Emma Colamarino is a Researcher at the Department of Computer, Control and Management Engineering "Antonio Ruberti" of Sapienza University of Rome. She holds an M.Sc. in Biomedical Engineering (2014, cum laude) and a Ph.D. in Bioengineering (2019). Since 2015, she has been a research collaborator at the Neuroelectrical Imaging and Brain-Computer Interfaces Lab of IRCCS Fondazione Santa Lucia in Rome and served as a Visiting Ph.D. student at Imperial College London (2018). From 2019 to March 2023, she was a Post-Doctoral Fellow at Sapienza University. Her research focuses on Advanced electroencephalographic (EEG) and electromyographic (EMG) signal processing Brain-Computer Interface (BCI) protocols for cerebral function recovery Machine learning in neurorehabilitation Hybrid BCIs integrating cortico-muscular networks Recent publications address stroke rehabilitation, BCI design, spectral graph theory, and EMG-EEG integration. Her work spans biomedical data analysis, neuroengineering, and rehabilitation technology validation. Scientific awards include multiple grants from Sapienza University and the Italian Ministry of Health, a Student Award at the 7th International BCI Meeting (2018), and recognition as a Subject Expert (2019). She has supervised/co-supervised 18 MD theses across Biomedical, Management, and Robotics Engineering disciplines.
Melanie Baljko is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering. She directs the Practices in Enabling Technologies (PiET) Lab and participates in graduate programs in Science & Technology Studies, Critical Disability Studies, Digital Media, and Interdisciplinary Studies. Research Focus: Human-centered computing, participatory design, maker methods, assistive technology, augmentative communication, and computer-supported speech therapy Teaching: Graduate courses in critical technical practice and human-computer interaction; undergraduate courses in user interfaces, human-computer interaction, and computer science projects Publications highlight her work in accessible technology for Parkinson's patients, DIY assistive technologies in Kenya, and participatory design frameworks. She collaborates with the University Health Network – Toronto Rehabilitation Institute as an Affiliate Scientist. Key Themes: Accessibility, equity in technical design, and empowering marginalized communities through technology. Recent work examines transit app accessibility, disability inclusion in clinical education, and mixed reality teaching tools.
WANG, Yushi is currently a Junior Researcher (Assistant Professor) at the Future Robotics Organization of Waseda University , with prior roles in the Faculty of Science and Engineering (2018–2021). His research focuses on robotics, tactile sensing, and actuator design. Education: Ph.D. in Science and Engineering from Waseda University (2015–2018). Research interests include Humanoid Robotics , Force/Torque Control , and Soft Robotics , particularly for applications in tactile sensing and safety mechanisms . Recent work explores Permanent Magnet Elastomer (PME)-based sensors and Series Clutch Actuators , enabling safer human-robot interactions and adaptive compliance. His publications span conferences like IROS , AIM , and SII , addressing challenges in 3-axis force measurement , collision safety , and material testing . He has taught courses such as 理工学基礎実験 and メカニカルエンジニアリングラボA (2018–2021). Professional memberships include IEEE , IEEE WIE , and the Japan Robotics Society . His work also involves patents for haptic interfaces and torque limiters , with grants like the 若手研究 (Young Researcher Grant) (2021–2023).
Darko Etinger is an Associate Professor and currently serves as the Dean of the Faculty of Informatics at Juraj Dobrila University of Pula in Croatia. His academic career spans over two decades with significant contributions to the fields of information systems, educational technology, and artificial intelligence. He teaches undergraduate courses including Artificial Intelligence, Business Information Systems, Business Process Management, ICT Fundamentals, Information Systems, Introduction to Artificial Intelligence, and Multimedia Systems. At the graduate level, he teaches Development of IT Solutions, IT Management, Modelling and Simulation, and Project Management. He also supervises doctoral research in Management of Information Technologies in Education. Dr. Etinger's research interests span several key areas in computer science and education technology. He has made significant contributions to understanding how information and communication technologies can support children with special educational needs, as evidenced by his 2024 and 2025 books on the topic. His work also focuses on business process management, educational data mining, and the application of artificial intelligence in educational contexts. His 2024 book 'Introduction to R and RStudio' demonstrates his commitment to data science education. Analysis of his recent publications shows a strong focus on practical applications of technology in education and business. His work spans educational robotics, learning management systems analysis, business process modeling, and the application of large language models in healthcare. He has a particular interest in how technology can be made accessible and beneficial for diverse learner populations, including those with special needs. His research often takes a human-centered approach, examining not just the technology itself but how it's adopted and used by end users. His 2025 bibliometric analysis of metaverse security demonstrates his ability to tackle emerging technological challenges. Associate Professor at Faculty of Informatics, Juraj Dobrila University of Pula Current Dean of Faculty of Informatics Author of multiple publications on educational technology and information systems Supervisor for numerous graduate theses on educational technology topics Active participant in EDIH Adria project as evidenced by 2025 publications Researcher in educational robotics implementation in Croatian schools Dr. Etinger has advised numerous students completing their theses, with a focus on educational technology applications. His research has been published in various international conferences and journals including IEEE Engineering Management Review, Procedia Computer Science, and System Dynamics Review. His current research appears to be heavily focused on the EDIH Adria project, which is a European Digital Innovation Hub initiative focusing on technology transfer and business innovation. He maintains an active research program with publications spanning from 2003 to the present, demonstrating sustained scholarly contribution to his fields of expertise.
Surjo R. Soekadar is the Einstein Professor of Clinical Neurotechnology at Charité – University Medicine Berlin. He leads the Clinical Neurotechnology Laboratory , which focuses on developing noninvasive neurotechnologies for treating neurological and psychiatric disorders through closed-loop brain stimulation and advanced brain-machine interfaces (BCI/BMI). His work integrates real-time EEG/MEG monitoring with electromagnetic stimulation to modulate pathological brain oscillations and enhance neuroplasticity in conditions like stroke, spinal cord injury, and psychiatric disorders. Education : Studied medicine in Mainz, Heidelberg, and Baltimore Clinical Training : Residency in Psychiatry and Psychotherapy at University of Tübingen Academic Journey : 2008-2011 Research Fellow at NINDS (USA); 2017 Venia Legendi at University of Tübingen; 2018 First Professor of Clinical Neurotechnology in Germany His research interests span: • Closed-loop neurostimulation combining real-time brain state monitoring with targeted intervention • Next-generation BCI using optically pumped magnetometers (OPM) for mobile MEG recordings • Neurorehabilitation through exoskeleton control and sensory feedback • Neurophysiological modeling of entropy measures and phase flows Recent publications highlight: • Adaptive deep brain stimulation protocols • Real-time phase-sensitive tACS applications • OPM-based BCI innovations • Stroke recovery mechanisms through corticospinal tract analysis Scientific recognition includes: International BCI Research Award BIOMAG Award NARSAD Young Investigator Award Funded by the European Research Council (ERC) , his lab trains doctoral students like David Haslacher (EEG/MEG integration), Khaled Nasr (multicoil TMS optimization), and Annalisa Colucci (entropy-driven BCI development). The team also explores quantum AI applications in clinical decision-making and bidirectional BCI systems using OPM and tES.
R. Jayakrishnan , a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering , University of California, Irvine, is a leading researcher in transportation systems engineering. Ph.D., University of Texas, Austin, Civil Engineering, 1992 M.S., University of Texas, Austin, Civil Engineering, 1987 B.S., Indian Institute of Technology, Madras, India, 1985 His research focuses on dynamic traffic assignment , urban traffic simulation , and real-time information systems to improve congested traffic corridors. He is developing advanced dynamic simulation-assignment models for urban traffic networks. Recent publications highlight his contributions to: Crowdsourced delivery optimization using decomposition heuristics Eco-driving algorithms with V2I communication Multi-furniture placement applications via augmented reality Subscription mobility services cost-benefit analysis Agent-based lane-changing coordination systems These works demonstrate his interdisciplinary approach combining transportation engineering, optimization algorithms, and emerging technologies like AR and connected vehicles.
Prof. Dr.-Ing. Jörg Müssig serves as a Professor at Bremen University of Applied Sciences within Faculty 5 (Department 2), focusing on sustainable composite materials development. His research bridges engineering and environmental science through innovation in natural fiber applications for industrial use. His primary research domains encompass natural fiber composites, biobased materials, and sustainable material systems, with specialized expertise in flax, hemp, and nettle fiber reinforcement. He investigates mechanical properties, interfacial adhesion mechanisms, flame retardancy solutions, and processing techniques like injection molding and filament winding, emphasizing sustainability metrics and biomimetic design principles. Analysis of his 2024-2025 publications reveals dominant themes in natural fiber composite optimization, particularly regenerated cellulose systems and coupling agent-free interfaces. Emerging trends include consumer perception studies of biobased materials and integration of ecological parameters into industrial design processes, reflecting expanding interdisciplinary approaches. Prof. Müssig leads extensive grant-funded projects including edible mushroom mycelium composites (2024-2026), sulfur-based flame retardants (2024-2026), natural fiber sector market analysis across Europe (2024-2025), and marine durability studies (2024-2025), demonstrating sustained research leadership with significant industry and cross-institutional collaborations. His work operates within a robust research ecosystem at Bremen University of Applied Sciences, where his project portfolio indicates leadership of a specialized team focused on sustainable material innovation, though specific lab infrastructure details remain unmentioned in source materials.
Gabriele Bavota is an Associate Professor at the Software Institute of Università della Svizzera Italiana (USI) in Lugano, Switzerland. He leads the SEART (Software Engineering Advanced Research Team) group and serves as Principal Investigator for the DEVINTA ERC starting grant focused on developer intelligence through mining software artifacts. Dr. Bavota's research spans Software Quality, Empirical Software Engineering, and Mining Software Repositories. His work has evolved from foundational studies on code smells and technical debt to cutting-edge research at the intersection of artificial intelligence and software development. He has made significant contributions to understanding API usage patterns, software quality metrics, and developer behavior through empirical studies of large software repositories. His recent publications reveal a strong focus on AI-assisted software development, with extensive research examining code generation, code summarization, and code review automation using large language models. He has also expanded his research to include quality assurance in game development (detecting game stuttering and low engagement events) and voice user interface testing. His work consistently bridges theoretical insights with practical applications for software developers. ACM SIGSOFT Distinguished Paper Award for API compatibility research (MSR 2019) ACM SIGSOFT Distinguished Paper Award for Hugging Face model documentation study (ICPC 2024) ACM SIGSOFT Distinguished Artifact Award for deep learning fault taxonomy (ICSE 2020) As an active member of the software engineering research community, Dr. Bavota serves on program committees for major conferences including ICSE, ASE, FSE, and MSR. He has held leadership roles such as Program Co-Chair for ICSME 2023 and Vision/Reflection Track Co-Chair for ICSE. His SEART research group develops practical tools like the SEART Data Hub that streamline large-scale source code mining and preprocessing for empirical software engineering research.
Dr. Jayesh Pillai is an Associate Professor at the IDC School of Design, Indian Institute of Technology Bombay, specializing in immersive media design, virtual reality, and augmented reality technologies. His work bridges the gap between design, technology, and storytelling, with a focus on creating meaningful user experiences in virtual environments. His research interests include: Immersive Media Design Virtual Reality & Augmented Reality Visual & Interactive Storytelling Interaction Design Dr. Pillai teaches courses in Design for Virtual Reality, Immersive Media Design, Interaction Design, and Trends in Interactive Technologies at the MDes level, as well as Digital Media Technologies at the BDes level. He has developed educational content through D'Source, including "Virtual Reality: Introduction." His recent publications demonstrate a strong focus on VR narrative techniques, AR educational applications, and social interactions in virtual spaces. His work explores audio-visual cues in 6DoF VR, interactive storytelling through digital game design, and the application of AR in mathematics education and vocational training. Dr. Pillai's research consistently examines how immersive technologies can enhance user experience, learning, and social connection. Dr. Pillai is the creator of "Cinévoqué," a form of responsive VR Cinema where storylines are driven by the viewer's point of interest, and has directed VR films including "Dragonfly" (2018) and "Manhole" (2022), which has been officially selected at multiple international film festivals. He leads the IMXD Lab at IIT Bombay, where his team conducts cutting-edge research in immersive media and interaction design. His work has been presented at major conferences including ACM SIGGRAPH, IEEE VR, and INTERACT.
Shin Yoo is a tenured Full Professor in the School of Computing at Korea Advanced Institute of Science and Technology (KAIST), where he leads the Computational Intelligence for Software Engineering (COINSE) research group. He received his PhD from King's College London in 2009 under the supervision of Prof. Mark Harman. Currently, he serves as the General Chair for ASE 2025, which will be held in Seoul, Korea. Professor Yoo earned his PhD in Computer Science from King's College London (2009), following an MSc in Software Engineering with Distinction from the same institution (2006). His academic journey includes positions as Tenured Associate Professor (2021-2025), Associate Professor (2018-2021), and Assistant Professor (2015-2018) at KAIST, as well as Lecturer and Research Associate positions at University College London and King's College London. His research focuses on the intersection of software engineering and artificial intelligence, particularly in search-based software engineering, software testing, automated debugging, SE4AI (Software Engineering for AI), and AI4SE (AI for Software Engineering). Professor Yoo's work bridges theoretical foundations with practical applications, developing innovative techniques for fault localization, test case generation, and debugging using machine learning and genetic programming approaches. His research has significant implications for improving software reliability and development efficiency in both traditional software systems and AI-powered applications. Professor Yoo's recent publications demonstrate a clear trend toward leveraging large language models and deep learning techniques for software engineering tasks. His work spans fault localization, automated debugging, GUI testing, and program analysis, with increasing focus on the challenges and opportunities presented by AI systems. His research shows a consistent evolution from traditional search-based software engineering to AI/ML-enhanced approaches, reflecting the broader trends in the field. ACM SIGEVO HUMIES Silver Medal (2017) for human competitive application of genetic programming to fault localization research IEEE TCSE Most Influential Paper Award (ICST 2024) for work on mutation-based fault localization Professor Yoo has supervised five PhD students to completion, with his former students now holding positions as assistant professors, post-doctoral researchers, and software engineers at institutions including Kyoungpook National University, Max-Planck Institute Security & Privacy, Università della Svizzera Italiana, Roku Korea, and NUS. He currently serves as an associate editor for the Journal of Empirical Software Engineering and ACM Transactions on Software Engineering and Methodology, and has held significant leadership roles in major software engineering conferences including Program Co-chair for SSBSE (2014), ICST (2018), and ICSE NIER track (2020), General Chair for SSBSE (2022), and Testing & Analysis Area Chair for ICSE (2024). As leader of the Computational Intelligence for Software Engineering (COINSE) group at KAIST, Professor Yoo directs research that combines computational intelligence techniques with software engineering challenges. The group focuses on developing novel approaches to software testing, debugging, and analysis using search-based and AI-driven methods. Their work spans both theoretical foundations and practical implementations, with strong connections to industry challenges and applications.
Dr. Ninghao Liu is an Assistant Professor of Computer Science in the School of Computing at the University of Georgia, part of the Franklin College of Arts & Sciences - Division of Physical & Mathematical Sciences. He holds a Ph.D. in Computer Science from Texas A&M University (2021) and an M.S. in Electrical and Computer Engineering from Georgia Institute of Technology (2015). His research focuses on Explainable AI (XAI), Graph Mining, Model Fairness, Recommender Systems, and Outlier Detection, with notable contributions to foundational AI techniques and their applications in education, healthcare, and environmental sciences. Dr. Liu has secured significant funding, including a three-year NSF grant (2022–2025) for 'Graph-Oriented Usable Interpretation' and a five-year $10 million grant from the U.S. Department of Education (2024–2029) for the GenAI Empowered National Initiative for STEM+C Education. He has also been honored with the Outstanding Paper Award at ICML 2022, Best Paper Award Shortlist at WWW 2019, and other distinctions. His work emphasizes interpretable machine learning, graph neural networks, and addressing algorithmic bias. He collaborates across disciplines, contributing to radiology AI, climate-smart forestry, and pandemic prediction through knowledge-enhanced deep learning. His lab is based at the Boyd Research and Education Center, where he advances research in trustworthy AI systems and data-centric solutions.
Vir V. Phoha is a distinguished Professor in the Department of Electrical Engineering and Computer Science at Syracuse University's College of Engineering and Computer Science. He holds multiple prestigious fellowships including AAAS, AAIA, IEEE, NAI, and SDPS, and was named an ACM Distinguished Scientist in 2008. Dr. Phoha's research spans across cybersecurity, machine learning, and biometrics. His work focuses on cutting across conventional disciplines to unify basic and common concepts, particularly in security (malignant systems, active authentication), machine learning (decision trees, statistical, and evolutionary methods), and computer networks (anomalies, optimization). He develops field-realizable defensive and offensive cyber-based systems using these methodologies. His recent publications reveal a strong focus on continuous authentication, biometric security, fake news detection, and adversarial challenges in cybersecurity. The research shows an evolution from traditional network security to more specialized areas like wearable device security, keystroke dynamics, and gait authentication. Scientific Awards: Fellow of AAAS, AAIA, IEEE, NAI, SDPS ACM Distinguished Scientist (2008) IEEE Computer Society Distinguished Visitor (2024-2026) ACM Distinguished Speaker (2012-2015) IEEE Region 1 Technological Innovation Award (2017) "Highest Impact Award" IEEE CVPR 2018 Workshop on Biometrics Dr. Phoha serves as an associate editor for the ACM journal, ACM Digital Threats: Research and Practice (DTRAP) , and as an associate editor of IEEE Transactions on Computational Social Systems (TCSS) . He has advised numerous students who have gone on to publish significant research in cybersecurity and biometrics. His work has been supported by grants from DARPA and NSF, including the development of the BB-MAS dataset which became one of IEEE DataPort's most popular datasets.
Akhtar Hussain serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Laval University, Quebec. His research centers on AI-driven optimization of power and energy systems, with emphasis on microgrid resilience, distributed energy resource integration, and electric vehicle-grid interactions. He actively contributes to advancing grid reliability through innovative resource allocation and consumer satisfaction frameworks. Ph.D. in Electrical Engineering, Incheon National University, South Korea (2019) M.Sc. in Electrical Engineering, Myongji University, South Korea (2014) B.Sc. in Electrical Engineering, National University of Sciences and Technology, Pakistan (2011) Dr. Hussain's research spans power systems resilience, smart grid technologies, and equitable energy access. His work integrates artificial intelligence with traditional power engineering to address challenges in microgrid operation, electric vehicle integration, and renewable energy management. Key focus areas include developing algorithms for optimal resource utilization, enhancing grid stability during contingencies, and designing frameworks for fair energy distribution in diverse communities. His recent publications (2023-2025) reveal a strong trajectory toward AI-enhanced grid management, with recurring themes of resilience optimization, equity-focused resource allocation, and electric vehicle-grid synergies. The research demonstrates increasing sophistication in handling uncertainty through machine learning while addressing socio-technical dimensions of energy transition. Dr. Hussain currently supervises one Master's student and has guided five Ph.D. candidates to completion. His research is funded by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant ($160,000/year) for the project 'Grid Condition and Resilience-Aware Incentivization and Deployment of Distributed Energy Resources' (2024-2029), supplemented by a Springboard to Discovery award ($40,000) for 2024-2025. As an IEEE member, he collaborates with industry partners on real-world grid modernization initiatives, focusing on practical implementation of resilience strategies through microgrids and mobile energy resources.
Thomas Bjørner is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. He serves as Head of the Media Innovation & Game Research (Me-Ga) unit and co-founded the research network for qualitative methods (since 2007) with 40+ company collaborations. Specializes in qualitative/mixed methods for technology evaluation Teaches PhD courses in advanced qualitative methods EU expert evaluator for research grants His research focuses on gamified learning , VR for social communication , and technology acceptance studies , often addressing UN Sustainable Development Goals. Recent projects include: Audio-only VR for blind gamers Generative AI integration in education Plastic crisis awareness games Smart city implementation barriers Scientific Awards: Serious Game Competition Award (2022) International conference prizes (2020, 2018) With over 121 publications including two textbooks, his work emphasizes applied qualitative methods with improved validity in technology contexts, particularly for youth education and media research.
Piet Desmet is a full professor at KU Leuven's Faculty of Arts, serving as vice rector of KU Leuven, Kulak Kortrijk Campus, and academic director of the Office of the Academic Director, Bruges Campus. He leads multiple research divisions including itec and its Language and Technology subdivision, and is a member of Leuven.AI - KU Leuven Institute for Artificial Intelligence. As general coordinator of itec and academic director of the imec smart education research program, he oversees significant research initiatives spanning multiple campuses. Desmet's research focuses on the intersection of language learning and technology, with particular expertise in Second Language Acquisition and Technology, Computer-assisted Language Learning (including AI-based chatbots), Learning Analytics, and Language Technology and Corpus Linguistics. His work explores intelligent feedback systems, linguistic complexity prediction, adaptive testing, and natural language processing applications for educational contexts. His research spans theoretical linguistic frameworks to practical educational implementations, with a strong emphasis on empirical validation of technological interventions in language learning. Analysis of Desmet's recent publications reveals a strong trajectory toward integrating artificial intelligence with language education, particularly through conversational AI and learning analytics. His work increasingly focuses on chatbot-assisted language learning, adaptive assessment systems powered by large language models, and the application of computational linguistics to educational problems. The publications demonstrate a consistent methodological approach combining theoretical linguistics with empirical educational research, often employing eye-tracking, ERP studies, and learning analytics to evaluate effectiveness. Desmet actively supervises numerous PhD students and leads multiple major research projects including Smart Education at Schools (2025-2026), Enhancing EFL Learners' Speaking Ability through Chatbot-Assisted Dynamic Assessment Powered by LLMs (2024-2028), and the Flanders Ed Tech Hub (2022-2025). His research portfolio demonstrates significant funding success across multiple national and international initiatives focused on educational technology and language learning. As head of itec (an imec research team at KU Leuven), Desmet leads a substantial research ecosystem focused on smart education technologies. The itec team collaborates extensively with Leuven.AI and the KU Leuven Educational Research Institute (LIVO), creating a multidisciplinary environment that bridges computational linguistics, educational psychology, and artificial intelligence. Recent initiatives include the 'AI in Education' online training course and the network for Edtech and Learntech in Flanders.
