors doctoral students in computational social science, with several advisees now faculty at top institutions. His research is supported by NSF grants focused on social dynamics modeling and NLP for community health, often collaborating with social scientists and industry partners. Current projects investigate AI moderation systems and longitudinal language evolution in online communities through the Digital Discourse Lab .

Lenka BenovaView profile

Researcher

• Public Health
• Maternal Health
• Health-seeking Behavior
• +4 more

Lenka Benova is a Researcher at the Institute of Tropical Medicine, Antwerp , where she serves as Unit Head in Reproductive and Maternal Health. She is a quantitative population health scientist with interdisciplinary training in management, economics, Middle East studies, demography, and epidemiology . Her career includes project coordination with Médecins Sans Frontières in Nigeria, West Bank, and South Sudan, as well as leading health pillar design in Egypt's conditional cash transfer program (2008-2010). Education: MA in Middle East studies (American University in Cairo) MSc in Demography and Health (London School of Hygiene & Tropical Medicine) PhD in Population Health (London School of Hygiene & Tropical Medicine) Her research focuses on health-seeking behavior in low- and middle-income countries, particularly reproductive/maternal health , with methodological interests in innovative data capture, self-reported indicator validity, and geospatial modeling . Her recent work examines maternal healthcare provision discontinuities in urban Sub-Saharan Africa through system dynamics and geospatial approaches. She teaches on Masters course modules and supervises PhD students , contributing to projects like: modeling maternal care accessibility in Guinea, analyzing fertility transitions in DR Congo, and evaluating hospital data utility for community epidemiology. Her research appears in journals such as Bioinformatics , BMC Pregnancy and Childbirth , and Scientific Reports , focusing on public health, maternal care, and health equity.

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Vahid Behzadan is an Assistant Professor in Data Science and Computer Science at the University of New Haven's Tagliatela College of Engineering. He leads the SAIL Lab, focusing on AI safety and security, particularly in autonomous systems like driverless cars and smart cities. His work addresses adversarial attacks on machine learning and reinforcement learning, with applications in cybersecurity and healthcare. Behzadan has held prior positions at Kansas State University, University of Nevada Reno, and University of Birmingham, UK. He holds a Ph.D. in Computer Science and an M.S. from the University of Nevada Reno, and a B.Eng. from the University of Birmingham. His research spans AI ethics, cybersecurity, and complex systems. Behzadan advises the UNH hacking team and actively participates in policy initiatives, including Connecticut's AI Working Group and the Connecticut AI Alliance. He has contributed to over 30 peer-reviewed articles and frequently engages in media discussions on topics like AI safety, facial recognition, and cybersecurity threats. Key research areas include adversarial machine learning, AI forensics, and ethical AI design. His work bridges theoretical advancements with real-world applications in transportation, healthcare, and national security. Behzadan collaborates with organizations such as the Transportation Research Laboratory (TRL) and Open Web Application Security Project (OWASP).

Alexandra KirschView profile

Assistant Professor

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +3 more

Alexandra Kirsch is an Assistant Professor in the Media Informatics Department at the University of Tübingen's Faculty of Informatics. She held the Carl von Linde Junior Fellowship at the Technical University of Munich (TUM) Institute for Advanced Study (TUM-IAS) from 2010. Previously, she was a senior research scientist at TUM's Intelligent Autonomous Systems Group and led the independent Junior Research Group “Planning for Adaptive Robot Assistance” within the Excellence Cluster CoTeSys (Cognition for Technical Systems). Education: Diploma in Computer Science from TUM, 2003 Doctoral degree from TUM, completed between 2003-2007 Research Interests: Kirsch focuses on developing control mechanisms for autonomous robots using artificial intelligence, aiming to create systems that collaborate closely and transparently with humans. Her work emphasizes models of world dynamics, robot action effects, and human behavior. She created the Robot Learning Language (RoLL) to automate model acquisition and update processes during robot operations. Collaborations with psychologists and neuroscientists explore joint human-robot planning tasks and model development for seamless interaction. Scientific Awards: Member of the Bayerische Akademie der Wissenschaften Förderkolleg (2012) Award by Comet Computer GmbH for excellent graduation results (2003) Advising & Grants: Managed interdisciplinary research projects during her junior fellowship at TUM. Previously worked as a management consultant at Booz & Co., 2007-2008. Her grants include the Carl von Linde Fellowship and support for the Junior Research Group. Labs/Teams: Active in the Planning for Adaptive Robot Assistance group (CoTeSys) and collaborates with the Cognitive Technology focus group at TUM-IAS. Engages in cross-disciplinary teams involving neuroscience and psychology for human-robot interaction studies.

Oksana BuzhdyganView profile

Researcher

• Biodiversity Conservation
• Ecosystem Ecology
• Ecological Modeling
• +3 more

Dr. Oksana Buzhdygan is a Senior Researcher in Theoretical Ecology at the Department of Biology, Faculty of Biology, Chemistry, Pharmacy at Freie Universität Berlin. She holds a PhD in Ecology from Chernivtsi National University and has held postdoctoral positions at institutions including the University of Georgia (USA) and Freie Universität Berlin. Her research focuses on biodiversity-ecosystem functioning links, multitrophic interactions, and ecological network analysis. Education: BSc, MSc, and PhD in Ecology (2000–2008), Chernivtsi National University, Ukraine Postdoctoral Fellowships: University of Georgia (2010–2012), Freie Universität Berlin (2013–2021) Research Interests: Environmental change impacts on biodiversity and ecosystem functions Ecological network analysis of multitrophic systems Food web dynamics in grasslands and freshwater ecosystems Publications reflect her expertise in biodiversity effects on energy flow, human impact on ecosystems, and plant diversity drivers. Her work bridges theoretical ecology with applied conservation challenges, particularly in grasslands and agroecosystems. Labs/Teams: Member of the Tietjen Group (Theoretical Ecology at Freie Universität Berlin), collaborating widely in international projects on biodiversity and ecosystem services.

• Biometrics
• Computer Vision
• Machine Learning
• +4 more

Marina L. Gavrilova is a Professor at the University of Calgary, Canada. Her research focuses on biometric systems, computer vision, and machine learning with an emphasis on multimodal recognition and security applications. She has authored numerous publications in top journals and conferences, contributing to advancements in fields like emotion-aware de-identification, generative adversarial networks, and ethical AI frameworks in healthcare. Her work spans social behavioral biometrics, gait recognition, masked face recognition, and aesthetic-based person identification. Key contributions include frameworks for ethical AI in care systems, fusion algorithms for multi-biometric systems, and innovations in visual and audio signal processing. Collaborations with experts like Osvaldo Gervasi, Jon G. Rokne, and Padma Polash Paul highlight her interdisciplinary approach. Publications emphasize practical applications such as privacy-preserved biometrics, emotion detection from social media, and adaptive systems for template aging. Despite no explicit mention of grants or labs, her extensive co-author network and frequent citations indicate significant academic influence.

Alva L. CouchView profile

Associate Professor

• Network and System Management
• Geo-informatics
• Data Management
• +9 more

Alva L. Couch is an Associate Professor at Tufts University's School of Engineering, Department of Computer Science, with a career spanning over 30 years. His work bridges network/system administration, autonomic computing, and hydrologic data science, focusing on scalable solutions for data management and automated system administration. Education: Ph.D. in Mathematics (1988), B.S. in Architecture (1978), and B.A. in Bassoon/Contrabassoon Performance (1978). Research Interests His research centers on: Network and System Administration: Tools like SLINK, Maelstrom, and Babble for dependency analysis, cloud migration, and policy enforcement. Geo-informatics: MEDFORD metadata language and HydroShare platform for hydrologic data curation and discovery. Autonomic Computing: Promise theory, convergent operators, and closure models for self-managing systems. Recent Work Trends His 2024-2018 publications emphasize: Cloud-based hydrologic data management (AnVILMEDFORD, HydroShare) Metadata standards for interdisciplinary research Machine learning for system administration Agent-based resource sharing models Scientific Awards Liebner Teaching Award (1996) Seymour Simches Advising Award (2017) Best Paper Awards: LISA 1996, AIMS 2008, LISA 2001 LISA 2000 Best Student Paper (with Michael Gilfix) Contributions He developed key software like Peep (network auralization) and Slink (configuration management), supported by NSF grants and industry partnerships. His work with CUAHSI's Water Data Center shapes national hydrologic data infrastructure. He also advocates for science education and privacy in computing.

Anja FeldmannView profile

Professor

• Internet Measurement
• Network Performance Debugging
• Software-Defined Networking
• +7 more

Anja Feldmann is Director at the Max Planck Institute for Informatics in Saarbrücken and Professor of Internet Network Architectures at Technische Universität Berlin (since 2006). Previously she held a full professorship at Technische Universität München (2002–2006) and conducted research at AT&T Labs Research , Saarland University , and Carnegie Mellon University , where she earned her Ph.D. in 1995. Education Ph.D. in Computer Science, Carnegie Mellon University, 1995 M.Sc. in Computer Science, Carnegie Mellon University, 1991 Diplom in Computer Science, Universität Paderborn, 1990 Research Interests Anja Feldmann’s research centers on measurement-driven understanding of the Internet. She tackles challenges such as software-defined networking , cloud-network interactions , performance debugging , and traffic characterization . A growing focus is the privacy and security of networked systems, evidenced by recent studies on online tracking, DNS security, and disinformation ecosystems. Her group designs scalable measurement platforms that combine passive and active monitoring , programmable data planes , and machine-learning analytics to dissect phenomena ranging from terabit-scale traffic to covert tracking on illegal streaming sites. Recent Publication Themes The 2021-2025 publications reveal a methodological evolution toward large-scale, longitudinal measurement . Topics include: Impact of global events (COVID-19, CrowdStrike outage) on Internet traffic Cross-country tracking ecosystems and privacy leaks DNS root and routing plane stability and security ML-driven real-time monitoring at terabit speeds Disinformation campaigns on encrypted messaging platforms Scientific Awards Gottfried Wilhelm Leibniz Prize (2011) – Germany’s highest research honor Berliner Wissenschaftspreis (2011) Elected Member of the German National Academy of Sciences Leopoldina (2009) Advising & Grants While individual student names are not listed, Prof. Feldmann leads a vibrant team at MPI-INF’s Internet Architecture department. She has supervised numerous doctoral candidates and post-doctoral researchers whose work is reflected in the co-authored papers. Funding sources include the German Research Foundation (DFG) via the Leibniz Prize and EU Horizon projects, although explicit grant numbers are not provided in the source material. Labs & Teams She heads the Internet Architecture department at MPI-INF, located at the Saarland Informatics Campus . The department operates state-of-the-art measurement infrastructure—including programmable switches, honeynets, and global vantage points—to support empirical network science.

• Gait Analysis
• Functional Task Analysis
• Neurological Rehabilitation
• +7 more

Sylvie Nadeau is a Full Professor in the School of Rehabilitation at the University of Montreal's Faculty of Medicine. Her research focuses on locomotor activity assessment, rehabilitation interventions for neurological conditions, and biomechanical analysis of movement. She leads interdisciplinary projects addressing spinal cord injuries, stroke recovery, and mobility challenges in aging populations. Key affiliations include the INTER strategic research group and the REPAR provincial rehabilitation research network. She collaborates with institutions like the Institut de Réadaptation Gingras-Lindsay-de-Montréal (IRGLM) and has secured funding from agencies such as FRQNT, MITACS, and the Rick Hansen Institute. Her work integrates technologies like smart stationary bikes and real-time avatars to enhance rehabilitation outcomes. Research interests span gait analysis, dynamic balance, and sensorimotor rehabilitation. She has supervised over 30 graduate students, contributing to advancements in post-stroke mobility, incontinence management, and telerehabilitation. Recent projects include developing intelligent exercise systems and evaluating environmental impacts on mobility in museum settings. Directed the 2019 SOFPEL international congress Co-led the TRIVEL intelligent cycle prototype development Pioneered studies on bilateral upper limb coordination post-stroke Her teaching includes courses in physiotherapy and evidence-based practice, shaping future generations of rehabilitation professionals. She prioritizes translating research into clinical practice through innovative interventions and technology integration.

Heeseung Andrew LeeView profile

Assistant Professor

• Economics of IT
• AI and Human Collaboration
• Digital Marketing
• +2 more

Heeseung Andrew Lee is an Assistant Professor at the Naveen Jindal School of Management, University of Texas at Dallas, specializing in Information Systems. His research explores the economics of information technology and human-AI collaboration, with applications in digital marketing and content consumption. Affiliation: Assistant Professor, Information Systems Department (UTD) Education: PhD & MS from KAIST (2022), BS from KAIST (2017) Teaching: Business Analytics with R, Colloquium in Management Information Systems Research interests span multiple domains in digital transformation: Economics of IT: Quantifying technology ROI in modern organizations AI-Human Collaboration: Understanding human-AI interaction dynamics Digital Marketing: Analyzing consumer behavior in online environments Content Consumption: Studying digital media engagement patterns Recent publications focus on digital content partitioning strategies (2025), behavioral nudges in e-commerce (2024), pandemic mobile tracing effectiveness (2023), and book consumption patterns (2021). These works demonstrate expertise in combining empirical analysis with digital platform research.

David E. BreenView profile

Professor

• Biomedical Image Informatics
• Geometric Modeling
• Textile Modeling and Design
• +12 more

David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.

• Environmental Sustainability
• Children's Health
• Physical Activity Promotion
• +3 more

Dr. Clare Hume is a Senior Lecturer in the School of Public Health at the University of Adelaide, within the Faculty of Health and Medical Sciences. She serves as Program Director for the Honours program in the School and teaches courses in Infant, Child and Adolescent Health, and Communication for Health Sciences. Her research focuses on sustainable environments and children’s health, emphasizing physical activity promotion, reducing sedentary behaviors, and improving nutrition through innovative interventions in family, school, and community settings. She is an Editorial Board member for the American Journal of Health Promotion and Associate Editor for the Health Promotion Journal of Australia . Currently supervising two MPH students and an Honours student, her work bridges environmental sustainability and public health, particularly addressing waste reduction and healthy eating strategies. Key research themes include the impact of built environments on physical activity, interventions targeting screen-time reduction, and policy analysis for health and environmental co-benefits. Dr. Hume’s publications highlight school lunchbox innovations, community garden effects, and the Transform-Us! trial’s impact on children’s cardiometabolic health. Her contributions emphasize translational research to translate evidence into actionable strategies for healthier lifestyles and sustainable practices among children and families.