Find Academic Supervisors

Ulrike FeltView profile

Professor

• Science and Technology Studies
• Public engagement in science
• Research cultures
• +9 more

Ulrike Felt is a Full Professor of Science and Technology Studies and Chair of the Department of Science and Technology Studies at the University of Vienna, where she has held academic positions since 1989. She served as Dean of the Faculty of Social Sciences (2014-2018) and Head of the Department of Science and Technology Studies during multiple periods (2004-2014, 2018-present). She also led the Interdisciplinary Research Platform 'Responsible Research and Innovation in Academic Practice' (2015-2022). With a PhD in physics and habilitation in social sciences, Felt's research spans diverse domains including life sciences, biomedicine, nanotechnologies, nuclear energy, and environmental research. Her work focuses on governance and public participation in technoscience, changing research cultures, temporal aspects of scientific developments, and responsible research innovation frameworks. She frequently conducts interdisciplinary collaborations with researchers from the sciences and comparative analyses across national contexts. Felt's recent publications demonstrate her continued engagement with cutting-edge topics including smart cities, digital health infrastructure, biobanking, border technologies, and temporal dimensions of academic work. Her work consistently examines how technological developments intersect with societal values, governance structures, and temporal frameworks. 4S Infrastructure Award (2017) Ziman Award of EASST (2014) ARS DOCENDI Austrian State Prize for Innovative Excellent Teaching (2015) UNIVIE Teaching Award (2014) Member of the SSH Panel of the ERC Felt served as editor-in-chief of Science, Technology & Human Values (2002-2007) and led the publication of the Handbook of Science and Technology Studies with MIT Press (2017). As President of the European Association for the Study of Science and Technology (2017-2020), she has significantly shaped the international STS community. Her work on card-based engagement methods (IMAGINE, RESPONSE_ABILITY) demonstrates her commitment to translating STS insights into practical tools for researchers.

Valerie Maier-SperedelozziView profile

Associate Professor

• Mechanical Engineering
• Industrial Engineering
• Systems Engineering
• +5 more

Valerie Maier-Speredelozzi is an Associate Professor in the Department of Mechanical, Industrial and Systems Engineering at the University of Rhode Island. She holds a Ph.D. in Mechanical Engineering from the University of Michigan (2003), with prior degrees in Industrial and Operations Engineering (M.S.E., 2001) and Mechanical Engineering (B.M.E., 1998). Her research bridges lean manufacturing, healthcare systems, and transportation engineering. Ph.D., Mechanical Engineering, University of Michigan, 2003 M.S.E., Industrial and Operations Engineering, University of Michigan, 2001 M.S.E., Mechanical Engineering, University of Michigan, 2001 B.M.E., Mechanical Engineering, Georgia Institute of Technology, 1998 Her work focuses on: Lean Manufacturing and Quality Assurance Human Factors in Industrial Systems Sustainable Supply Chain and Facility Location Transportation Safety and Dynamic Messaging Recent publications highlight trends in: Naval Engineering Education (2024) Healthcare Continuous Improvement (2016) Remanufacturing in SMEs (2016) Dynamic Message Sign Efficacy (2008–2011) Grants from the Office of Naval Research (2020–2021) support collaborations with UConn on safety and ergonomics in naval workforce development. She mentors graduate students and contributes to systems engineering pedagogy through workshops and project-based curricula.

• Transportation modeling
• Applied operations research

Jee Eun (Jamie) Kang is an Associate Professor in the Department of Industrial and Systems Engineering at the University at Buffalo's School of Engineering and Applied Sciences. Research focuses on transportation modeling and applied operations research, with applications in urban mobility, shared autonomous vehicles, and sustainable transportation systems. Education includes a PhD from UC Irvine. Research emphasizes data-driven approaches to travel behavior, electric vehicle adoption, and humanitarian logistics. Publications consistently address mobility innovation, including pricing strategies for emerging services, predictive analytics for transit, and optimization of shared transportation systems.

• Artificial Intelligence
• Machine Learning
• Medical Technology
• +7 more

Anis Yazidi is a Professor at Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design and the Department of Information Technology. His research focuses on Artificial Intelligence, Machine Learning, Medical Technology, and IoT Security, with a particular emphasis on Applications of AI in Healthcare, EEG Signal Processing, and Digital Transformation. Active research projects include AI Mind (dementia diagnostics), Glycopathology in dry eyes, and Pain and mental distress analysis Completed projects: Digital hate speech analysis, AI in reproductive technology, Nano-antibiotics development His recent publications (2023-2025) demonstrate expertise in: Tsetlin Automaton algorithms for concept learning EEG classification using visibility graphs and vision transformers AI ethics frameworks for medical practice Deepfake detection methodologies Collaborative work spans institutions in Norway, Czech Republic, and international AI research communities.

• Cybersecurity
• Machine Learning for Security
• IoT Security
• +5 more

Dr Raja Akrom is a Senior Lecturer in the Department of Computer Science , School of Natural and Computing Sciences , University of Aberdeen since July 2020. Previously, he held research positions at Royal Holloway, University of London (Post Doctoral Research Assistant), University of Waikato (Research Fellow), and Edinburgh Napier University (Senior Research Fellow). PhD in Information Security from Royal Holloway, University of London MSc in Information Security and Computer Science from Royal Holloway and University of Agriculture, Faisalabad BSc in Mathematics and Physics from University of the Punjab His research focuses on user-centric applied security and privacy architectures , data ownership in heterogeneous computing , security for machine learning , and security in emerging technologies such as blockchain, UAVs/drones, and autonomous vehicles. Key technical interests include smart card security, cryptographic protocols, IoT security, and Trusted Execution Environments. The article list reveals expertise in: edge computing security (DECML 2025), medical AI applications (2024), embedded device ownership (CO-TSM 2024), NFC transaction security (2024), and malware detection with ML (2024). Earlier work explored UAV security , blockchain governance , and smart card protocols . Currently teaching courses in Operating Systems , Secure Software Design , and Enterprise Security Architecture . Supervises postgraduate MSc Cybersecurity program.

• Public Transport
• Logistics and Supply Chain Management
• Transport Infrastructure
• +5 more

Dr. Geoffrey Clifton is a Senior Lecturer in Transport and Logistics Management at the Institute of Transport and Logistics Studies (ITLS) within the University of Sydney Business School. He holds a Bachelor of Economics with first class Honours in Economic Statistics from the University of Queensland and a PhD from the University of Sydney. Joining the University of Sydney in 2004 after teaching at the University of Queensland since 1998, Clifton brings extensive academic and practical experience, having previously worked for three years at the Reserve Bank of Australia. As Program Director for the Master of Logistics and Supply Chain Management, he oversees academic development and quality assurance for the Master's program as well as the Graduate Diploma and Certificate in Logistics and Supply Chain Management. His teaching portfolio includes foundational courses in supply chain management, production and operations management, quantitative logistics, and transport analysis. Clifton's research primarily focuses on public transport challenges, particularly growing patronage in suburban areas and providing transport for people with special needs due to age or disability. His work explores how reforms to policies, planning, pricing and provision of public transport services can deliver value for money solutions that support transport accessibility for all. His research methodologies include choice modeling, surveys, and smart card data analysis, with recent work examining railway safety, flexible transport systems, and the impact of emerging technologies on transport enterprises. As a consultant, Clifton has worked with aviation, maritime, logistics, rail, taxi and bus industries as well as governments both within Australia and internationally. His expertise is frequently sought by media outlets including ABC, Sydney Morning Herald, The Guardian, and Channel 7, where he comments on current transport issues ranging from Sydney's rail network challenges to light rail systems and public transport policy. Clifton coordinates multiple research projects, supervises postgraduate students, and has published extensively in leading transportation journals. His recent work demonstrates a strong focus on railway safety analysis, transport accessibility, and the integration of different transport modes within urban environments.

• Information Security
• Cybersecurity
• Smart Card Security
• +15 more

Konstantinos Markantonakis is a Professor of Information Security in the Department of Information Security at Royal Holloway, University of London, where he also serves as Director of the Smart Card and IoT Security Centre and the Transformative Digital Technologies, Security and Society Catalyst. He is a leading figure in embedded systems and IoT security, with extensive research and consultancy experience. BSc (Hons) in Computer Science, Lancaster University, 1995 MSc in Information Security, Royal Holloway, 1996 PhD in Smart Card Security, Royal Holloway, 2000 MBA in International Management, Royal Holloway, 2005 His research focuses on securing embedded and cyber-physical systems, including smart cards, mobile devices, drones, automotive systems, and IoT. He investigates trusted execution environments, side-channel analysis, secure protocols, and hardware-software binding. His work bridges theoretical security and practical implementation, often uncovering zero-day vulnerabilities in consumer devices. The recent publications highlight a strong trend in trusted computing, remote attestation, secure embedded systems, and privacy-preserving technologies. His research integrates blockchain for secure energy trading, develops frameworks for edge machine learning, and advances forensic techniques for damaged storage media. He also explores covert channels in mobile and cloud environments, demonstrating a deep understanding of both offensive and defensive security. Best Paper Award Markantonakis has led major research projects such as EXFILES (forensic extraction from encrypted smartphones), Future TPM (quantum-resistant trusted modules), and the Academic Centre of Excellence in Cyber Security Research. He has supervised numerous PhD students and delivered keynotes at international conferences. His consultancy work has impacted financial institutions, transport operators, and mobile platform security. He leads the Smart Card and IoT Security Centre, a research hub focusing on practical security for connected devices. The centre conducts cutting-edge research in side-channel attacks, secure application execution, and forensic analysis, contributing significantly to both academic and industrial advancements in cybersecurity.

• Transportation Modeling
• Applied Operations Research
• Sustainable Transportation
• +3 more

Jee Eun (Jamie) Kang is an Associate Professor in the Department of Industrial and Systems Engineering at the University at Buffalo, located within the School of Engineering and Applied Sciences. Her research focuses on transportation modeling, applied operations research, and sustainable mobility systems. She has contributed extensively to studies on autonomous vehicles, emergency evacuation planning, and electric vehicle infrastructure. Her work bridges theoretical optimization frameworks with real-world applications, addressing challenges in multi-modal travel environments, disaster logistics, and shared mobility systems. Dr. Kang's research often involves data-driven methodologies, leveraging automated fare collection systems and smart card transactions to infer user behavior and optimize transportation networks. Her publications span topics such as strategic parking location models for autonomous vehicles, pricing mechanisms in bike-sharing systems, and scenario-based analyses for battery electric vehicle feasibility. She actively advises students on projects related to urban mobility, evacuation planning, and transportation sustainability. Scientific Awards: None explicitly mentioned in the provided texts. Dr. Kang's advising and collaborative work include projects on household activity patterns, hydrogen refueling station optimization, and evacuation warning systems. Her research has been applied to real-world scenarios like the Nepal earthquake relief efforts and California's hydrogen infrastructure planning.

Renaud PacaletView profile

Researcher

• Hardware Security
• Side-Channel Attacks
• Embedded Systems
• +7 more

Renaud Pacalet is a Researcher at Institut Mines-Télécom – Télécom Paris , affiliated with the Communications and Electronics (Comelec) Department and the System on Chip (LabSoc) research team under the Information Processing and Communication Laboratory (LTCI). His work spans hardware security, embedded systems, and software-defined radio (SDR) architectures. Current Research: Hardware security, side-channel attacks (power, timing, fault injection), RISC-V security analysis using gem5, FPGA scheduling for cloud data centers, and model-driven design methodologies. Past Research: Hardware acceleration for ray tracing, SDR front-end processing, SoC security, and memory bus protection (SecBus project). Teaching: Courses on Digital Systems, Computer Architecture, and Hardware Security at EURECOM, including lab sessions on side-channel attacks and fault analysis. Email: renaud.pacalet@telecom-paris.fr Contact: Télécom ParisTech, Campus SophiaTech, 450 route des Chappes 06410 Biot, France

Filipe RodriguesView profile

Associate Professor

• Machine Learning
• Intelligent Transportation Systems
• Transportation Science
• +7 more

Filipe Rodrigues is an Associate Professor in the Department of Technology, Management and Economics at the Technical University of Denmark (DTU), where he conducts research in intelligent transportation systems and transportation science. His work integrates machine learning, artificial intelligence, and behavioral modeling to improve urban mobility and public transport systems. His research interests lie at the intersection of machine learning , transportation science , and behavioral modeling . He specializes in discrete choice modeling , reinforcement learning , graph neural networks , and smart card data analytics . His work contributes to sustainable urban mobility, leveraging big data and AI for proactive traffic control and public transport optimization. The recent publications highlight a strong trend toward integrating AI and behavioral science in transportation. Key themes include ride-sourcing driver behavior , public transport trip validation , autonomous fleet control , and causal machine learning . These works predominantly employ deep learning , Bayesian modeling , and offline reinforcement learning techniques, often applied to real-world datasets from Denmark and beyond. Scientific Contributions: Active contributor to journals like Transportation Research Part C and Journal of Choice Modelling . Supervises multiple PhD projects on AI in transportation and causal modeling. Regular presenter at major transportation and AI conferences. Advising and Grants: Filipe Rodrigues is the main or co-supervisor of several PhD students including O. B. Lassen, F. M. F. Santos, A. Nguyen, and X. Wu. He leads and participates in funded research projects such as 'Proactive traffic control through AI and Big Data' and 'Causal Graph Neural Networks for machine learning meta-modelling', indicating sustained grant support. His collaborative network spans institutions in Europe and beyond. Labs and Teams: He is part of the Intelligent Transportation Systems research group at DTU, collaborating closely with researchers like F. C. Pereira and C. M. L. Azevedo. The team focuses on data-driven mobility solutions, combining simulation, machine learning, and behavioral insights.

Ross HorneView profile

Senior Lecturer

• Security protocols
• Privacy-preserving technologies
• Concurrency theory
• +7 more

Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.

• Tourism Economics
• Education Economics
• Sustainable Mobility
• +3 more

Daniel Miravet is an Adjunct Professor at the Department of Economics , Universitat Rovira i Virgili , and a Mobility Technician at the Camp de Tarragona Territorial Authority for Mobility. His research focuses on Tourism Economics , Education Economics , and Sustainable Mobility . Research Interests: Tourist mobility patterns Public transport data analysis Pandemic impact on urban mobility Human capital in labor economics Publications highlight trends in: Smart card data applications (2021-2023) COVID-19 transport behavior (2020-2022) High-speed rail tourism dynamics (2019) Seasonal tourism mobility (2016) Key Collaborations: Aaron Gutiérrez, Xavier Delclòs-Alió, Josep Tomàs-Porres, Gemma Vich, Sergi Domènech.

• Human-Computer Interaction
• Technology and Gender Equality
• AI Ethics
• +4 more

Elaine Huang is an Associate Professor of Human-Computer Interaction (HCI) and Head of the People and Computing Lab at the University of Zurich's Department of Informatics. She holds a PhD in Computer Science from Georgia Institute of Technology (2006). Her career includes prior roles as Assistant Professor at the University of Calgary and Senior Staff Researcher at Motorola Labs. Her research focuses on the interplay between technology and human behavior, particularly in areas of gender equality in tech, AI ethics, sustainable HCI design, and accessible technologies. She critiques systemic biases in AI training data and advocates for inclusive design processes integrating Hofstede's cultural dimensions. Her work also explores trust dynamics in sharing economies and predictive health technologies. Huang emphasizes empirical studies over intuition, stressing the need for data-driven insights into disruptive technologies like ChatGPT. She leads initiatives to improve STEM PDF accessibility and designs tools for chronic condition management through incident cards. Her lab develops frameworks addressing obsolescence in smart homes and sustainability in digital interfaces. Awards and recognitions focus on her contributions to HCI ethics and gender studies. She advises students to proactively shape their academic trajectories and leverage institutional resources strategically.

Paula BrancoView profile

Assistant Professor

• Machine Learning
• Data Mining
• Data Science
• +8 more

Paula Branco is an Assistant Professor at the School of Electrical Engineering and Computer Science, University of Ottawa (since 2020). Previously, she was a PostDoctoral Fellow at Dalhousie University's Faculty of Computer Science (2019). She holds a PhD in Computer Science from the University of Porto, alongside a MSc in Data Mining and a Mathematics degree. She is an external researcher at INESC TEC's LIAAD laboratory. Her research focuses on Machine Learning, particularly utility-based learning and imbalanced domains, with applications in cybersecurity, healthcare, and environmental monitoring. Key areas include anomaly detection, fraud detection, rare event prediction, and spatio-temporal data analysis. Recent work emphasizes resampling techniques for imbalanced regression (e.g., SMOGN, ImbalancedLearningRegression Python package), evaluation metrics for imbalanced domains, and cybersecurity applications like intrusion detection and malware analysis. She has supervised seven graduate students and contributed to open-source projects like UBL (R package) and ImbalanceMetrics. Her teaching includes courses on databases and AI for cybersecurity. She actively publishes in top venues and collaborates on tools like SMOGN-LIDTA17 and NeighborhoodBiasResamplingRegression.

Thivya KANDAPPUView profile

Assistant Professor

• Human-Machine Collaborative Systems
• Pervasive Sensing & Systems
• Human-Computer Interaction
• +6 more

Thivya KANDAPPU is an Assistant Professor at the School of Computing and Information Systems, Singapore Management University (SMU). Her research focuses on mobile and wearable computing systems for human cognition monitoring, memory modeling, and technology-enhanced learning. Education: PhD in Computer Science, University of New South Wales (2014) Research Interests span: Human-Centric Wearable Systems Cognitive State Analysis Event-Based Vision & Sensing Privacy in Pervasive Systems Health & Wellbeing Applications Smart City Mobility Analytics Selected Publications demonstrate expertise in eye tracking, cognitive monitoring, and privacy-preserving wearables, with recent work appearing in NeurIPS and ACM IMWUT. Research Grants include projects funded by MOE and A*STAR on cognitive dynamics, privacy-aware systems, and multimodal travel analytics. Professional Service involves organizing AutoMLPerSys 2025, and serving on TPCs for ACM MobiSys 25, IEEE PerCom 25, and ICDCN 25.