Martin Christof Kindsmüller is a Professor of Human-Computer Interaction at the University of Applied Sciences Brandenburg , holding this position since September 2014. Previously, he served as Acting Professor of Human-Computer Interaction at the University of Hamburg (2012-2014). Member of GI e.V. - Fachbereich MCI Associated with Zentrum Mensch-Maschine-Systeme (ZMMS) at TU Berlin Co-founder of IUUI Research Group - Intuitive Use of User Interfaces Research Interests: His work spans User Experience (UX) , Usability Engineering , and Intuitive User Interfaces , with applications in Smart Applications , Medical Systems , and cross-platform development. He has contributed to frameworks like HCD3A for data-driven app design and theories of trend literacy. Recent Publication Trends: His 2025 studies focus on tangible interfaces and collaborative spatial interaction , while 2024 work addresses artistic data visualization and media informatics education . Earlier research (2021-2017) emphasizes UX implementation in SMEs , zooming UIs , and emotional computing . Academic Contributions: He has served on program committees for Mensch & Computer , CogSci , and KogWis conferences, and as reviewer for Behaviour & Information Technology . His teaching focuses on media informatics curricula and practical UX integration.
Dr. Idongesit Ekerete (FHEA, IEEE/IPEM member) is a Lecturer in Computing Science at the School of Computing , Ulster University. He serves as Lab Manager for the Pervasive Computing Research Centre and co-investigator in a £3.3M Advanced Research and Engineering Centre project focused on FinCrime. His academic background includes a B.Eng. (First Class) in Electrical/Electronic Engineering from University of Uyo (2011), M.Sc. in Biomedical Engineering from University of Strathclyde (2017), and a PhD in Unobtrusive Sensing from Ulster University (2021). Current role: Lecturer in Computing Science (Ulster University, since 2021) Past role: Lecturer in Electrical/Electronic Engineering (University of Uyo, 2011–2021) Professional: Vice-Chair of IEEE SMC UK-Ireland Chapter His research focuses on privacy-preserving home monitoring systems using unobtrusive sensing , sensor fusion , and AI activity modeling . Recent publications explore thermal sensor applications for mood detection, federated learning for financial crime detection, and gait analysis for elderly wellbeing. Key themes include human-computer interaction , digital twins , and control systems engineering applied to healthcare contexts. Scientific contributions include: Learning and Teaching Award 2024 for student support UNIUYO Best Graduating Student Award Prof. Hilary’s Academic Excellence Award He has authored 20+ research outputs and led collaborations across biomedical engineering, pervasive computing, and financial crime detection domains.
Kelly Bijanki, Ph.D. , is an Associate Professor at Baylor College of Medicine with primary affiliation in Neurosurgery and joint appointments in Psychiatry and Neuroscience. Her research focuses on intracranial mapping of affective neural circuits and developing neuromodulation therapies for psychiatric disorders. Baylor College of Medicine (2016-present) Director of Intracranial Monitoring Research Research Platforms: Stereotactic EEG-informed DBS, Human Electrophysiology Research Expertise : Investigates neural substrates of mood disorders using invasive brain recordings Specializes in cingulum bundle, amygdala, and salience network stimulation Develops translational models for affective dysfunction treatment Integrates advanced neuroimaging with electrophysiological data Studies autonomic and facial motor correlates of emotional states Publication Trends : Focus on socio-affective processing networks Emphasizes brain stimulation for psychiatric conditions Combines imaging and electrophysiology in depression research Explores temporal dynamics of neural circuits Develops novel analytical methods for neurostimulation data Scientific Recognition : NIH R01 MH127006 (2021-2026) - $3.6M NIH K01 MH116364 - NIMH Mentored Career Development NIH R21 NS104953 - Exploratory Brain Stimulation Research Caroline Wiess Law Fund Support Collaborative grants with institutions like Duke, UCLA, and University of Iowa Collaborative Network : Key collaborators: Dr. Sarah Heilbronner, Dr. Nader Pouratian, Dr. Nanthia Suthana Multi-institutional partnerships in biophysics and biomedical engineering Leadership in stereotactic EEG-augmented DBS for psychiatric disorders
Albert J. Kettner is an Associate Professor at the University of Colorado Boulder and serves as the Research Associate Director of INSTAAR (Institute of Arctic and Alpine Research) and Director of the DFO Flood Observatory. His work focuses on understanding and modeling Earth surface processes, particularly related to hydrology, sediment transport, and flooding on a global scale. Dr. Kettner received his educational training in the Netherlands: PhD: Delft University of Technology, 2007 MS: Wageningen University, 1997 BS: Wageningen University, 1993 His research primarily focuses on modeling sediment flux responses within river basins to human impact and climate change. He develops methodology to simulate sediment properties based on provenance and studies influences of rapid climate change (deglaciation) during the late Quaternary on sediment fluxes to the ocean. His work integrates remote sensing data with numerical modeling to understand hydrological extremes, flood dynamics, and sediment transport processes in changing environments. Analysis of his recent publications reveals a strong trend toward understanding climate change impacts on hydrological systems, with particular emphasis on how warming temperatures affect sediment transport in mountainous regions, flood dynamics, and delta morphology. There's a clear research trajectory incorporating satellite data for flood monitoring and advancing FAIR (Findable, Accessible, Interoperable, Reusable) principles into community modeling software infrastructure. Dr. Kettner has received notable recognition for his scholarly contributions: PROSE Award for Best Earth Science Book, Association of American Publishers, 2019 As Director of the DFO Flood Observatory and Associate Director of INSTAAR, Dr. Kettner leads significant research initiatives in flood monitoring and Earth surface dynamics. He assumed the role of acting director of INSTAAR on July 10, 2023, following Merritt Turetsky's return to faculty positions. His work has been supported by substantial grants, including a $2.56 million National Science Foundation grant for the OpenEarthScape project, where he serves as a co-PI alongside Eric Hutton, Irina Overeem, and Mark Piper. Dr. Kettner is deeply involved with the Community Surface Dynamics Modeling System (CSDMS), where he contributes to advancing research in geosciences through model integration tools. His DFO Flood Observatory provides critical flood and river information using remote sensing approaches to water monitoring, serving as an important resource for understanding global flood patterns and risks, particularly in the context of climate change.
Owen Rambow is a Professor at Stony Brook University's AI Innovation Institute, specializing in natural language processing and computational linguistics with a focus on formal linguistic analysis. Education and Career: Ph.D. in Computer and Information Sciences, University of Pennsylvania 15-year tenure as Research Scientist at Columbia University Industry experience at AT&T Labs—Research and Elemental Cognition LLC Research Focus: Rambow's work centers on morphology, syntax, and semantics within Tree Adjoining Grammar (TAG) frameworks, bridging phrase structure and dependency representations. His research spans natural language generation/understanding, discourse analysis of belief/sentiment signaling in email/Twitter communications, and sociolinguistic studies of power/gender dynamics in written conversations across Arabic, English, German, and Hindi. Publication Trends: Recent work (2024-2025) heavily explores large language model capabilities in multi-dimensional writing assessment, emotion recognition, theory of mind validation, and morphophonological processing. Key themes include zero-shot learning limitations, cross-dialectal analysis, and pragmatic marker recognition in specialized domains like roadrunner cartoon dialogues.
Professor Hyung Seok Kim is a distinguished academic at Sejong University, currently serving as Professor in the Department of AI and Robotics. He also holds significant administrative positions including Dean of the College of Software Convergence at Sejong University. Professor Kim leads the MINES LAB (Mobile Intelligent Embedded Systems Lab), located in Room 211, Chungmu Hall at Sejong University, where he directs research in cutting-edge AI and embedded systems technologies. Professor Kim's educational background includes: Bachelor of Engineering: Department of Electrical Engineering, Seoul National University Master of Engineering: Department of Electrical and Computer Engineering, Seoul National University Doctor of Engineering (Ph.D.): Department of Electrical and Computer Engineering, Seoul National University Professor Kim's research spans multiple domains at the intersection of artificial intelligence and embedded systems. His work focuses on AI robots, wearable AI devices, Large Language Models (LLMs), and on-device AI technologies . His research group develops innovative solutions for emotion recognition, medical imaging analysis, and IoT applications. The MINES LAB specifically targets the integration of AI with embedded systems to create efficient, low-latency solutions for real-world problems ranging from healthcare monitoring to industrial applications. Analysis of Professor Kim's recent publications reveals a strong focus on medical AI applications, federated learning for IoT networks, and multimodal emotion recognition . His work demonstrates consistent innovation in applying deep learning techniques to medical imaging (particularly ophthalmology and cardiology), developing efficient edge-AI solutions for wearable devices, and creating novel network optimization approaches for industrial IoT. The publications show a clear trajectory toward more integrated, privacy-preserving AI systems that can operate effectively on resource-constrained devices. While specific awards to Professor Kim aren't detailed in the provided information, his research group has achieved notable recognition: Dr. Song Seung-hwan, a Ph.D. candidate at the lab, received the Presidential Industrial Service Medal Professor Kim has mentored an extensive number of students throughout his career, with alumni pursuing diverse career paths at leading organizations worldwide. His former students have secured positions at major technology companies including Samsung Electronics, LG Electronics, Kakao, and Amazon, as well as academic positions at universities globally. The MINES LAB currently supports multiple graduate students, post-doctoral researchers, and research assistants working on various AI and embedded systems projects. Professor Kim's research appears to be well-funded, with connections to industry partners including Hyundai Motor Company and Samsung Electronics, though specific grant details aren't provided in the text. The MINES LAB serves as the central hub for Professor Kim's research activities, focusing on AI robots, wearable AI devices, and LLM applications. The lab maintains active collaborations with industry partners and has produced numerous commercial applications through its alumni network. Current research directions include developing low-latency emotion recognition systems, medical imaging analysis tools, and efficient network protocols for IoT applications. The lab environment appears highly collaborative, with both full-time and part-time researchers contributing to various projects across the AI and embedded systems spectrum.
Clemens Brunner is a Researcher at the Institute of Psychology within the Faculty of Natural Sciences at the University of Graz. His work bridges electrical/biomedical engineering and cognitive neuroscience, specializing in the neural mechanisms of arithmetic processing and numerical cognition. He actively develops open-source neuroimaging tools used globally in EEG research and sleep analysis. His research focuses on EEG oscillations, biosignal processing, and machine learning applications in cognitive neuroscience. Key interests include arithmetic fact learning, neural correlates of numerical order processing, and non-invasive brain stimulation effects on mathematical cognition. His expertise spans Python programming, statistical analysis, and contributions to major scientific libraries like scikit-learn and SciPy. Analysis of his recent publications reveals consistent emphasis on electrophysiological signatures of arithmetic processing, with growing integration of computational methods and neuromodulation techniques. His work demonstrates strong methodological innovation through open-source software development for EEG analysis and sleep staging. Brunner contributes to the University of Graz's "Brain and behavior" research network, developing tools like MNELAB, SleepECG, and XDF.jl that enhance reproducibility in neuroscience. His collaborations extend to major projects including MNE-Python and BNCI Horizon 2020, advancing brain-computer interface methodologies and neuroimaging standards.
Ingela Nyström is a Professor in Visualization at Uppsala University's Department of Information Technology. She serves as the node coordinator for InfraVis and as Director of Postgraduate Studies at the Department of Information Technology. Her interdisciplinary work bridges Uppsala University's three academic domains through collaborations with the Centre for Image Analysis (CBA), Centre for Women's Mental Health (WOMHER), Uppsala Centre for Digital Humanities (CDHU), and Medtech Science & Innovation (MTSI). Medical image analysis 3D visualization Haptics in surgery planning Interactive segmentation Digital geometry Biomedical engineering Her recent research focuses on rotation-equivariant neural networks for biomedical image classification, interactive segmentation tools for cranio-maxillofacial surgery planning, and precision evaluation of intraoral scanning technologies. Publications since 2023 demonstrate continued work on 3D imaging protocols for implant dentistry and surgical applications. 2024: Equivariant CNNs for rotation-invariant biomedical imaging 2023: In vivo precision studies of full-arch implant scans 2021: Virtual surgical planning with haptic assistance 2016-2017: Multimodal robotics perception and 3D segmentation tools 2014: Orbital morphology analysis in craniosynostoses 2005-2011: Foundational work in 3D skeletons and fuzzy object measurements
Stefano Calzolari is a Ph.D. candidate in Computer and Systems Engineering at the Department of Control and Computer Engineering (DAUIN), Polytechnic University of Turin. He is also an external lecturer and teaching assistant at DAUIN, contributing to courses such as Game Design and Gamification, Computer Science, and Aerospace Engineering. Education MSc in Cinema and Media Engineering (LM-32), Polytechnic University of Turin (2023) PhD in Computer and Systems Engineering (2023–present) Stefano's research focuses on Embodied Conversational Agents (ECAs) for Extended Reality (AR/VR) applications. His work integrates animation techniques (Motion Matching and Inverse Kinematics), emotion modeling (PAD and Circumplex models), speech technologies (STT/TTS), and AI-based behavior planning (FSM, BT, GOAP, and LLMs). The goal is to enhance user believability through UX questionnaires and interaction data analysis. Research Groups Computer Graphics & Vision Group (CG&VG) Teaching Contributions Master's Degree Course in Game Design and Gamification (2024/25) Bachelor's Degree Course in Computer Science (2025/26 and 2024/25) for Aerospace Engineering
Patrick Rider is a Lecturer and Assistant Department Chair in the Department of Kinesiology at East Carolina University's College of Health and Human Performance. His research focuses on biomechanics, sensorimotor integration, and physical activity patterns. University: East Carolina University Department: Kinesiology Academic Rank: Lecturer Rider's research spans sports biomechanics, virtual reality-based balance assessment, and neuromechanics of fatigue and concussion. He investigates how training history affects joint mechanics, ligament properties in athletes, and the role of visual attention in sports performance. His recent publications highlight advancements in EMG modeling, physical activity dynamics, and high-intensity weightlifting biomechanics. Themes include neural signatures of fatigue, kinematic adaptations in distracted movements, and ligament stiffness responses. East Carolina Alumni Association Outstanding Teaching Award Finalist, 2016 Robert L. Jones Teaching Award Finalist, 2016 Rider has secured grants from the National Science Foundation (NSF) and Office of Naval Research for biomechanical studies. His service includes leadership roles in the American Society of Biomechanics and National Biomechanics Day presentations.
Dr. Bipin Indurkhya is a Professor at the Jagiellonian University 's Department of Cognitive Science within the Faculty of Philosophy. With a PhD in Computer Science, he has lectured globally and leads research projects in social robotics, affective computing, and creative interaction design. Master of Science in Electronic Engineering (Philips International Institute, 1981) PhD in Computer Science (University of Massachusetts, 1985) His research focuses on: Social Robotics - child-robot interaction, elderly care, educational applications, and ethical considerations Multimodal Interaction - combining visual, auditory, and haptic modalities for enhanced user experience UX Design - participatory and co-design methodologies for technology development Affective Computing - haptic-based communication systems Creative Cognition - metaphor theory and its applications in technology design Recent publications show strong emphasis on robot ethics , cross-cultural HRI studies , participatory design , and creative technologies . His work spans educational robotics, elderly care systems, and theoretical investigations into metaphorical cognition. Key scientific contributions include navigation architectures for autonomous robots, calm technology frameworks, and prosody modeling systems for artificial communication.
Maolin Qiu, PhD, is an Associate Research Scientist in the Department of Radiology & Biomedical Imaging at Yale University School of Medicine. Dr. Qiu is a key member of the Bioimaging Sciences division and works within the Magnetic Resonance Research Center (MRRC), where he contributes to cutting-edge neuroimaging and MR physics research. His work spans multiple collaborative projects across Yale's imaging facilities, including the Yale Biomedical Imaging Institute. Dr. Qiu holds a PhD in Artificial Intelligence and Computer Vision from the Institute of Automation (1996) and an MSc in Artificial Intelligence and Autonomous System Control from Beijing Institute of Technology (1993). His educational background in computer vision and AI provides a strong foundation for his current work in medical imaging physics and analysis. Dr. Qiu's research focuses on MR physics and applications, with particular expertise in functional MRI, cerebral blood flow measurement, anesthesia effects on brain function, and cardiac imaging techniques. His work bridges engineering principles with clinical applications, developing novel imaging methods to better understand brain function under various conditions including anesthesia. He has made significant contributions to understanding how anesthetic agents like sevoflurane affect regional cerebral blood flow, BOLD responses, and functional connectivity in the human brain. Analysis of Dr. Qiu's publication record reveals a strong focus on neuroimaging techniques, particularly fMRI methodology development and applications. His work spans multiple disciplines including neuroscience, anesthesiology, cardiology, and sports medicine. A consistent theme throughout his career has been the development and application of advanced MRI techniques to measure physiological parameters like blood flow and oxygenation in various tissues. Collaborates extensively with Todd Constable (5 publications) Works closely with Nallakkandi Rajeevan (5 publications) Partners with D. S. Fahmeed Hyder (3 publications) Collaborates with Michelle Hampson and Xenophon Papademetris (2 publications each) Has published with Albert Sinusas in cardiovascular applications Dr. Qiu's research has resulted in numerous publications spanning from 2004 to 2023, with recent work focusing on cardiac MRI techniques, ketamine effects on brain function, and software tools for improving MRI acquisition. His most recent publications demonstrate continued innovation in MR physics and applications across multiple organ systems. His work on HALO (a real-time head alignment tool) exemplifies his focus on practical solutions to improve MRI data quality through software development.
Roger Mallol Parera is a contracted professor at the Department of Engineering, International Faculty of Commerce and Digital Economy, Universitat Ramon Llull. His research spans metabolomics, biomedical data analysis, and educational innovation, with a focus on connecting biological insights to clinical outcomes. Research Interests: Metabolomics (NMR spectroscopy, lipoprotein profiling), software platforms for data integration, empathy in social robotics, and pedagogical strategies for student engagement. Recent article trends include metabolomic disease biomarkers (METCOVID cohort), cloud-based bioinformatics tools (CloMet), and empathy-driven robotics interfaces. He has collaborated on environmental soundscapes (Sons al Balcó) and digital health projects. Additional Activities: Principal investigator for CLOMET (bioinformatics workflows) and co-investigator for multidisciplinary projects involving environmental research and social robotics.
Dr. Michael Dietz is a Researcher at the Chair of Human-Centered Artificial Intelligence ( University of Augsburg , Faculty of Applied Informatics, Institute of Informatics). His work focuses on Human-Computer Interaction , Mobile Assistive Systems , and Signal Processing with Machine Learning applications. Key research trends include: Development of mobile frameworks for real-time affective feedback (SSJ Framework, SenseEmotion) Augmented reality applications for public spaces and ambient media Privacy-preserving machine learning on mobile devices Physiological signal analysis for stress detection in older adults Eye-tracking innovations for visual search detection Explainable AI techniques in facial expression recognition Projects: EmmA (Emotional mobile Avatar) Glassistant (Smart Glasses for MCI patients) SenseEmotion (Multisensorial emotion recognition) SSJ Framework (Social Signal Processing)
Naser Al Madi is an Assistant Professor of Computer Science at Colby College, where he teaches core courses including Data Structures and Algorithms (CS231) and Software Engineering (CS321). His research integrates eye tracking with software engineering to enhance source code comprehension through analysis of developer behavior and eye movement patterns during software development. His educational background includes a PhD from Kent State University (2020), followed by a visiting research scholar position at Harvard University's School of Engineering and Applied Science and Schepens Eye Research Institute in 2023. Prior to joining Colby, he began his teaching career at Hamilton College where he taught Operating Systems and Wearable Technology courses. PhD, Kent State University, 2020 Visiting Research Scholar, Harvard University, 2023 Began teaching career at Hamilton College Dr. Al Madi's research focuses on the intersection of eye tracking technology and software engineering, particularly examining how developers comprehend source code through eye movement analysis. His work extends to Human-Computer Interaction applications in clinical rehabilitation settings and the impact of AI tools like GitHub Copilot on code readability and developer workflows. He maintains an active research blog discussing cognitive aspects of programming and regularly collaborates with undergraduate students on research projects. His recent publications analyze lexical similarity in identifier names, the readability of AI-generated code, and longitudinal eye tracking studies of developers progressing from novice to expert levels. These works collectively explore how cognitive processes affect software development practices and how tools can be designed to better support developer cognition. Dr. Al Madi is deeply committed to inclusive computer science education, advocating that 'anyone can become a computer scientist if they work hard' regardless of background. He actively mentors undergraduate researchers, emphasizing the importance of diversity in technology development to prevent exclusionary design patterns. His teaching philosophy integrates modern software engineering practices with critical analysis of AI tools, requiring students to understand and verify all AI-generated code rather than using it uncritically. Based in the Davis Science Center at Colby College, he maintains an active presence in the software engineering research community, serving on program committees for major conferences including ASE and FSE. His blog features practical career advice for students, including guidance on resume building, internship applications, and navigating the tech industry.
