Mubbasir Kapadia is an Associate Professor in the Department of Computer Science at Rutgers University, affiliated with the School of Arts and Sciences. His research focuses on autonomous virtual humans, crowd simulation, and digital storytelling. Grants: NSF SA&S, DARPA SocialSim, NSF CHS Projects: Human-Building Interaction, NUCLEUM Kapadia’s work combines artificial intelligence , visual computing , and human-computer interaction to develop intelligent systems for crowd modeling, interactive narratives, and architectural design optimization. He has published in venues like European Conference on Computer Vision and Computers and Graphics , emphasizing applications in urban planning and disaster simulation. Scientific Awards: NSF SA&S Grant DARPA SocialSim Grant NSF CHS Grant Kapadia contributes to crowd-aware computer-aided design and interactive storytelling tools , with his research group Intelligent Systems driving innovations in virtual environments.
Dr. Mia McLanders serves as an Adjunct Lecturer in the School of Psychology at the University of Queensland, where she bridges psychological science with clinical healthcare improvement through human factors engineering and simulation-based methodologies. Her work directly impacts neonatal resuscitation protocols, trauma care systems, and medical device design for high-acuity environments. She completed her PhD at the University of Queensland in 2018 with the thesis "Developing the NeoReady TM : a systems approach to supporting teams during neonatal resuscitation", establishing her focus on systems-level interventions in emergency care. Dr. McLanders' research centers on human factors in healthcare , emphasizing medical simulation , neonatal resuscitation , and trauma care systems . Her methodology integrates cognitive task analysis, teamwork observation, and technology evaluation to address critical gaps in clinical workflows. Key contributions include designing cognitive aids for resuscitation teams and developing vibrotactile monitoring systems that reduce cognitive load during emergencies. Analysis of her publication trajectory reveals consistent interdisciplinary collaboration across medicine and psychology, with recent work (2024) prioritizing scalable solutions for rural healthcare barriers and standardized neonatal training. Her studies uniquely combine laboratory validation with real-world clinical implementation, particularly through the Queensland Trauma Education (QTE) program. No scientific awards or fellowships are documented in available materials. While no graduate student supervision is indicated, her collaborative network spans anesthesiology, emergency medicine, and human factors research groups. Current projects appear focused on expanding telehealth-supported trauma care and refining the NeoReady TM system for broader clinical adoption. Her research is operationally linked to the Queensland Trauma Education initiative and neonatal resuscitation improvement programs, involving multidisciplinary teams of psychologists, clinicians, and biomedical engineers working within University of Queensland-affiliated healthcare simulation frameworks.
Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.
Christopher Pal is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. With a Ph.D. from the University of Waterloo, he has held academic positions at the University of Rochester and the University of Toronto, and industry roles at Interval Research and Microsoft Research's Interactive Visual Media Group. Fields of Expertise: Artificial Intelligence, Computer Vision, Pattern Recognition, Machine Learning, and Natural Language Processing Affiliations: CIFAR Chair in Artificial Intelligence, Institute for Data Valorization (IVADO) Member His research focuses on deep learning applications in visual question answering , medical image segmentation , and generative models . Recent work involves multimodal data analysis for climate modeling and vision-language systems for code generation. Key projects include CarbonSense for climate flux modeling and GeoCoder for geometry problem-solving AI. His 15 most recent publications (2023-2025) span topics from diffusion models to multi-agent systems , with emphasis on video generation , 3D animation , and environmental applications . Scientific recognition includes: CIFAR Chair in Artificial Intelligence IVADO Institute Membership Top-2% cited researcher (2021) He has supervised 22 Ph.D. and Master's students, with recent graduates working on generative AI , reinforcement learning , and medical imaging . Current research grants include MITACS-funded projects in software engineering agents and drone imagery analysis for tropical forest conservation.
Claudio Fornaro is a Lecturer and teaching assistant at the Department of Control and Computer Science (DAUIN) at Politecnico di Torino. He has been actively involved in Technological Innovation Engineering doctoral colleges and teaches courses in Computer Science and Aerospace Engineering since 2019/2020. His work focuses on programming education, particularly in C89, and educational technology. University: Politecnico di Torino Department: Department of Control and Computer Science (DAUIN) Affiliated Schools: School of Engineering Academic Rank: Lecturer Research & Publications Key Research Areas: Educational technology, 3D modeling, software development for learning, and programming languages (C89). Recent Work: In 2022, he co-authored an article in IEEE Transactions on Learning Technologies about an integrated framework to support design students in 3D modeling. Labs & Groups Member of the TORSEC - Security Group (DAUIN) at Politecnico di Torino.
Jason Anquandah is a Lecturer in Statistics and Data Analytics at the Faculty of Arts, Creative Industries, and Education (ACE) at the University of the West of England (UWE Bristol). He holds a Ph.D. in Statistics from the University of Leeds, an MRes in Mathematical Modelling, and MSc in Mathematical Science, with a first degree in Actuarial Science. His academic focus spans statistics, data science, and applied mathematical fields. Ph.D. in Statistics, University of Leeds MRes in Mathematical Modelling MSc in Mathematical Science BSc in Actuarial Science His research expertise encompasses Probability and Statistics , Stochastic Control Theory , Mathematical Finance , Actuarial Science , and Machine Learning . He applies these to areas such as Survival Analysis , Insurance , and Labour Markets . His recent publications highlight interdisciplinary work in health informatics , telemedicine , and social determinants of well-being , leveraging statistical methods for public health and behavioral research. His publications demonstrate a focus on applied statistical modeling , health interventions , and data-driven policy analysis . Key trends include: Use of video games to address body image in youth Analysis of telemedicine adoption during the Covid-19 pandemic Studies on health disparities among adolescent mothers in South Africa Application of systematic reviews to assess psychosocial outcomes in medical contexts Jason serves as a member of the Eurofound Advisory Committee (CEI expert in quality of life and public service) and the Institute and Faculty of Actuaries . His work bridges quantitative analysis with real-world applications in health and social sciences.
Andrea Tigrini serves as a Researcher in the Department of Information Engineering at Marche Polytechnic University's School of Engineering in Ancona, Italy. His scientific sector is Bioengineering (IBIO-01/A), with research spanning biomedical signal processing and human motion analysis. Dr. Tigrini's research interests focus on the intersection of biomedical engineering and machine learning, particularly in developing innovative approaches for human motion analysis through electromyography (EMG) and inertial sensing. His work emphasizes creating minimal-sensor solutions for practical applications in rehabilitation technologies, gait analysis, and assistive devices. He investigates neuromuscular control mechanisms during various activities including walking, balance maintenance, and hand gestures. Analysis of his recent publications (2023-2025) reveals a strong trend toward developing accessible diagnostic and assistive technologies using machine learning approaches. His research consistently addresses real-world challenges in diabetic neuropathy detection, prosthetic control, and rehabilitation monitoring, with particular emphasis on creating solutions that require minimal sensor setups to enhance practicality and adoption in clinical settings. His work demonstrates significant contributions to understanding the relationship between neuromuscular signals and movement patterns, with applications spanning rehabilitation engineering, human-computer interaction, and clinical diagnostics. The interdisciplinary nature of his research bridges engineering principles with physiological understanding to create practical healthcare solutions.
Timo Kretschmer M.A. is a Lecturer at HTWK Leipzig's Faculty of Architecture and Social Sciences, specializing in Building Information Modeling (BIM), computer-aided design, and architectural animation. He has been affiliated with the university since 2004, initially working in the Faculty of Civil Engineering before moving to the Faculty of Architecture and Social Sciences in 2014. As Webmaster of the IT organization and Member of the Faculty Council, he plays a significant role in the university's digital infrastructure. His research focuses on BIM implementation, digital building applications, and virtual construction monitoring. He has been involved in significant projects including the cooperative doctoral procedure with Leipzig University on the reconstruction of Max Klinger's 'Christus im Olymp' and the Saxon Ministry of Justice's model project (2007-2008). His current research (2023-2025) continues to advance digital methods in architectural practice. Kretschmer's publications and presentations demonstrate a clear trajectory from foundational BIM concepts to advanced implementation strategies. His 2024 handbook 'BIMcert Handbuch Grundlagenwissen openBIM' represents the culmination of his expertise, while his earlier works from 2004-2015 established his contributions to architectural history and education. His conference presentations since 2015 show increasing specialization in BIM competence development, data security, and interdisciplinary applications. Chairman of DIN NA 005-13-05 AA 'Professional Competence' Spokesperson for buildingSMART eV Specialist Group 'Certification' Member of buildingSMART International PCert Sub-Committee Member of CEN/TC 442/WG8 'Competence' Founding member of buildingSMART eV Regional Groups in Saxony and Central Germany As an active participant in professional organizations, Kretschmer contributes significantly to standardizing BIM competence frameworks. His work with the Saxony Chamber of Architects on the 'Digital Building Application' working group demonstrates his commitment to bridging academic research and professional practice. His jury work for the BIM Champions awards (2021-2025) further establishes his authority in the field. The IT infrastructure he helps maintain, including the BIMcloud system, supports numerous architectural design projects across the faculty.
Manfredo Atzori serves as Associate Professor at the Department of Neuroscience, University of Padova, and has been a research scientist at the Institute of Information Systems of the University of Applied Sciences Western Switzerland (HES-SO Valais) since 2011. Education M.Sc. in Physics, University of Padova, 2006 Ph.D. in Bioengineering, University of Padova, 2009 Research Focus Dr. Atzori pioneers machine learning applications for biomedical multimodal data analysis. His work spans convolutional neural networks for surface electromyography (a field he helped establish globally in 2015), computer-aided cancer diagnosis in biopsies, and 3D-printed robotic prosthetic hands controlled via machine learning. He leads the Horizon 2020 ExaMode project for weakly-supervised knowledge discovery in digital pathology, integrating text and image analysis for medical diagnostics. Research Leadership As Scientific Coordinator of the Horizon 2020 ExaMode project (2019-present), he manages a seven-partner consortium advancing multimodal medical data analysis. He previously coordinated the Hasler Foundation's ProHand project for 3D-printed prosthetics and led the MeganePro Project (2016-2019), which investigated eye-hand coordination in robotic prostheses and neurocognitive effects of amputations using multimodal datasets. Since 2011, he has curated the Ninapro database—a globally utilized resource with thousands of users for robotic hand prosthesis research. Professional Recognition With over 80 peer-reviewed publications exceeding 2,000 citations, Dr. Atzori frequently presents as an invited speaker at international conferences. He serves on the editorial board of Scientific Data (Nature Publishing Group), reflecting his standing in computational biomedical research.
Nasim Parsa serves as Assistant Professor in the Gastroenterology, Hepatology, and Nutrition Division within the Department of Medicine at the University of Minnesota Medical School, focusing on AI-enhanced endoscopic diagnostics and therapeutic interventions. Her research pioneers artificial intelligence applications in gastrointestinal endoscopy, with specialized expertise in: Barrett's Esophagus surveillance and dysplasia detection Peroral Endoscopic Myotomy (POEM) for achalasia management AI-human collaboration frameworks in real-time endoscopy Ultrasound image segmentation using self-supervised learning Rare esophageal conditions like lichen planus Analysis of her 47 publications (2017-2026) reveals escalating research momentum, with recent work (2025-2026) concentrating on clinical AI integration for Barrett's Esophagus, human-AI interaction paradigms, and advanced imaging techniques across gastrointestinal endoscopy. Dr. Parsa maintains active international collaborations reflected in co-authorship networks spanning multiple continents, with research output including 29 articles, 8 reviews, and 5 commentaries. Her work contributes to UN Sustainable Development Goals through AI-driven healthcare innovation.
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.
Kai Hamburger serves as Assistant Professor in the Department of Experimental Psychology and Cognitive Science at Justus Liebig University Gießen, where he conducts research at the intersection of spatial cognition and sensory processing. His institutional role is evidenced by office location (Room F 161, Phil. I) and inclusion in the university's research team listings. His academic credentials include: Dipl.-Psych. from University of Frankfurt (2004) Dr. rer. nat. from University of Gießen (2007) Habilitation from University of Gießen (2015) Research focuses on multimodal landmark processing in human navigation, with pioneering work on olfactory and auditory spatial cues challenging traditional visual-centric models. His investigations into emotion-reasoning interactions —particularly how anxiety affects logical inference—and consciousness mechanisms in spatial tasks integrate cognitive psychology with geographic information science. Recent projects employ virtual reality environments like SQUARELAND to simulate real-world navigation challenges. Publication analysis reveals a decisive shift toward non-visual navigation research since 2020, with 60% of recent work exploring olfactory/auditory landmarks. His 2023-2025 output demonstrates strong collaboration with Markus Knauff's group and increasing application of GIScience methodologies to cognitive questions, particularly in urban navigation contexts. Dr. Hamburger contributes to the DFG-funded SPP1516 project "New Frameworks of Rationality" within a multidisciplinary team including cognitive scientists, psychologists, and computer scientists. The research group maintains dedicated facilities for virtual environment experiments and regularly publishes in high-impact journals like Frontiers in Psychology and Cognitive Science .
Jaakko Sahlsten is a Postdoctoral Researcher at the Department of Computer Science, Aalto University . His work focuses on applying deep learning and Bayesian methods to medical imaging challenges, particularly in radiotherapy and VR-based image manipulation . He collaborates with interdisciplinary teams across oncology, dentistry, and computational biology . Key Research Areas : Medical image segmentation, uncertainty quantification, VR applications, diabetic retinopathy analysis Methodologies : Deep learning, DualUNet architectures, large language models (DR-GPT), Bayesian modeling Clinical Domains : Oropharyngeal cancer, head and neck tumors, dentistry, diabetic retinopathy His recent publications analyze 3D medical image manipulation in VR , AI-driven tumor segmentation , and uncertainty estimation in radiotherapy. He actively explores model robustness and reproducibility in healthcare AI applications, with collaborations spanning institutions in radiation oncology and medical imaging .
Auxiliadora Sarmiento Vega is a full professor at the University of Seville 's School of Engineering within the Department of Signal Theory and Communications . With over two decades of research experience, her work bridges audio signal processing and biomedical applications, focusing on blind source separation, entropy-based methods, and machine learning for healthcare diagnostics. Research Pillars : Audio source separation, biomedical signal/image analysis, and virtual reality integration Key Projects : ACACIA (Signal Analysis), NEUBIAS (Bioimage Analysts Network), and multiple NIH-funded biomedical imaging initiatives Academic Contributions span 15+ years, with groundbreaking work in: Alpha-Beta divergence clustering algorithms EEG processing for motor imagery BCI systems Automated breast cancer grading from histological images Glaucoma and diabetic retinopathy diagnostics via retinal image analysis Virtual reality platforms for emotion analysis research She actively collaborates with institutions like the IEEE Women in Engineering (Spanish section secretary) and NEUBIAS network , while mentoring through outreach programs like g4g Day that empower young women in STEM.
Dr. Lecturer Cengiz GÜNDÜZALP is a Turkish academic at Kafkas University's Kazım Karabekir Technical Sciences Vocational School , Department of Computer Technologies since 2012. Promoted to Assistant Professor in 2022, their work focuses on educational technology integration in STEM fields, particularly through Web 2.0 tools , interactive video , and artificial intelligence applications. Current roles: Assistant Professor (2022-), Lecturer (2012-2022) Institutional committees: Education and Ethics Commission (2023-), Academic Unit Quality Committee (2020-2021) Research interests include metacognitive skill development , digital game-based learning , and technology proficiency in teacher training. Their 15 most recent articles (2015-2025) examine: Augmented reality gamification in science education AI adoption frameworks for STEM teachers Interactive video effectiveness in web-based courses Project/resource-based teaching methods Robotics integration in education Collaboration network includes: Hüseyin Ateş (Kırşehir Ahi Evran University) Yüksel Göktaş (Atatürk University) Ezgi Pelin Yıldız (Kafkas University) Academic metrics: 36 publications, 89 citations, h-index 5 (YÖKSIS); Google Scholar: 162 citations, h-index 7.
