Find Academic Supervisors

• Bullying Prevention
• Family Violence
• Adverse Childhood Experiences
• +3 more

Dr. Sally A. Kuykendall is a Professor in the Department of Health Sciences at Saint Joseph's University, where she has served since 2004 and chaired the department from 2011 to 2015. Her academic journey spans nursing, chemistry, and public health, reflecting a unique interdisciplinary perspective. Her educational credentials include: PhD in Health Studies, Temple University (Dissertation: A phenomenological description of youth firearm carrying) MS in Health Education, Saint Joseph's University (Thesis: Dream interpretation and stress management) BSc (Hons) Chemistry and Biology, Plymouth Polytechnic (Research: Properties and actions of desensitizing toothpastes) Diploma in Nursing, Thomas Jefferson University Kuykendall pioneered bullying prevention research in the U.S. through a nine-year national study, later expanding into family violence, adverse childhood experiences, and trauma-informed care. Her 2020 book Skewed Studies critically examines scientific misconduct in health research, revealing systemic issues of data fabrication and bias. Current work focuses on creative problem-solving methodologies. Analysis of her 2007-2019 publications reveals three dominant research trajectories: (1) Rigorous evaluation of bullying prevention programs (particularly Olweus), (2) Interdisciplinary investigations of violence exposure across developmental stages, and (3) Critical analysis of research integrity in health sciences. Her work consistently bridges public health practice with psychological theory. Key recognitions include: Teaching Excellence Award (Saint Joseph's University, 2003) Crystal Community Impact Award (SmithKline Beecham, 1996) Ambassador Award (Abington Memorial Hospital, 1992) Meggy Memorial Prize in Chemistry (University of Plymouth, 1988) As principal investigator, Kuykendall secured over $3 million in grant funding including $680,000 from PA Commission on Crime and Delinquency for bullying prevention, $750,000 CDC-funded youth health initiatives, and multiple Barra Foundation grants for family violence intervention. Her work emphasizes community-academic partnerships with Saint Christopher's Hospital, Philadelphia Department of Public Health, and School District of Philadelphia. She maintains active collaborations through the Institute for Safe Families and International Bullying Prevention Association, developing trauma-informed curricula and translating research into school-based violence prevention protocols across urban educational settings.

• Sociology
• Childhood Studies
• Gerontology
• +7 more

Marit Haldar is a Professor of Sociology at Oslo Metropolitan University, Faculty of Social Sciences, Department of Social Sciences. She specializes in Service organization and innovation in social work and child welfare. Her research spans childhood studies, gerontology, gender studies, family sociology, social inequality, and welfare state studies. Professor Haldar's research interests focus on qualitative methodology, medical sociology, and care technology. She is particularly known for her work on the relationship between politics/ideology and the implementation of presence technology in welfare contexts. Her research examines how digital communication technologies are both perceived as causes of and solutions to loneliness problems. She discovered untapped data sources within qualitative methods and has developed new methodologies referenced in international methodological literature. Her recent publications (2023-2025) demonstrate a strong focus on loneliness, technology, and welfare systems. The research shows increasing interdisciplinary work connecting sociology, medical humanities, and technology studies. Key themes include telepresence robots in education and healthcare, loneliness as a policy issue, and the social implications of welfare technology implementation across different institutional settings. Scientific recognition includes: OsloMet's Research Prize (2019) Professor Haldar leads the research center CEDIC and the interdisciplinary research group Welfare Access Through Technology (WATT). She is actively involved in several research projects including the Evaluation of the Stay Safe at Home reform, Easy and safe contact with relatives (an innovation project with loneliness-reducing technology in elderly care in Oslo), and Virtual Presence: A cultural analysis of loneliness. Her work bridges theoretical sociological frameworks with practical welfare technology implementation. Her research groups include Big city children (research on childhood in big cities), Service organization and innovation in social work and child welfare, and Welfare Access Through Technology (WATT).

Tomoki NakamaruView profile

Assistant Professor

• Domain-Specific Languages
• Mining Software Repositories
• Notebook Programming
• +5 more

Tomoki Nakamaru is an Assistant Professor at the Department of Multidisciplinary Systems Science, Graduate School of Arts and Sciences, The University of Tokyo. He holds a Ph.D. in Information Science and Engineering from The University of Tokyo, advised by Prof. Shigeru Chiba. Education: PhD (2021), The University of Tokyo M.Sc. (2018), The University of Tokyo B.Eng. (2016), The University of Tokyo His research focuses on Domain-Specific Languages , Mining Software Repositories , and Notebook Programming . He develops tools like Multiverse Notebook and Silverchain to enhance code exploration and API usability. He has published extensively at top venues like OOPSLA and PLDI , covering topics from Fluent Interface Generation to Runtime Monitoring . His 15 most recent works span 2017–2025. Scientific Awards: Yamashita Memorial Research Award (2023) University of Tokyo Business Reform Special Award (2021) JSST Student Encouragement Awards (2019–2020) Distinguished Artifact Award at OOPSLA (2019) Dean's Award, UTokyo (2018) Nakamaru serves on program and artifact committees for conferences like ECOOP , OOPSLA , and ‹Programming› . He teaches courses including Practical Programming and Introduction to Information Systems .

Matteo CastiglioniView profile

Assistant Professor

• Artificial Intelligence
• Algorithmic Game Theory
• Machine Learning
• +5 more

Matteo Castiglioni is an assistant professor (RTD-A) at the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. He received his PhD in computer science from the same institution under the supervision of Prof. Nicola Gatti. His academic career spans multiple teaching roles across various programs at Politecnico di Milano. Castiglioni's research focuses on the intersection of artificial intelligence, algorithmic game theory, and multi-agent systems. He specializes in combining machine learning techniques with economic paradigms to build strategic agents capable of operating in complex multi-agent environments. His work addresses fundamental challenges in contract theory, mechanism design, and strategic decision-making under uncertainty. His publication record shows a clear trajectory toward increasingly sophisticated models that integrate learning with strategic behavior. Recent papers demonstrate expertise in constrained optimization, regret minimization, and handling both stochastic and adversarial environments. His work bridges theoretical computer science with practical applications in economics and market design. Castiglioni has taught across multiple academic levels including B.Sc., M.Sc., and Ph.D. programs. He has served as both professor and teaching assistant for courses in Game Theory, Online Learning Applications, and Computer Science and Engineering programs.

• Heat Pump Systems
• Refrigeration Cycles
• Refrigerant Selection
• +6 more

Christian Vering is a Researcher and Team Leader for Refrigeration Cycles at the Chair of Building and Room Climate Technology within RWTH Aachen University's Faculty of Mechanical Engineering. He specializes in evaluating the performance and environmental impacts of heat pump systems, from refrigerant selection to system controllers, utilizing advanced optimization methods coupled with dynamic simulation models and hardware-in-the-loop validation techniques. Dr. Vering earned his doctorate in April 2023 with a dissertation titled "Optimal Design of Heat Pump Systems for Existing Buildings." He studied Mechanical Engineering with a focus on renewable energy technology at RWTH Aachen from 2010 to 2016, including a six-month internship at Porsche AG investigating thermal management strategies for sports vehicles. During his studies, he worked for seven semesters at the Chair of Technical Thermodynamics. His research demonstrates a clear trajectory toward integrating artificial intelligence with traditional control systems, particularly using deep reinforcement learning to optimize heat pump performance while simultaneously reducing noise and increasing efficiency. Recent work emphasizes environmental impact assessment of refrigerants and the critical role of heat pumps in decarbonizing residential heating systems, with significant focus on natural refrigerants like propane. His publications reveal a methodological approach combining theoretical modeling, experimental validation, and practical implementation. Dr. Vering established and operationalized the Refrigerant Laboratory at RWTH Aachen, featuring a compressor test bench and an air-water heat pump using propane refrigerant. Since July 2023, he serves as Principal Investigator in the German Research Foundation's Priority Program 2403, investigating interactions between heat pumps and storage systems. His scientific contributions have been recognized with notable awards: Borchers Plakette, RWTH Aachen University (2024) Young Scientist Award of the German Climate and Refrigeration Technology Association (2022) As Principal Investigator in Priority Program 2403, Dr. Vering leads significant research initiatives investigating heat pump interactions with storage systems. His work involves extensive collaboration with multiple research groups and industry partners. While not explicitly listed as primary advisor, his leadership role in the Refrigeration Cycles team suggests substantial involvement in mentoring junior researchers and students. Dr. Vering is actively involved with the Urban Energy Lab 4.0 initiative, which takes an integrated approach to sustainable urban energy systems. His Refrigerant Laboratory serves as a key experimental facility for validating theoretical models and developing next-generation heat pump technologies, particularly focusing on flammable natural refrigerants and their safe implementation in building energy systems.

Le ChenView profile

Researcher

• Robotics
• Machine Learning
• Reinforcement Learning
• +5 more

Le Chen is a Doctoral Researcher at the Empirical Inference Department of the Max Planck Institute for Intelligent Systems and ETH Zurich , advised by Prof. Bernhard Schölkopf and Prof. Dieter Büchler. Previously, he obtained his M.S. in Electrical Engineering and Information Technology from ETH Zurich and gained research experience at Microsoft Mixed Reality & AI Lab, Tencent AI Lab, and Tencent Robotics X Lab. Research Interests: Le Chen focuses on the intersection of robotics and machine learning, with a specific emphasis on reinforcement learning for dexterous manipulation, visual-inertial calibration, and uncertainty-aware robotic perception. His work spans dynamic motion control, policy gradient subspaces, and novel algorithms for 3D/4D reconstruction. Key Contributions: He co-developed the RP1M dataset for bimanual piano manipulation and contributed to tendon-driven robot design ( Safe & Accurate ) and LEAP-VO for robust visual odometry. His research also includes Gaussian splatting dynamics for 4D content creation ( GaussianFlow ). Scientific Awards: Best Systems Paper Finalist at RSS 2024 for the RP1M dataset

Karen FeighView profile

Associate Professor

• Human Factors
• Cognitive Systems Engineering
• Human-Machine Interaction
• +3 more

Karen Feigh is an Associate Professor at the Daniel Guggenheim School of Aerospace Engineering within the Georgia Institute of Technology . Her research focuses on designing cognitive work support systems for individuals and teams in dynamic sociotechnical environments such as airline operations, air transportation systems, and unmanned aerial vehicle ground control stations. Developed an interface to assist astronauts in executing extravehicular activities safely and efficiently Investigated natural human-machine teaching interactions for robotics in domestic settings Explored autonomy and pilot training requirements for urban/regional air mobility systems Her work emphasizes intuitive machine learning integration and workload management in high-stakes environments.

Kyriakos G. VamvoudakisView profile

Professor

• Reinforcement Learning
• Control Theory
• Cyber-Physical Security
• +4 more

Kyriakos G. Vamvoudakis is the Dutton-Ducoffe Endowed Professor at the Daniel Guggenheim School of Aerospace Engineering and directs the Intelligent Cyber-Physical Laboratory. He holds a secondary appointment in the School of Electrical and Computer Engineering. His research integrates reinforcement learning , control theory , and game theory to develop secure and fault-tolerant autonomous systems, with applications in aviation, robotics, and critical infrastructure. His research focuses on: Safe autonomy for urban air mobility and cyber-physical systems Adversarial reinforcement learning to mitigate security threats Data-driven control for resilient multi-agent systems Bounded rationality in complex adaptive environments Recent publications emphasize adversarial robustness , safe RL , and cyber-physical security , with trends showing increased focus on real-time learning under uncertainty, deception in multi-agent games, and quantum control applications. He leads federally funded projects from NASA , NSF , ARO , and ONR , including: NASA ULI: Safety-Aware Learning for Aviation NSF CPS: Secure Assured Autonomy ARO: Non-Equilibrium Game-Theoretic Learning ONR Minerva: Cyber-Physical Situation Awareness At the Intelligent Cyber-Physical Laboratory , he oversees research on multi-agent coordination, secure autonomy, and reinforcement learning frameworks validated through real-world UAV and robotics platforms.

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

Prof. Dr. Mario Fritz is a Professor at Saarland University and faculty member at CISPA Helmholtz Center for Information Security. He serves as a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on Trustworthy Information Processing at the intersection of AI & Machine Learning with Security & Privacy. Mario Fritz leads numerous significant research initiatives including the European Large Open Multi-Modal Foundation Models for Robust Generalization (ELLIOT), European Lighthouse on Secure and Safe AI (ELSA), and multiple projects on privacy-preserving AI applications in healthcare. His work spans security and privacy aspects of large language models, foundation models, and medical AI applications. He has established himself as a leading researcher in trustworthy AI through his extensive publication record and leadership in major collaborative projects. His recent research (2025 publications) demonstrates a strong focus on the security and safety challenges of large language models, including model stealing attacks, causal reasoning capabilities, sampling methods, and privacy risks. His work bridges theoretical foundations with practical applications across multiple domains, particularly in healthcare and cybersecurity. Mario Fritz actively mentors PhD students and Post-Docs, seeking new researchers to join his group. He has been involved in numerous grants and collaborative projects, including those funded by BMBF and the Helmholtz Association, demonstrating his ability to secure substantial research funding and lead large interdisciplinary teams.

Ante Bilić PrcićView profile

Associate Professor

• Visual Impairment Rehabilitation
• Assistive Technology for Disability
• Psychosocial Aspects of Disability
• +3 more

Dr. Ante Bilić Prcić serves as Associate Professor and Dean at the Faculty of Education and Rehabilitation Sciences , University of Zagreb. He teaches courses in the Department of Visual Impairments , including Family and Rehabilitation , Electronic Aids in Rehabilitation , and Psychosocial Implications of Visual Impairment . His research focuses on rehabilitation methodologies, assistive technology applications, and social skills development in individuals with visual impairments. Core Research Areas : Visual Impairment Rehabilitation, Assistive Technology, Psychosocial Interventions Teaching Expertise : Braille literacy, ICT accessibility, independent mobility training Recent publications analyze Braille literacy program effectiveness , social skill disparities in visually impaired adolescents, and ICT applications for safe navigation. His work addresses pandemic-specific challenges in disability support and art therapy accessibility. Key Collaborations : Laboratory for Psycholinguistic Research, Centre for Lifelong Learning Students : Supervises clinical exercises and graduation theses in visual impairment rehabilitation

• Robotics
• Control Systems
• Reinforcement Learning
• +4 more

Zhen Kan is a Professor in the Mechanical and Aerospace Engineering Department at the University of Florida's College of Engineering, with previous affiliations at the University of Iowa and the Air Force Research Laboratory (AFRL). His extensive publication record spans over 15 years with significant output in recent years, indicating an active research career in robotics and control systems. Dr. Kan's research focuses on advanced robotics systems with expertise in temporal logic motion planning, reinforcement learning, and human-robot interaction. His work bridges theoretical control systems with practical robotics applications, particularly in multi-robot coordination, autonomous systems, and wearable robotics. The research demonstrates a strong emphasis on formal methods for ensuring safety and correctness in complex robotic systems. Analysis of recent publications reveals a consistent research trajectory centered around temporal logic specifications for robotic systems, with increasing integration of machine learning techniques. His work shows progression from theoretical control frameworks to practical implementations in quadruped robots, exoskeletons, and multi-robot systems operating in dynamic environments. Dr. Kan has established significant collaborations with researchers across multiple institutions, particularly with Warren E. Dixon (35 co-authored papers), Zhijun Li (23 papers), and Mingyu Cai (22 papers), indicating leadership in collaborative research projects. His publications appear in top-tier venues including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, and International Journal of Robotics Research. While specific grant information isn't visible in the provided text, the volume and quality of publications suggest substantial research funding. Dr. Kan's work has practical applications in autonomous systems, human-robot collaboration, and assistive technologies, with potential impact in defense, healthcare, and industrial automation sectors.

Jonathan M. AitkenView profile

Senior Lecturer

• Autonomous robotics
• Computer vision
• Spatial awareness in robotic systems
• +4 more

Dr. Jonathan M. Aitken is a Senior Lecturer in Robotics at the University of Sheffield's School of Electrical and Electronic Engineering. Previously a Research Fellow at the Autonomous Control Laboratory (ACSE), his work focuses on autonomous robotic systems with emphasis on quadcopters, computer vision, spatial awareness, and multi-robot collaboration. Expert in safe autonomous drone deployment Specializes in collaborative robotics (cobots) Qualified UK commercial drone pilot Research spans: Autonomous reconfiguration of robotic systems Dynamic risk assessment for systems-of-systems Visual SLAM for feature-sparse environments Formal verification of UAS systems Human-robot co-working interfaces Recent publications examine: Robust localization in sewer pipes Visual saliency algorithms for mobile robots Cobotic safety controller synthesis Modular digital twinning frameworks Spatial awareness for multi-robot teams Major grants include EPSRC Programme Grants for buried pipe sensing and Lloyds Registry Foundation funding for cobot safety integration.

Benjamin AltView profile

Researcher

• Cognitive Robotics
• Neurosymbolic AI
• AI Safety
• +4 more

Dr. Benjamin Alt serves as the Technical Director at the AICOR Institute for Artificial Intelligence, affiliated with the University of Bremen. His research focuses on enabling robots to understand and execute complex manipulation tasks collaboratively with humans, emphasizing cognitive robotics , neurosymbolic AI , AI safety , and human-AI interaction . Education: PhD (Dr.-Ing.) in Computer Science, University of Bremen. Current Role: Technical Director at AICOR Institute, operationalizing research strategy and coordinating interdisciplinary teams. Research Goals: Building embodied AI systems that are intuitive, explainable, and safe for human collaboration.

Ulrich KühneView profile

Lecturer

• Embedded Systems Security
• Formal Methods in Security
• Hardware and Software Attacks
• +3 more

Ulrich Kühne is a Lecturer at Télécom Paris , affiliated with the Secure and Safe Hardware (SSH) team and the Information Processing and Communication Laboratory (LTCI) . His research focuses on embedded systems security and formal methods for security guarantees. Research Interests: Embedded systems security, formal verification of protection schemes, and mitigation of hardware/software attacks. Publications: His work spans moving target defense for connected cars, side-channel attack mitigation in neural networks, and hardware-assisted security mechanisms. Labs & Teams: Active in LTCI and SSH, focusing on hardware-software co-design for security.

Aude BillardView profile

Professor

• Robotics
• Human-Robot Interaction
• Imitation Learning
• +7 more

Aude Billard is a Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she leads the Learning Algorithms and Systems Laboratory (LASA). Her work focuses on enabling robots to learn complex tasks through human demonstration, with applications in manipulation, sports, and safe human-robot interaction. Her educational background includes: M.Sc. in Physics, EPFL (1995) M.Sc. in Knowledge-Based Systems, University of Edinburgh (1996) Ph.D. in Artificial Intelligence, University of Edinburgh (1998) Aude Billard's research centers on imitation learning, where robots learn from few demonstrations and even failed attempts to improve generalization and robustness. She emphasizes feasibility over optimality in control, modeling human-like variability to allow rapid adaptation in dynamic environments. Her work enables robots to perform delicate tasks like handling fragile objects and reacting instantly to perturbations, such as catching fast-moving items or playing golf with moving targets. Her research has been widely recognized and featured in BBC and IEEE Spectrum, highlighting its impact on real-world robotics applications. Notable scientific recognitions include: Intel Corporation Teaching Award Swiss National Science Foundation Career Award Outstanding Young Person in Science and Innovation (Swiss Chamber of Commerce) IEEE-RAS Best Reviewer Award Seven best paper awards at premier robotics conferences (ICRA, IROS, ROMAN) She has played key leadership roles in the robotics community, serving as an elected member of the IEEE Robotics and Automation Society Administrative Committee (2006–2008, 2009–2011), keynote speaker at ROMAN 2005, General Chair for HRI 2011, and Co-General Chair for Humanoids 2006. She has also contributed significantly to conference organization and peer review excellence. Aude Billard leads the Learning Algorithms and Systems Laboratory (LASA) at EPFL, a leading research group dedicated to developing intelligent robotic systems capable of learning complex motor skills through interaction with humans and environments.