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دانشیار
Marc Geilen is an Associate Professor at the Electronic Systems group of Eindhoven University of Technology (TU/e) . He leads the Model-Based Design Lab within the CompSOC Lab and High Tech Systems Center .
Kazuhiko Tamesue is an Associate Professor at the Faculty of Science and Engineering , Waseda University , with a focus on Terahertz Communication , Artificial Intelligence , and IoT Network Security . His academic journey spans academia and industry, including long-term roles at Panasonic Corporation (1991–2009) and current leadership in advanced wireless systems since 2022. Research Areas : Telecommunications, Wireless Hardware, Data Science, Machine Learning, Atmospheric Sensing Key Contributions : Pioneering 300GHz OFDM transceivers, AI-driven GNSS spoofing detection, and dual-frequency THz radar for cloud physics Projects : NICT-funded terahertz networks (2023–2024), ultra-low-latency systems (2022–2024), and security-enhancing radar technologies His 15 most recent publications (2024–2008) demonstrate expertise in (1) terahertz propagation for NTN/HAPS platforms, (2) machine learning for security (LSTM, GANs), and (3) next-generation IoT protocols (LPWAN, distributed ledger). He holds 20+ patents in antenna design, direct-conversion receivers, and power line communication. As an IEEE and IEICE member, he contributes to standards in 5G/6G and EMC.
Dr. Klen Čopič Pucihar serves as Associate Professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He holds multiple leadership roles including Department Chair of Information Sciences and Technologies, Deputy Chair of HICUP Lab, and Study Programme Coordinator for the Doctoral Computer Science program. His research centers on Human-Computer Interaction with particular emphasis on: Augmented, Mixed, and Virtual Reality systems Micro-gesture recognition using radar sensing (e.g., Google Soli) Paper interfaces and augmentation of physical media AR for educational applications, particularly vocabulary learning Addressing the 'dual-view problem' in handheld AR systems Dr. Čopič Pucihar's work is driven by the vision to 'unclog the bottleneck' between humans and digital information. His recent publications (2019-2025) show a strong trajectory from theoretical interaction techniques toward practical educational applications and novel input methods using radar sensing, with consistent output in top venues including CHI, ISS, MobileHCI, and ISMAR. His notable achievements include: Best Paper Award at ACM IUI 2025 Honorable Mentions at ACM EICS 2022 and ACM ISS 2022 Best Poster Award at ISMAR Multiple hackathon victories including at Columbia University As Study Programme Coordinator for Doctoral Computer Science, Dr. Čopič Pucihar mentors graduate students and shapes research directions. His HICUP Lab hosts an international research group focused on making digital interfaces more intuitive and effective for human use through advanced sensing methods and personalized services. HICUP Lab leverages techniques from data mining, machine learning, computer vision, and human perception to develop interfaces that function as extensions of human minds, bodies, and behavior, with the ultimate goal of enabling 'digital augmentation of human abilities to its fullest potential.'
مدرس ارشد
Dr. Matthew Hughes is a Senior Lecturer at Swinburne University of Technology's School of Health Sciences and serves as the National Imaging Facility (NIF) Fellow for MRI research. With a PhD from the University of Newcastle completed in 2010, his research focuses on understanding neural mechanisms underlying cognitive processes in various psychiatric conditions using advanced neuroimaging techniques. His primary research interests include: Neural basis of response inhibition and cognitive control Neuroimaging studies of schizophrenia and bipolar disorder Investigation of neurocognitive abnormalities in anorexia nervosa and hoarding disorder Relationship between brain morphology and cognitive function across diagnostic categories Methodological approaches for reproducible neuroimaging analysis Dr. Hughes employs advanced neuroimaging techniques including 3T MRI, MEG, and proton magnetic resonance spectroscopy in his research. His recent work has explored innovative data analysis approaches for neuroimaging, as evidenced by his contribution to the Neurodesk platform published in Nature Methods, which aims to improve reproducibility in neuroimaging analysis. His research has been supported by multiple competitive grants from the Barbara Dicker Brain Science Foundation, including projects examining EMDR therapy effects in concussion, transcranial direct current stimulation for anorexia nervosa, hearing aid use impact on brain activity, and neurocognitive abnormalities in psychiatric disorders. As a supervisor, Dr. Hughes is available to guide Doctorate (PhD) students and has supervised multiple doctoral projects focusing on various aspects of cognitive neuroscience and psychiatric disorders. His supervision portfolio demonstrates a commitment to training the next generation of researchers in both methodological approaches and clinical applications of neuroscience research.
Carol Stewart is a Professor in the Department of Management and International Business at Southern Connecticut State University. Her primary research and teaching interests include Leadership Studies , Crisis Communication , and Diversity in Organizations . She has published extensively on topics spanning gender differences in leadership, soft skills gaps, and corporate social responsibility. Teaching Interests : Leadership in Organizations Managerial Communication Creativity & Innovation Organizational Behavior Diversity and Inclusion Research Themes : Her work explores organizational leadership in crisis contexts (e.g., pandemic response, sports scandals), soft skills development through initiatives like the Thinkubator Alliance, and gender dynamics in corporate and public sectors. She frequently collaborates with scholars like Angela Wall and Susan Marciniec. Recent Grants : $1,200: "Asyncrhonous Videos for Online and Blended Classes" (SCSU Faculty Development, 2017–Present) $8,000: "Perceived Soft Skills Deficiencies of Emerging Women Leaders" (AAUP, 2023–2024) $2,300: "The Thinkubator Alliance: Closing the Soft Skills GapC" (CSU Grant, 2016–Present) Conference Participation : Stewart presents regularly at the American Society for Competitiveness, Eastern Academy of Management, and International Academy of Business Disciplines, focusing on leadership ethics, soft skills, and organizational innovation.
Niklas Ravaja is a Professor in the Department of Psychology at the University of Helsinki, where he serves as a Supervisor in multiple doctoral programs including Human Behavior, Cognition, Learning, Teaching and Communication, Social Sciences, and Population Health. He is also affiliated with the Helsinki Information Technology Research Institute. His research spans interdisciplinary domains connecting psychology with technology and neuroscience. Professor Ravaja's research focuses on the intersection of psychological processes, physiological responses, and technological interfaces. His work examines how social interactions manifest in physiological arousal, particularly in face-to-face versus mediated communication contexts. He investigates time perception alterations under different emotional and intentional states, exploring how cognitive processes influence temporal experience. His research on virtual reality environments examines emotional responses during intergroup encounters and the impact of haptic feedback on social interaction. Ravaja's work consistently integrates neuroscience methodologies with social psychology questions, creating innovative approaches to understanding human behavior in technologically mediated environments. Analysis of his recent publications reveals a strong trend toward neuroadaptive interfaces and physiological measurement in social contexts. His work increasingly focuses on comparing in-person versus mediated interactions, particularly examining how video communication alters physiological responses during self-disclosure. There's a clear progression from basic research on emotional responses to applied work on health behavior change through biofeedback applications. The integration of virtual reality with physiological measurement represents a significant methodological innovation across his recent work. Professor Ravaja has secured substantial research funding from the Academy of Finland, currently leading three active projects: Meta (focusing on programmable metasurface networks), EngIne (examining engagement in remote social interactions), and PREventive Care Infrastructure. His previous projects have included investigations of mediated haptic communication during social decision making. These projects demonstrate his ability to secure competitive funding for interdisciplinary research bridging psychology, neuroscience, and technology. His academic activities include extensive peer review work (17 instances documented), conference participation and organization (4 instances), editorial work, and academic visits to institutions including University Rennes 1 Graduate School of Management. He has also contributed to media discussions through interviews with Tietoviikko and Hämeen Sanomat, demonstrating his engagement with public discourse around psychological research.
Antonios Liapis is an Associate Professor at the Institute of Digital Games, University of Malta. He completed his PhD in September 2014 under the supervision of Georgios N. Yannakakis at the IT University of Copenhagen. His academic journey includes an M.Sc. in Information Technology from the same institution and a 5-year Diploma in Electrical and Computer Engineering from the National Technical University of Athens. Dr. Liapis has held various academic positions at the University of Malta: Post-doctoral Researcher (2014-2015), Lecturer (2015-2020), Senior Lecturer (2020-2022), and currently Associate Professor (2022-present). He has served as General Chair for multiple international conferences including FDG (2020), GALA (2019), and EvoMusArt (2018-2019). He is an Associate Editor of the IEEE Transactions on Games and a member of the Games Technical Committee of the IEEE Computational Intelligence Society. His research focuses on Artificial Intelligence as an autonomous creator and as a facilitator of human creativity. Key areas include computationally intelligent tools for game design and computational creators that blend semantics, visuals, sound, plot, and level structure to create various game genres including horror, adventure, shooter, and dungeon crawler games. His work has resulted in over 150 peer-reviewed publications and several research awards. Dr. Liapis has secured multiple research grants from the European Commission, including projects on AI-powered robotic material recovery, virtual reality aided design, and learning science through coding and play. His notable project series "Data Adventures" demonstrates the use of open data from Wikipedia, DBpedia, Wikimedia Commons, and OpenStreetMap to automatically generate adventure games with complete plots, characters, items, and locations. His scientific contributions have been recognized with several awards including Best Paper Awards at major conferences, Best Reviewer Award, and Runner-Up Best Student Paper Award. Dr. Liapis has also co-organized 16 workshops in diverse conferences throughout his career. Research interests include: Artificial Intelligence for creative applications Procedural Content Generation in games Computational Creativity systems Machine Learning for game design Affective Computing in virtual environments Human-AI collaboration in creative processes His recent work shows a strong trend toward integrating Large Language Models with game design, exploring quality diversity algorithms for creative applications, and advancing affect modeling for improved player experience. The research spans computer science, artificial intelligence, game studies, and human-computer interaction, with practical applications in education, entertainment, and design.
استادیار
Dr. Wenhao Yang is an Assistant Professor in the Department of Industrial and Systems Engineering at Lamar University, specializing in Augmented Reality (AR), Mixed Reality (MR), and Human-Robot Interaction for industrial applications. His work bridges immersive technologies with robotics to solve manufacturing and operational challenges. Education: Ph.D. in Engineering, Rochester Institute of Technology, 2023 M.S. in Mechanical Engineering, The Hong Kong University of Science and Technology, 2019 B.S. in Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, China, 2018 Dr. Yang's research pioneers AR/MR system design for human-robot collaboration , with breakthroughs in telepresence interfaces , cybersecurity for gesture-based interactions , and registration accuracy . His projects—like AR-assisted assembly demonstration systems and mobile manipulators for hazardous environments—emphasize cognition-aware design to reduce user cognitive load while improving task efficiency. Key innovations include 97.03% accurate gesture recognition for password security analysis and global correction methods for video see-through AR misregistration. His 9 recent publications (2021-2025) reveal a cohesive trajectory: evolving from foundational AR-robot programming frameworks (2021) to advanced cybersecurity and assembly demonstration systems (2024-2025), consistently targeting real-world industrial implementation with rigorous evaluation via user studies and benchmark testing. Teaching: Courses include Collaborative Robotics, AI/VR for Industrial Engineering, and Computer Applications, integrating hands-on AR development with industrial case studies. Active Research: Current projects focus on next-generation MR headsets (2024) and telepresence manipulators, with historical work spanning AR maintenance systems, depth map completion, and telerobotic fitness instruction.
Ali Saraa is a Visiting Lecturer and Postgraduate Student at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science, Institute of Artificial Intelligence and Digital Sciences, and the Research and Educational Laboratory of Big Data Analysis Methods. She began her work at HSE in 2021 and is currently in her 3rd year of postgraduate studies. Her educational background includes a Master's degree in Mechatronics and Robotics from Moscow State Technological University "Stankin" (2021) and a Bachelor's degree in Electromechanical Engineering from Tishreen University (2018). Dr. Saraa's research focuses on machine learning , deep learning , and generative adversarial networks , with applications spanning physics instrumentation, electrical engineering, safety monitoring, and educational technology. Her work on personalized adaptive learning systems involves developing methods and algorithms for building personal learning trajectories, from Bayesian Knowledge Tracing (BKT) up to modern machine learning approaches. She conducts detailed analysis of current implementations of methods and algorithms in various Personalized Adaptive Learning Systems (PALSs), examining statements, input data, results, ideas, solutions, software implementation details, efficiency, and adoption. Her recent publications demonstrate a strong trend toward applying deep learning techniques to solve practical problems across multiple scientific and engineering domains. She has made significant contributions in fault detection for electrical systems, calorimeter response correction in particle physics, safety monitoring through PPE detection, and video stream processing for robotic systems. Letter of gratitude from the Senior Director for Research and Development at HSE (August 2024) As a Postgraduate Student, Ali Saraa is working on her dissertation titled "Efficient parameterizations for training and retraining generative adversarial networks in the image and audio domain" under the supervision of Denis Aleksandrovich Derkach. She has co-authored multiple publications, contributed to research projects at the Institute for Information Transmission Problems (IITP RAS), and holds two patents related to AI applications in industrial settings. Dr. Saraa is affiliated with the Research and Educational Laboratory of Big Data Analysis Methods within the Institute of Artificial Intelligence and Digital Sciences at HSE. Her work bridges theoretical machine learning research with practical applications in physics, electrical engineering, robotics, and educational technology, demonstrating the interdisciplinary nature of modern AI research.
Prof. Dr. Thomas Kopinski is a Professor at the Faculty of Engineering and Economics, South Westphalia University of Applied Sciences in Meschede, Germany. He leads the AI Safety and Collective Intelligence Lab, focusing on cutting-edge research in machine learning applications for industrial and automotive systems. His work bridges academic research and industry collaborations, notably with BMW AG. Research Focus: His team explores: Deep learning architectures for real-time gesture recognition and automotive HMI AI safety protocols and collective intelligence frameworks Industrial applications including predictive maintenance and anomaly detection 3D programming and sensor fusion techniques Team & Students: Current advisees include PhD candidates working on: Bayesian deep learning for predictive maintenance (Felix Neubürger) Generative models for image synthesis (Yasser Saeid) Object recognition in crash test videos (Daniel Gierse) Key Projects: Actively directs WiTraPres and Core Transformer initiatives, with upcoming R&D in AI Safety launching in 2025. Industrial collaborations focus on automotive safety systems and manufacturing optimization.
پژوهشگر ارشد
Zhang Fangyi is a research fellow at Queensland University of Technology's School of Electrical Engineering and Robotics, specializing in robotics, computer vision, and machine learning. With a PhD completed in 2018 titled 'Learning real-world visuo-motor policies from simulation,' Zhang has established a strong research trajectory focusing on bridging the gap between simulation and real-world robotics applications. Zhang's research interests center around robotic perception and manipulation, with particular expertise in sim-to-real transfer techniques, tactile sensing systems, and graph neural networks. Their work spans multiple domains including robotic grasping, fabric manipulation, face clustering algorithms, and graphene-based sensor development. A consistent theme throughout Zhang's research is the development of robust systems that can effectively transition from simulated environments to real-world applications. The publication record shows a clear evolution from foundational work in sim-to-real transfer (2015-2019) toward more specialized applications in tactile sensing and material science (2021-2024). Recent work demonstrates expanding interests into graphene-based sensor technology while maintaining core expertise in robotic perception. Zhang frequently collaborates with leading researchers at QUT including Peter Corke, with whom they've published multiple papers on robotic grasping and tactile sensing. Zhang's research has practical applications across multiple domains including assistive robotics, sensor development, and computer vision systems. Their work on laser-induced graphene sensors shows particular promise for next-generation tactile interfaces and wearable technology.
