Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.
Shuangquan (Peter) Wang is an Assistant Professor of Computer Science at Salisbury University. He holds a PhD in Computer Science from the College of William & Mary (2020) and a PhD in Pattern Recognition and Intelligent Systems from Shanghai Jiao Tong University (2008), along with earlier degrees from Wuhan University of Technology and Wuhan Institute of Technology. His research focuses on mobile/wearable computing, activity recognition, smart health, and machine learning. He has over 10 years of experience in academia and industry, including roles at Philips Research East Asia and Nokia Research Center (Beijing). His work emphasizes wearable sensor-based health monitoring, such as fall detection, mastication analysis, and Parkinson’s disease monitoring. He leads the WISH Research Lab and serves as an Associate Editor for Elsevier's Smart Health Journal. Recent contributions include papers on salinity anomaly detection (2024), LLM-based user requirement analysis (2024), and socially acceptable food recognition (2022). His research trends emphasize interdisciplinary applications of machine learning in healthcare and sensor-driven human activity analysis. Professional service roles include coordinating Salisbury University’s Center for Applied Mathematics and Science (2021–2024) and chairing ACM/IEEE CHASE conferences. He has delivered invited talks on artificial intelligence and its societal impacts to diverse audiences, including the Institute of Retired Persons at Salisbury University. His lab, WISH Research Lab, explores innovative solutions in smart health and mobile computing, integrating wearable technologies with machine learning for real-world health applications.
Prof. Vinod Namboodiri is the Forlenza Chair in Health Innovation and Technology at Lehigh University's Department of Computer Science & Engineering and College of Health. He leads the Accessibility and Assistive Technologies (ACCESS) Lab, focusing on computing technologies to address health disparities affecting people with disabilities. His NSF-funded research develops navigation solutions for individuals with disabilities, with emphasis on smart communities and built environment accessibility. He holds a Ph.D. from UMass Amherst and previously served as Full Professor/Associate Director at Wichita State University and Adjunct Senior Scientist at Envision Research Institute. His research spans assistive technologies, applied computer vision, and smart health systems. Notable work includes MABLESim (indoor accessibility simulation), NaVIP (visually impaired navigation), and economic analyses of accessibility investments. His publications explore both technical innovations and policy implications of assistive technologies. Prof. Namboodiri has received multiple awards for research, teaching, and innovation. His work bridges computer science with disability studies, emphasizing real-world impact through interdisciplinary collaboration. Current projects address indoor navigation systems, cost-benefit analysis of accessibility infrastructure, and human-agent interaction platforms for disability empowerment.
Claire Bishop is a Presidential Professor of Art History at the CUNY Graduate Center, widely considered an original thinker and creative interpreter of contemporary art, as well as a dynamic teacher. Her work critically examines participatory art, performance practices, and the relationship between art and politics. She has been based at the CUNY Graduate Center since 2008 and serves as a Contributing Editor to Artforum. Her publications have been translated into twenty languages, reflecting her international influence in the field of contemporary art history. Education: Ph.D. University of Essex, 2002 M.A. University of Essex, 1996 B.A. University of Cambridge, 1994 Bishop's research interests span Contemporary Art, Performance Art, Art & Politics, Exhibition History, History of Art Pedagogy, Post- and De-colonial Theory, and Museology. She is particularly known for her critical engagement with participatory art practices, questioning their political efficacy while exploring new modes of spectatorship in contemporary art. Her work examines how the digital revolution has transformed how we engage with art, arguing against simplistic narratives about technology's impact on visual culture. Bishop's scholarly contributions have been recognized with prestigious awards including the Guggenheim Fellowship (2024), the Mentoring and Teaching Award from CUNY Graduate Center (2024), and the College Art Association's Frank Jewett Mather Award for art criticism (2013). She has also received significant research support including a fellowship from the Center for Ballet and the Arts at NYU to study Merce Cunningham's Museum Events. Awards and Recognition: Guggenheim Fellowship, 2024 Mentoring and Teaching Award, CUNY Graduate Center, 2024 Andy Warhol Foundation Arts Writers Grant, 2017 Frank Jewett Mather Award for art criticism, 2013 Research Fellowship, Sterling and Francine Clark Institute, 2013 Bishop has received substantial grant support for her research, including the Andy Warhol Foundation Arts Writers Grant which enabled her to deepen her investigation into art and politics. Her work as a mentor has been formally recognized by CUNY Graduate Center, highlighting her commitment to developing the next generation of art historians. She has organized numerous academic events including the 'Post-Discipline? Contemporary Artists and Research' seminar series at the Center for the Humanities at CUNY Graduate Center. Bishop maintains an active presence in both academic and artistic communities, regularly contributing to major art publications and participating in international conferences. Her work bridges theoretical inquiry with practical engagement in contemporary art institutions and practices.
Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.
Margherita Pagani is a Full Professor and Director of the SKEMA Centre for Artificial Intelligence at SKEMA Business School in Paris. She holds a Ph.D. in Management and an HDR (Habilitation à Diriger des Recherches). Her roles include Research Affiliate at UC Berkeley’s APEC Study Center and Advisor to the European Economic Social Committee (EESC) on virtual worlds and the Metaverse. Previously, she founded and led the MSc in Digital Marketing & Data Science and the AIM Research Center at emlyon business school. She has held visiting roles at MIT, UCLA, Georgetown, NUS, and Redlands University. Education: Ph.D. (2015, Lyon), HDR (2016, Évry), MSc (1995, Bocconi), MIT Certifications (2005-2006). Research: Focuses on AI in consumer engagement, digital ecosystems, robotics in services, and metaverse applications. Over 130 publications in journals like MIS Quarterly, MIT Sloan Management Review, and Harvard Business Review. Awards: 2023 International Marketing Trends Award, 2022/2023 Top 2% Cited Scientist (Elsevier), 2009 Mobile Marketing Academic of the Year. Her work bridges AI and marketing creativity, emphasizing human-centric systems. She leads initiatives like the SKEMA AI School and organizes conferences on ethics, AI in education, and service recovery. Active in editorial roles for journals like Micro & Macro Marketing and Industrial Marketing Management . Key affiliations include the Association Française de Marketing and involvement in policy initiatives. Supervised over a dozen PhD students, focusing on AI applications in marketing and entrepreneurship.
Simon Colreavy Donnelly is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a member of the Interaction Design Centre and focuses on interdisciplinary research at the intersection of artificial intelligence, educational technology, and healthcare informatics. His work spans machine learning applications in medical data analysis, virtual reality (VR) and extended reality (XR) for inclusive education, and deep learning techniques in chemical analysis and spectroscopy. Research Interests: His primary areas of investigation include generative AI for education equity, semisupervised learning algorithms, virtual learning environments design, and the ethical deployment of immersive technologies in healthcare and palliative care. He also explores NMR spectroscopy analysis using deep learning and develops tools for nutritional content estimation through image processing. Collaborations: His recent collaborations span international teams addressing challenges in toxicity-free online discourse (PAN 2024), semisupervised learning distribution mismatches, and VR applications for post-pandemic blended learning. His work integrates computational methods with real-world applications in education, healthcare, and chemical analysis. Labs/Teams: Active within the Interaction Design Centre at UL, his research group develops practical solutions for accessibility in digital education and healthcare systems, emphasizing user-centered design principles for extended reality applications.
Robert S. Laramee is a Professor at the University of Nottingham (previously at Swansea University), specializing in visualization research. His work focuses on data visualization, scientific visualization, and computational fluid dynamics. He has authored over 170 publications in top journals like IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, and IEEE Computer Graphics and Applications. Research Interests: His research spans information visualization, flow visualization, visual literacy, and educational aspects of visualization. He emphasizes practical applications in fields like healthcare, digital humanities, and computational science. Recent Trends: Recent work includes studies on treemap literacy, educational frameworks for visualization, and interactive systems for clinical data. He has also contributed to visualization resources and surveys, aiming to bridge academic and industry needs. Grants & Collaborations: Collaborations include projects on visualization for smart cities, protein-lipid interactions, and quantum chromodynamics data analysis. No specific grant details are provided in the text. Labs & Teams: Affiliated with visualization research groups at Nottingham and Swansea, though specific lab names are not mentioned.
Prof. Sarthak Misra is a Full Professor in Medical Robotics at the University of Groningen’s Faculty of Medical Sciences, affiliated with the University Medical Center Groningen (UMCG). He leads research in the Robotics and image-guided minimally-invasive surgery (ROBOTICS) group and the Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE) team. His work focuses on advancing medical robotics, microrobotics, and magnetic actuation technologies for surgical and biomedical applications. He holds an ORCID identifier and has published over 127 research outputs, including high-impact articles in journals like Advanced Materials Technologies and European Heart Journal . His research addresses challenges in minimally invasive surgery, soft robotics, and smart materials. Media engagements highlight his contributions to robotic surgery and addressing healthcare workforce shortages through automation. Research interests include: Microrobotics and fluidic systems Magnetic and acoustic actuation for medical devices Soft robotic systems for surgical applications Image-guided interventions 3D printing for biomedical robotics His recent articles emphasize innovations like MagNoFE3D printing and magnetic probes for endovascular interventions. Collaborations span global institutions, reflecting his interdisciplinary approach. No explicit awards are listed, but his extensive media coverage and 127+ publications underscore his impact. He is involved in grants, including OTP-funded projects, and mentors students in advanced robotics and medical engineering.
Dr. Farzan Sasangohar is an Associate Professor in the Department of Industrial & Systems Engineering at Texas A&M University, holding the Mike and Sugar Barnes Faculty Fellowship. He also serves as an Assistant Professor at Houston Methodist Hospital's Center for Outcomes Research and Department of Surgery. His academic roles include affiliations with the Environmental and Occupational Health, Biomedical Engineering, and multiple centers focused on health technologies and systems design. Education: PhD in Industrial Engineering (Human Factors Engineering), University of Toronto (2015) Research Interests: Human factors in healthcare delivery and telehealth systems Wearable technology for stress/health monitoring Crisis management team cognition and decision-making Remote patient monitoring systems Mental health self-management interventions Awards: Jack A. Kraft Innovator Award (HFES, 2023) Dr. Hamed K. Eldin Early Career Award (2022) William C. Howell Young Investigator Award (2021) TEES Young Faculty Fellow (2021) Nominated for Ergonomics Journal Best Paper (2021) Advising & Grants: Mentored over 15 graduate students including Dr. Mahnoosh Sadeghi (PhD 2023) Recipient of NSF PATHS-UP Engineering Research Center funding Active grants in offshore worker fatigue management and telehealth integration Labs/Teams: Director of the Applied Cognitive Ergonomics Lab (ACE-lab) , focusing on human-system interactions in healthcare, aviation, and disaster management. Current projects include: - Wearable stress monitoring systems - Telehealth integration frameworks - Crisis team cognition analysis
Alan H. Barr is a Professor of Computer Science at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science and the Computation & Neural Systems (CNS) department. He is a founding member of the Caltech Computer Graphics Group and a leader in developing mathematically rigorous methods for computer graphics and predictive modeling. His research focuses on enhancing computational modeling accuracy through approaches like interval analysis and constraint-based systems. Notable contributions include deformable models, quaternion interpolation, and cellular simulation frameworks. He has advised over 20 graduate students, many of whom became industry leaders at Pixar, Microsoft Research, and academic institutions like NYU and Brown University. Awards include the ACM SIGGRAPH Achievement Award (1988) and ACM Fellow (1995). Research Interests: Predictive modeling with error bounds Scientific visualization and MRI data analysis Biophysical systems simulation (e.g., cellular organelles) Self-assembling robotic structures for space colonization Mathematically robust computer graphics techniques Key Collaborations: Caltech Biological Imaging Center (Beckman Institute) JPL (Jet Propulsion Laboratory) New computational substrates research (quantum/DNA computing) Recent Work: Expanding into computational biology, medical imaging optimization, and high-confidence systems for managing complex computational interactions. Active in interdisciplinary projects across Caltech divisions.
Afshin Ashari is an Assistant Professor in Landscape Architecture at the School of Environmental Design and Rural Development , University of Guelph. Prior to academia, he worked at BrookMcIlroy Inc., an interdisciplinary firm in Toronto, on architectural and landscape projects in public and private sectors. Education : Masters in Landscape Architecture, University of Toronto Bachelor of Computer Engineering, Azad University of Tehran Research Interests : Afshin explores the intersection of computational design and mixed-reality environments, focusing on: Art-Technology Unity in Public Spaces Algorithmic and Parametric Modeling Data-Driven Design Approaches Interactive Immersive Environments Biophilic Design Agricultural Urbanism Article Trends : His publications emphasize: AI tools for design processes Parametric modeling in urban rehabilitation Climate change communication via social media Drones for visual impact assessments Augmented reality in public spaces Historical and future-oriented design frameworks
Nicola Ballhausen is an Assistant Professor in the Department of Developmental Psychology at the Tilburg School of Social and Behavioral Sciences, Tilburg University, Netherlands. Her research focuses on cognitive and psychological aspects of aging, particularly prospective memory, executive function, and social influences on cognitive health in older adults. Her research interests include prospective memory , cognitive aging , metacognition , problem-solving in older adults , social cognition , and longitudinal studies of aging . She investigates how factors such as intergenerational contact, sense of purpose, and technology use impact cognitive performance and well-being in later life. Her work integrates experimental, survey-based, and qualitative methods, often in cross-national datasets like the Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). The most recent articles highlight a strong focus on prospective memory across the lifespan , the role of social engagement in cognitive functioning , and designing accessible cognitive interventions for older adults. Her publications span top journals in gerontology, psychology, and cognitive science, reflecting interdisciplinary collaboration and methodological rigor. Dr. Ballhausen contributes to research aligned with the UN Sustainable Development Goals, particularly those related to healthy aging and well-being. She collaborates extensively with researchers across Europe and has contributed to major reference works such as The Oxford Handbook of Human Memory . Her work includes both empirical studies and methodological advancements, such as exploratory structural equation modeling. While no formal students or awards are listed, her role in supervising research and contributing to academic training is implied through her position and course involvement. Dr. Ballhausen is involved in the design and evaluation of web-based cognitive tools, such as the Shared, Web-based, Intelligent Flexible Thinking Training (SWIFT), emphasizing user-centered design and ecological validity. Her work bridges fundamental cognitive research with practical applications for aging populations.
Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.
Monica Tatasciore serves as an Honorary Research Fellow, Casual Teaching staff member, and Multi-Discipline Research Fellow at the School of Psychological Science, University of Western Australia. As an Early Career Researcher in the Human Factors and Applied Cognition laboratory, she focuses on optimizing human-automation systems in high-stakes environments like air traffic control and uninhabited vehicle operations. Her academic credentials include: Doctor of Philosophy from The University of Western Australia (2018-2021) Master of Industrial and Organisational Psychology from The University of Western Australia (2018-2020) Bachelor of Science (First Class Honours) in Psychology (2015) Dr. Tatasciore's research examines critical intersections of human cognition and automation, specifically investigating how transparency in decision aids affects operator trust, situation awareness, and workload under time pressure. Her work addresses fundamental questions about automation failure recovery and individual differences in attention control during human-machine collaboration. Analysis of her 2024-2025 publications reveals a cohesive research trajectory centered on human-automation interaction, with strong methodological emphasis on experimental paradigms from cognitive psychology and applied ergonomics. These works consistently address defense-relevant applications while advancing theoretical understanding of trust calibration mechanisms. She has supervised one graduate student and actively contributes to defense-related research through the Human Factors and Applied Cognition lab, where her team develops evidence-based frameworks for automation design in safety-critical systems.
