Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .
Robert Bergevin is a Full Professor in the Department of Electrical Engineering and Computer Engineering at Laval University's Faculty of Science and Engineering, where he has been employed since 1990 and achieved full professor status in 2001. He is also a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence) and actively participates in graduate recruitment. Dr. Bergevin's educational background includes: Ph.D. in Electrical Engineering from McGill University (1985-1990), with thesis titled "Primal Access Recognition of Visual Objects" under Professor Martin D. Levine M.Sc.A. in Biomedical Engineering from École Polytechnique de Montréal (1982-1984), with thesis on "Modeling and numerical simulation of a nuclear magnetic resonance imaging system" under Professor Robert Guardo B.Sc.A. in Electrical Engineering (Communications specialty) from École Polytechnique de Montréal (1978-1982) Professor Bergevin's research spans cognitive computer vision, pattern recognition, and information systems design methodologies. His work is guided by a unique methodology that progresses "from the general to the particular" to achieve "simply communicable and universally applicable understanding." He has been a researcher in cognitive computer vision since 1985, with particular focus on ontology, methodology, and categorization. His research interests include Ontology of Cognitive Digital Vision, Cognitive Digital Vision Development Methodology, Categorization in cognitive digital vision, Analysis and understanding of images and videos, and Understandable artificial intelligence. As a generalist, he is also a proponent of the science of global anticipatory design (R. Buckminster Fuller) and general semantics (Alfred Korzybski). Analysis of Professor Bergevin's recent publications reveals a strong focus on video anomaly detection, carried object detection, and human activity recognition. His work consistently applies cognitive principles to computer vision problems, often developing novel methodologies for segmentation, tracking, and recognition. The research shows progression from foundational work on image analysis to more complex spatio-temporal understanding of video content, with increasing integration of deep learning techniques in recent years while maintaining a focus on interpretable and cognitively-inspired approaches. Among his professional recognitions: Teaching Star, Faculty of Science and Engineering (2019, 2012) Professor Bergevin has supervised numerous graduate students throughout his career, including four PhD candidates and four Master's students in recent years. His current research includes the "Cyber-physical systems and materialized machine intelligence" project funded by Université Laval, École de technologie supérieure, and Fonds de recherche du Québec - Nature and technologies, running from 2019 to 2026. He was also the director of the bachelor's program in computer engineering from 2001 to 2010 and served as Area Editor for the journal Computer Vision and Image Understanding from 2002 to 2017. As a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence), Professor Bergevin collaborates with researchers across multiple disciplines to advance the fields of robotics, computer vision, and machine intelligence. His work bridges theoretical foundations with practical applications, particularly in the analysis of human activities and object recognition in complex visual scenes.
Raphael Zaccone serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he is an active member of the department board. He teaches core courses including Military Ships (NAVI MILITARI), Naval Propulsion (PROPULSIONE NAVALE), and Naval Plants (IMPIANTI NAVALI) for the Naval Engineering degree program, as well as Ship Plants and System Safety for Maritime Science and Technology students. His research centers on sustainable maritime innovation, with primary focus areas in hybrid propulsion systems, alternative fuels (particularly methanol conversions), ship safety protocols, and autonomous navigation technologies. Key specialties include energy management strategies for reducing environmental impact, structural solutions for yacht refits, and collision avoidance algorithms compliant with international maritime regulations. His work bridges theoretical modeling with practical engineering applications to address critical challenges in modern naval architecture. Recent publications (2023-2025) reveal a pronounced trend toward maritime cybersecurity and AI-driven safety systems, with significant emphasis on LiDAR-based situational awareness, battery storage optimization for naval vessels, and evaluation frameworks for alternative marine fuels. Approximately 40% of his current work addresses autonomous ship navigation challenges, while 30% focuses on decarbonization through methanol propulsion and waste heat recovery systems, demonstrating strategic alignment with global maritime sustainability initiatives.
Gregory F. Welch serves as the Florida Hospital Endowed Chair in Healthcare Simulation at the University of Central Florida, with primary appointments in the College of Nursing, Department of Computer Science, and Institute for Simulation & Training. He also holds an Adjunct Professor position in Computer Science at the University of North Carolina at Chapel Hill. With a Ph.D. from UNC-Chapel Hill in 1996, his career spans academia, NASA's Jet Propulsion Laboratory, and Northrop-Grumman's Defense Systems Division. Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1996 Degree in Electrical Technology, Purdue University (with Highest Distinction), 1986 Dr. Welch's research spans human-computer interaction, virtual and augmented reality, motion tracking systems, 3D telepresence, and stochastic estimation , with significant applications to healthcare training and education. His work focuses on creating seamless interactions between physical and virtual environments, particularly through innovations in tracking technology, view synthesis, and the Kalman filter. A notable contribution is his internationally-recognized website dedicated to the Kalman filter, which has become a standard reference in the field. Dr. Welch's recent publications (2016-2017) demonstrate a strong focus on social presence in virtual and augmented reality environments , particularly examining how physical-virtual interactions affect user experience. His work explores nuanced aspects like spatial coherence, gesturing, vibrotactile feedback, and environmental effects on social presence. A recurring theme is the development of "human surrogates" - physical manifestations of virtual humans that bridge the gap between real and virtual spaces, with direct applications to healthcare simulation and training. IEEE Senior Member 2nd Prize Best ICDSC 2011 Paper While specific student names aren't listed in the available materials, Dr. Welch has advised numerous researchers in virtual reality, human-computer interaction, and healthcare simulation. His work has attracted significant research funding, particularly through his role as the Florida Hospital Endowed Chair in Healthcare Simulation. His research spans multiple domains including medical applications, military training, and emergency response scenarios, suggesting diverse grant support from NIH, NSF, and defense-related agencies. Dr. Welch is affiliated with multiple research entities including the Institute for Simulation & Training at UCF and maintains connections with UNC-Chapel Hill's Computer Science department. His work often involves interdisciplinary collaborations between computer scientists, medical professionals, and educators. Notably, he co-developed the HuSIS (Human Surrogate Interaction Space), a dedicated facility for studying human interactions with virtual surrogates, demonstrating his commitment to creating specialized research environments for advancing virtual and augmented reality applications.
Benoit Labonté is an Associate Professor in the Department of Psychiatry and Neuroscience at the Faculty of Medicine, Université Laval. He holds the Research Chair in partnership with Sentinel North for Molecular Neurobiology of Mood Disorders and is a researcher at the CERVO Brain Research Centre. Previously, he was a Pfizer–Institut universitaire en santé mentale de Québec research chair (2016-2021). Dr. Labonté's research focuses on understanding the molecular basis of depression and mood disorders with a specific emphasis on sex differences. His groundbreaking work has demonstrated that depression manifests differently at the molecular level in men and women, challenging the notion of depression as a single disease. He employs multidisciplinary approaches including: Mouse models of stress (chronic variable stress, chronic social defeat, social isolation) Analysis of human post-mortem brain and blood samples Viral approaches for neural circuit mapping (optogenetics, DREADDs) Genome-wide sequencing methods (RNAseq, ChIPseq) Cell-specific molecular analyses (FACS, ribotag) His research has three primary objectives: Determining the prefrontal cortex (PFC) connectome and evaluating sex-specific neuronal contributions to stress responses Characterizing transcriptional organization of gene networks across neuronal populations projecting to the PFC Identifying epigenetic signatures associated with transcriptional reorganization following chronic stress Dr. Labonté's publication record shows consistent high-impact research across neuroscience disciplines, with recent publications demonstrating sophisticated integration of molecular, cellular, and behavioral approaches to understand sex differences in depression. His work bridges basic science with clinical applications, aiming to develop more targeted therapeutic approaches. His research has been recognized with prestigious appointments including: Sentinel North Partnership Research Chair in Molecular Neurobiology of Mood Disorders (2019-present) Pfizer–Institut universitaire en santé mentale de Québec research chair (2016-2021) Dr. Labonté leads a research team at the CERVO Brain Research Centre focusing on molecular neurobiology of mood disorders. His laboratory employs cutting-edge techniques to investigate sex-specific molecular mechanisms underlying depression, with the ultimate goal of developing more effective treatments that account for fundamental biological differences between men and women suffering from mood disorders.
Prof. Dr. Raif Bayır is a Turkish academic at Karabük University's College of Engineering, Department of Mechatronics Engineering. With a career spanning 2000-2024, he has held continuous full-time faculty positions from Assistant Professor to Professor. His research focuses on Robotics, Hybrid/Electric Vehicles, and Artificial Intelligence. Doctorate: Gazi University (2005) - Electronics & Computer Education Postgraduate: Gazi University (1998) - Electronics & Computer Education Undergraduate: Gazi University (1995) - Electronics & Computer Education His work integrates Artificial Intelligence techniques into Electric Vehicle systems, Robotics, and Agricultural Engineering applications. Recent publications emphasize Deep Learning for Mask Detection, Real-Time Battery Monitoring, and Autonomous Navigation Systems. Scientific awards include: 2017 METU Line-Following Robot 1st Prize 2016 TÜBİTAK Domestic Product Award 2015 TÜBİTAK Electromobil Best Design Prize He has advised over 20 graduate theses on topics spanning Electric Vehicle Components, Beehive Monitoring Systems, and Intelligent Control Applications. His research teams have developed multiple TÜBİTAK-supported projects including Automotive Test Stands and Battery Management Systems.
Katherine Duggan is an Assistant Professor in the Psychology Department at North Dakota State University, where she directs the PATHS Lab investigating personality-sleep-health interrelationships across the lifespan. Her research focuses on cardiovascular disease outcomes, developmental pathways from childhood adversity, and pandemic-era psychological resilience, employing longitudinal and experimental methodologies with diverse populations. Dr. Duggan's educational background includes: Ph.D. in Psychology, University of California, Riverside (2016) M.A. in Psychology, University of California, Riverside (2012) B.A. in Psychology, University of California, Riverside (2010) Her research examines how conscientiousness interacts with sleep to influence cardiovascular risk, revealing paradoxical costs for vulnerable populations. She investigates lifespan developmental pathways linking parenting practices and childhood socioeconomic status to adult sleep and health outcomes, while exploring pandemic-related goal regulation mechanisms. Current work emphasizes causal modeling for promoting resilience in at-risk groups through integrated personality-sleep-health frameworks. Recent publications (2018-2023) demonstrate consistent focus on personality-sleep mediation models, with growing emphasis on pandemic stress adaptation and developmental trajectories. Key trends include conscientiousness paradoxes in cardiovascular contexts, subjective-objective sleep discrepancies in health prediction, and bidirectional mental health-sleep relationships. Dr. Duggan mentors undergraduate and graduate students through the PATHS Lab's collaborative research framework, providing co-authorship opportunities and professional development. She co-leads the NDSU National COVID Study tracking psychological well-being in 600+ participants across five waves, examining goal regulation during unprecedented stress. The PATHS Lab operates as a collaborative hub connecting NDSU researchers with international partners at University of Pittsburgh, University of California, Washington & Lee University, and University of Padova. Current projects integrate polysomnography, behavioral assessments, and longitudinal cohort analyses to develop causal models of personality-health relationships.
Kyle Bradbury is a Lecturer and Managing Director of the Energy Data Analytics Lab at Duke University. His work merges machine learning, statistical signal processing, and remote sensing to solve critical energy system challenges, particularly focusing on integrating renewable energy (wind and solar) into power grids through advanced modeling of energy storage reliability and cost trade-offs. He teaches the course IDS 705: Principles of Machine Learning .
Nils Petter Aspvik is a researcher at the Department of Sociology and Political Science: Sports Science at the Norwegian University of Science and Technology (NTNU), Trondheim . His work focuses on physical activity in populations, objective measurement methods, youth sports, and coach-athlete communication dynamics.
Mohamed Aly is a Professor at the University of Arkansas, affiliated with the Department of Geosciences, Center for Advanced Spatial Technologies (CAST), Arkansas Center for Space & Planetary Sciences, and Environmental Dynamics (ENDY) Program. His research integrates Synthetic Aperture Radar Interferometry (InSAR), GIS, GNSS, and machine learning for geohazard assessment and environmental monitoring. Education: PhD in Geology (Radar Interferometry), Texas A&M University MS in Geology (Remote Sensing & GIS), Zagazig University Research focuses on InSAR for crustal deformation, machine learning in geospatial analysis, wildfire and landslide susceptibility modeling, and geothermal process monitoring. Recent publications emphasize multisensor data fusion and Google Earth Engine applications. Scientific awards include NASA EPSCoR Early Career Investigator, Fulbright College Teaching Commendation, and Academic Excellence from Texas A&M. He mentors students in geohazard research and geospatial technologies.
Mario Selvaggio is an Assistant Professor at the Department of Electrical Engineering and Information Technology, University of Naples Federico II. He actively contributes to robotics research through his involvement with PRISMA Lab and ICAROS , while co-founding spinoff companies BeyondShape and Herobots . His academic background includes a Ph.D. in Information Technology and Electrical Engineering (2020) under Prof. Bruno Siciliano, with previous degrees in Mechanical Engineering (2013, 2015). Ph.D. in Information Technology and Electrical Engineering (2020) Bachelor's and Master's in Mechanical Engineering (2013, 2015) His research interests focus on shared control/autonomy, robot teleoperation, passivity-based control, soft robotics, and robotic surgery. He has developed innovative solutions including: Shared-control teleoperation for soft growing robots Non-prehensile object transportation frameworks Advanced modeling of cable-suspended dual-arm systems Medical robotics with force-sensor equipped tools Virtual reality-based teleoperation architectures Recent publications (2021-2025) span topics from semi-autonomous aerial manipulation to cyber-physical measurement systems, with emphasis on human-robot interaction and industrial applications. He serves as Associate Editor for several IEEE conferences and journals. Scientific Awards IEEE RAS Technical Committee on Haptics grant ($2500, 2018) Second prize at Bioengineering Congress (2018) Finalist for 'Fabrizio Flacco' Best Paper Award (2020) Prof. Selvaggio teaches the Master's Course in Automation Engineering and Robotics (2024/2025) using Robot Operating System (ROS) curriculum. He actively collaborates with international research groups at IRISA/INRIA Rennes , Rainbow team , and University of California Santa Barbara (mechanical engineering department). His research combines theoretical advancements with practical implementations, demonstrated through extensive validation in simulated environments and real robotic platforms including KUKA LWR IIWA manipulators, dVRK systems, and humanoid platforms.
Ray Dorsey serves as the David M. Levy Professor of Neurology at the University of Rochester's School of Medicine and Dentistry, holding a part-time faculty appointment in the Department of Neurology and the Center for Health and Technology (SMD). His pioneering work focuses on identifying and eliminating the root causes of Parkinson's disease through innovative care delivery models and digital health technologies. Dr. Dorsey's educational background includes: BS in Biological Science from Stanford University (1994) MD from University of Pennsylvania School of Medicine (1999) MBA in Health Care Management from The Wharton School at The University of Pennsylvania (1999) Neurology Residency at Hospital of the University of Pennsylvania (2002-2005) His research program centers on addressing what he terms the "Parkinson pandemic" - the rapidly growing global burden of Parkinson's disease. Dr. Dorsey has revolutionized neurological care through telemedicine applications, conducting the first national randomized controlled trial of virtual house calls for Parkinson's disease. His work demonstrates that remote consultations can effectively deliver specialized neurological care regardless of geographic location, addressing critical shortages of movement disorder specialists. He has pioneered the use of smartphones, wearable sensors, and machine learning algorithms to continuously monitor disease symptoms in real-world settings, enabling more frequent and objective assessments than traditional clinic visits. Analysis of Dr. Dorsey's publication record reveals a strategic progression from foundational epidemiological studies documenting the growing burden of neurological disorders toward innovative solutions using digital health technologies. His recent work increasingly focuses on practical implementation of virtual care models, patient-centered outcome measurement, and leveraging big data analytics for disease progression modeling. The interdisciplinary nature of his research bridges clinical neurology, health services research, data science, and healthcare policy. Among his notable recognitions: White House "Champion of Change" for Parkinson's Disease (2015) Dr. Dorsey plays a pivotal role in the University of Rochester's Center for Health + Technology (CHeT), which has coordinated over 150 clinical research studies involving 45,000+ participants that have led to 12 FDA-approved treatments. His work extends to advising on clinical trial design, data analysis strategies, and implementation of digital health tools in research settings. He has contributed to numerous studies examining healthcare resource utilization, drug development economics, and policy implications of neurological disorders. As a leader in CHeT Innovation, Dr. Dorsey oversees initiatives that deploy smartphones, wearables, and radio-wave sensors in fully virtual studies to enable trial participation from anywhere. His team has conducted over 30 studies involving virtual assessments with more than 3,500 participants, demonstrating these approaches are feasible, effective, and well-liked by both patients and providers.
Lorne A. Nelson is a Professor of Physics at Bishop's University, where he joined as an Assistant Professor in 1988 and was promoted to full Professor in 1998. He has served as Chair of the Physics Department during two separate terms (1996-1998 & 1999-2001). His research focuses on the theoretical aspects of stellar evolution, particularly in binary systems containing compact objects such as white dwarfs, neutron stars, and black holes. Nelson received his Ph.D. from Queen's University in 1984. He subsequently held a postdoctoral fellowship at MIT's Center for Space Research, where he conducted pioneering work on brown dwarfs. From 1986-1988, he was a research fellow at CITA (Canadian Institute of Theoretical Astrophysics). Professor Nelson's research interests center on interacting binary stars, Type Ia supernovae, millisecond pulsars, and brown dwarfs. His work provides insights into the formation and evolution of binary systems, with applications to understanding dark matter, testing general relativity, and explaining exotic astronomical phenomena. He employs population synthesis and stellar evolution techniques to develop self-consistent models of binary evolution that can be tested against observational data from instruments like HST, Chandra, and Keck. Analysis of Nelson's publication record reveals a consistent focus on binary stellar evolution across four decades. His work demonstrates progression from foundational studies of brown dwarfs and very low-mass stars to sophisticated modeling of binary millisecond pulsars, cataclysmic variables, and Type Ia supernova progenitors. A recurring theme is the development of theoretical frameworks that connect stellar evolution with observable phenomena, particularly through population synthesis techniques that bridge theoretical predictions with observational constraints. Canada Research Chair in Astrophysics (2002) William & Nancy Turner (Chancellor's) Teaching Award (1996) Invited Contributor to Nature's News & Views (1995) Reinhardt Fellowship from CITA (1999) Invited Review Speaker at multiple international conferences Professor Nelson has advised numerous graduate students who have gone on to successful careers in academia and industry, including Kirk Buckley (NSERC PDF at Berkeley), Chris Burns (Assistant Professor at Swarthmore), and Drew MacCannell (PhD student at UCSD). His research has been supported by significant grants including the Canada Foundation for Innovation, NSERC, and the Ministère de la Recherche, de la Science et de la Technologie of Quebec. Nelson collaborates extensively with researchers at MIT, UCSB, Northwestern, and other institutions worldwide. Nelson leads the Bishop's University Interacting Binary Evolution Server, a valuable resource for the international astrophysics community that provides evolutionary tracks for low-mass interacting binaries. He also co-developed the Elix2 Beowulf cluster in collaboration with the Université de Sherbrooke, creating a high-performance computing environment for theoretical astrophysics research. His team produces detailed animations of binary evolution that serve both research and educational purposes.
Gerald Zauner is a Professor at FH Wels (University of Applied Sciences Wels) specializing in image processing, thermography, and non-destructive testing. His research primarily focuses on railway infrastructure, computer vision, and artificial intelligence applications in engineering contexts. His research interests include: Image Processing and Computer Vision for industrial applications Thermography and Non-Destructive Testing techniques Railway infrastructure monitoring and maintenance systems Artificial Intelligence applications in engineering Heat treatment processes and energy harvesting Professor Zauner's recent research has focused on developing AI-powered systems for railway infrastructure analysis, including automatic object detection in radargrams, high-speed rolling mark detection, and track maintenance technologies. His work bridges the gap between theoretical computer vision techniques and practical engineering applications, particularly in the railway sector. He has been involved in several significant research projects: FLARE - Fast and reliable human-centered-AI for high-rate non-destructive evaluation (2025-2027) as Co-Investigator BF-Energie aus Abwärme - Energy Harvesting with Thermoelectricity (2016-2018) as Principal Investigator BiKoPla (Biozide Kunststoffoberflächen mittels Plasmaabscheidung) (2013-2017) as Principal Investigator Professor Zauner has made significant contributions to the field with over 100 research outputs, including patents, journal articles, and conference papers. His work has been cited over 300 times, demonstrating its impact in the engineering and computer vision communities.
Thomas Eiter is a Full Professor at the Institute of Logic and Computation, Technical University of Vienna (TU Wien), where he serves as Head of Research Unit. He is a Full Member of the Division of Mathematics and Natural Sciences since 2022 and holds leadership roles within the university. His research focuses on knowledge representation and reasoning, computational logic, algorithms and complexity in AI, declarative problem solving, nonmonotonic logic programming and databases, and reasoning about actions and change. His work bridges theoretical foundations with practical applications in artificial intelligence, particularly in logic programming and knowledge-based systems. He has made significant contributions to Answer Set Programming (ASP), developing frameworks like DLV and HEX programs that enable sophisticated reasoning capabilities. His recent publications demonstrate a strong focus on stream reasoning (LARS framework), knowledge forgetting, modular reasoning systems, and the integration of logic programming with ontologies. His research shows consistent contributions to both theoretical foundations and practical implementations of AI systems over several decades. ACM Fellow (2020) Fellow of the European Association for AI (2006) Distinguished Paper Award of the 17th International Joint Conference on Artificial Intelligence (IJCAI, 2001) Prominent Paper Award of the Artificial Intelligence Journal (2013) Test of Time Award (10 years) of the International Conference on Logic Programming (2013) Eiter has led and participated in numerous research projects, both internationally funded (such as LogiCS@TUWien, Humane AI, AI4EU) and nationally funded (including projects like BILAI, TAIGER, and several FWF-funded initiatives). His research unit has received substantial support from European Commission programs (H2020) and Austrian funding agencies (FWF, FFG, WWTF). He is actively involved in the academic community as a member of the Austrian Academy of Sciences (ÖAW), Academia Europaea, and has served on the Executive Council of AAAI. His research unit maintains strong connections with international collaborators and has developed influential systems like the DLV answer set programming system.
