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Prof. Elisabeth André is a Full Professor of Computer Science at Augsburg University , leading the Chair for Human-Centered Artificial Intelligence. She holds academic roles including Managing Director of the Institute of Computer Science (2004–2006) and serves on numerous national/international committees such as the Bavarian Artificial Intelligence Council and DFG panels. Her research focuses on multimodal interfaces , affective computing , and social robotics , with emphasis on human-centered design principles and ethical AI. Education: 1988: Diploma in Computer Science (Saarland University) 1995: Dr. rer. Nat. (Saarland University) Research Interests: Multimodal analysis (physiological/gaze/speech/gesture), tangible interfaces, technology-enhanced learning, and AI ethics. She has pioneered projects like CALLAS (affective multimedia systems) and CUBE-G (cultural adaptation for agents). Awards: 2021: Gottfried Wilhelm Leibniz Prize (Germany’s highest research honor) 2013: ECCAI Fellow 2010: Member of Leopoldina and Academia Europaea Grants & Leadership: Led EU projects (e.g., METABO, E-Circus), DFG initiatives, and co-chaired major conferences (ICMI, AAMAS). Supervised over 20+ PhD students and 11 ongoing doctoral candidates. Labs/Teams: Leads the Human-Centered AI team at Augsburg, collaborating on projects like FORSocialRobots and TherapAI. Active in interdisciplinary efforts for ethical AI frameworks and educational robotics.

• Multimodal User Interfaces
• Affective Computing
• Social Robotics
• +5 more

Fernando Sánchez-Figueroa is a Full Professor at the University of Extremadura's Department of Computer Systems Engineering and Telematics. He is a co-founder of Homeria Open Solutions, a spin-off engaged in R&D projects under EU frameworks. His research focuses on Software Engineering, Machine Learning, Data Visualization, and Ambient Intelligence. He has authored over 50 scientific articles and led numerous R&D contracts with public and private entities. Key roles include: Academic: Full Professor at University of Extremadura Entrepreneur: Co-founder of Homeria Open Solutions Research: Participation in EU-funded projects and development of AI-driven solutions for healthcare, smart cities, and education Research Interests: Machine Learning applications in healthcare, predictive analytics for education, and sustainable smart city technologies. His work bridges theoretical advancements with practical implementations, such as medical image segmentation using SAM models and cost-efficient UAV systems. Publications: Recent works include decision support systems for employability analysis, zero-shot learning in medical imaging, and recommender systems for education. He emphasizes data-driven approaches and model-driven engineering in software development. Impact: Developed tools like CompareML for preliminary data analysis and LiveSankey for advanced web visualization. His contributions span academia and industry, addressing challenges in healthcare, urban sustainability, and educational technology.

• Software Engineering
• Big Data
• Business Intelligence
• +3 more

Dr. Udayanto Atmojo is a Staff Scientist in the Department of Electrical Engineering and Automation at Aalto University. His research focuses on industrial automation systems, distributed control architectures, and IEC 61499 standard implementation. He holds a doctoral degree in Engineering from the University of Auckland. Research Focus: Distributed control systems using IEC 61499 standard OPC-UA integration for industrial interoperability Cybersecurity in Industry 5.0 environments Digital twin applications in industrial settings His publications demonstrate strong emphasis on industrial automation standards, secure data exchange, and virtual commissioning. Recent work addresses security challenges in human-intensive automated factories and confidential data sharing for life cycle assessments in process industries. Projects and Recognition: Principal investigator for TwinFlow project on distributed control systems (2024-2026) Contributor to CloViC project on cloud virtual commissioning Finalist in World Challenge Finland 2018 competition He develops laboratory test procedures for industrial applications and contributes to open science initiatives including FAIR principles for research software.

• Industrial Automation
• Distributed Control Systems
• OPC-UA Integration
• +3 more

Maria Dolores Blanco Rojas is a Full Professor and Deputy Director of the Systems and Automatic Engineering Department at Universidad Carlos III de Madrid (UC3M). Her research focuses on robotics and biomedical engineering, particularly in the development of soft robotic exoskeletons, shape memory alloy (SMA) actuators, and rehabilitation technologies. She leads the Robotics Lab and has contributed to over 100 peer-reviewed articles. Affiliations : UC3M, Robotics Lab, Systems Engineering and Automation Department Education : Not explicitly stated in text Her research interests include: Soft Robotics : Design of wearable exoskeletons for pediatric and post-stroke patients Materials Science : SMA-based actuators for medical and robotic applications Control Systems : Adaptive control algorithms for rehabilitation devices Biomedical Engineering : Integration of sEMG signals for gesture classification in assistive technologies Recent articles explore topics like hyperparameter optimization for machine learning models, SMA actuator efficiency, and eye-hand coordination assessment systems. Projects include the development of pediatric rehabilitation robots (Discover2Walk) and soft exoskeletons for ankle and wrist mobility. Grants/Projects : SRAR (2024–2027): Soft robotics for ankle rehabilitation STRIDE-UC3M (2022–2024): Pediatric exoskeleton validation Advising : Supervised theses on SMA actuators, soft exoskeletons, and rehabilitation systems Her lab develops novel sensors and actuators, including a silver-coated polyamide sensor and multi-wire SMA actuators for high-displacement applications. Collaborations include Airbus and TechnoFusión facilities.

• Robotics
• Biomedical Engineering
• Rehabilitation Engineering
• +3 more

Bala Balasingam is a Professor at the University of Windsor's Faculty of Engineering, specializing in interdisciplinary research at the intersection of electrical engineering, human factors, and autonomous systems. His work focuses on battery management systems, cognitive load assessment, and the human aspects of automated driving. Collaborating with the Faculty of Human Kinetics, he addresses challenges related to driver distraction and vigilance in autonomous vehicles. Research interests include battery parameter estimation, real-time state-of-charge tracking, and thermal management of lithium-ion batteries. His team employs advanced methods such as electrochemical impedance spectroscopy (EIS), Kalman filtering, and machine learning for battery diagnostics. In human factors, his studies utilize eye-tracking and biometric sensors to evaluate cognitive workload during complex tasks like vehicle takeovers in automated systems. Key contributions include novel approaches to battery internal resistance estimation, optimized charging algorithms, and validation frameworks for battery management systems. His recent work explores the integration of portable devices in automated driving systems and the impact of cognitive load on driver performance. Collaborations span engineering and kinesiology domains, emphasizing practical applications in transportation and energy sectors. Labs/Teams: Leads interdisciplinary projects combining electrical engineering and human kinetics expertise, with a focus on real-world applications in automotive and industrial automation.

• Battery Management Systems
• Autonomous Vehicles
• Human Factors Engineering
• +4 more

Dr. Yara Khaluf is an Assistant Professor in the Information Technology Group at Wageningen University & Research, Department of Social Sciences. She holds a PhD (2014, Paderborn University, cum laude) on robot swarm task allocation, followed by postdoctoral research at Paderborn University (2014–2015) and Ghent University’s IDLab (2015–2021). Her work focuses on computational social science, hybrid human-agent societies, and distributed artificial cognition, leveraging agent-based modeling and systems dynamics for behavior prediction/modulation. She leads European-funded projects like ChronoPilot (EU Horizon2020 FET) and DELICIOS (FWO, 2019–2022). Her research explores interactions between artificial agents and humans, developing cognitive capacities for seamless interaction via social feedback networks. Notable contributions include collective foraging algorithms, time perception modeling, and agent-based simulations for public health interventions. Awards include competitive IGS and DFG fellowships. She collaborates with leading experts in swarm intelligence (Dorigo, Stuetzle), collective decision-making (Hamann, Marshall), and experimental psychology (Johansson, Vatakis). Current projects investigate modulating human time perception and delegation of conflict-of-interest decisions to AI agents. Teaching includes courses on model thinking, agent-based modeling of complex systems, and data science applications in food/consumer science. Her work bridges computational methods with societal challenges, emphasizing scalable solutions for hybrid systems.

• Computational Social Science
• Artificial Intelligence
• Robotics
• +5 more

Theocharis Kyriacou is a Reader in Computer Science at Keele University, School of Computer Science and Mathematics. He holds roles as Director of Education and Programme Director for undergraduate and postgraduate Computer Science programmes since 2018. Educated at the University of Sheffield (BEng, 2000) and University of Plymouth (PhD in Computer Science, 2004), his research focuses on Data Science and Machine Learning applied to healthcare, robotics, education, and sports science. He has led a 3-year Knowledge Transfer Partnership (KTP) with Bentley Motors and supports local SMEs through consultancy. His work spans academic research collaborations across disciplines and organizational roles in curriculum development. Research interests include machine learning applications in cardiology (predicting cardiovascular risks), wearable electronics for neurological conditions, and educational technology for curriculum design. He has published widely in journals like International Journal of Cardiology and BMJ Open Sport and Exercise Medicine , with a focus on interdisciplinary problem-solving. Awards and recognitions are not explicitly listed, but his contributions include impactful collaborations with medical institutions and industry partners. Advising and grants include guiding students in KTP projects and securing funding for robotics and healthcare-related research. He has developed new academic programmes in computer science apprenticeships and cross-school initiatives. His involvement in labs/teams includes collaborations with Keele’s pharmacy, sports science, and medicine departments, as well as international partners.

• Data Science
• Machine Learning
• Robotics
• +4 more

Jonathan W. Hurst is a Professor of Robotics at Oregon State University's College of Engineering, Mechanical, Industrial, and Manufacturing Engineering department. He co-founded the Oregon State University Robotics Institute and serves as CTO and co-founder of Agility Robotics. He holds degrees from Carnegie Mellon University: B.S. in Mechanical Engineering, and M.S./Ph.D. in Robotics. His research focuses on legged locomotion fundamentals, merging machine learning with traditional control methods to achieve advanced robotic mobility. Education: B.S. Mechanical Engineering (Carnegie Mellon), M.S. and Ph.D. Robotics (Carnegie Melllon). Research emphasizes numerical studies, animal data analysis, simulation models, and physical robot prototyping. Key areas include dynamic gaits, passive compliance in movement, and bio-inspired design. His work aims to enable robots to navigate environments like humans, with commercial applications via Agility Robotics. Awards include the 2018 OSU Faculty Innovator Award, Engelbrecht Young Faculty Award (2014), and Popular Mechanics Breakthrough Innovators recognition (2012). He leads the Dynamic Robotics Laboratory and collaborates on projects such as the Cassie robot. Grants and industry partnerships support his research, advancing robotics for economic productivity and quality-of-life improvements. His lab integrates academic and applied research, producing both scholarly publications and commercializable technologies.

• Robotics
• Legged Locomotion
• Biomechanics
• +4 more

Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +7 more

Patrick Dallasega is an Associate Professor in the Department of Industrial Plants at the Faculty of Science and Technology of the Free University of Bolzano (Italy). He holds a PhD from the University of Stuttgart and has been a Visiting Scholar at Chiang Mai University (Thailand) and Worcester Polytechnic Institute (USA). His expertise spans supply chain management, Industry 4.0 integration in SMEs, lean construction methodologies, and sustainable production planning in ETO/MTO environments. He teaches Project Management and Industrial Plants courses in Industrial Mechanical Engineering programs. His research focuses on digital transformation in manufacturing, including smart mobile factories, augmented reality applications for training, and synchronization of production and on-site assembly processes. Collaborative projects like the AR-enhanced industrial training initiative with Memc aim to reduce errors and costs in complex industrial setups. His work emphasizes human-centered technology integration, sustainability, and real-time data utilization for adaptive production strategies. Education Bachelor/Master: Free University of Bolzano (Italy) MSc: Polytechnic University of Turin (Italy) PhD: University of Stuttgart (Germany) Research Interests Professor Dallasega’s research explores the intersection of Industry 4.0 technologies with lean manufacturing principles, particularly in complex Engineer-to-Order (ETO) and Make-to-Order (MTO) sectors. He investigates how digital twin frameworks, augmented reality (AR), and real-time data analytics can enhance supply chain resilience, reduce operational losses, and improve workforce training efficiency. His work also addresses sustainability challenges in mobile and distributed manufacturing systems, emphasizing eco-friendly logistics and smart factory design. Key Projects Recent collaborations include: Development of an AR-based training module to boost procedural knowledge retention in machinery setups Comparative studies on Industry 4.0 adoption in SMEs across Europe and Asia Framework for digital twin-driven quality control in precast manufacturing Grants & Advising No specific grants or student advisees are listed in the provided data. His focus remains on collaborative industry projects and institutional teaching responsibilities. Labs & Teams Involved in cross-disciplinary teams at the Free University of Bolzano, particularly in the NOI Techpark innovation hub. Leads initiatives on smart mobile factories and human-centered robotics applications in manufacturing environments.

• Supply Chain Management
• Industry 4.0
• Lean Construction
• +7 more

Yi-Chi Liao is a postdoc researcher at ETH Zürich under the SIP Lab, funded by the ETH Zürich Postdoc Fellowship Programme. He holds a PhD from Aalto University (supervised by Prof. Antti Oulasvirta) and Master's/Bachelor's degrees from National Taiwan University. His research focuses on computational interaction, human-in-the-loop optimization, and biomechanical simulation. He has contributed to over 14 top-tier publications in venues like CHI, UIST, and TiiS. Education: PhD in Computer Science, Aalto University (Finland) Master's in Computer Science, National Taiwan University Bachelor's in Computer Science, National Taiwan University Research Interests: Advances in HILO frameworks for adaptive systems, human-AI co-design, and biomechanical motion simulation. His work integrates reinforcement learning, Bayesian optimization, and computational modeling to enhance interactive systems. Publications: Over 14 papers in top HCI venues, emphasizing optimization techniques, tactile interfaces, and 3D interaction. Recent work includes meta-Bayesian optimization for wrist-based interactions and real-time target inference via biomechanical simulation. Awards: CHI 2022 Honorable Mention, multiple outstanding review recognitions, and the ETH Postdoc Fellowship. He serves on program committees for CHI, UIST, and TEI. Teaching: Delivered lectures on Bayesian statistics, deep learning, and computational design at Aalto and NTU. Served as a teaching assistant for HCI and computer architecture courses. Labs: Active in the Human-Computer Interaction Lab (Saarland University), SIP Lab (ETH Zürich), and collaborations with Meta Reality Labs.

• Human-Computer Interaction
• Human-in-the-Loop Optimization
• Reinforcement Learning
• +4 more

Dr. Kazem Kazerounian is a Professor of Mechanical Engineering at the University of Connecticut, affiliated with the School of Mechanical, Aerospace, and Manufacturing Engineering. He holds B.S., M.S., and Ph.D. degrees in Mechanical Engineering from the University of Illinois at Chicago (1980–1984). His expertise spans analytical and computational kinematics/dynamics applied to bio-nano machines, robotics, gear systems, and product design with health/ergonomics focus. He is a Fellow of ASME and recipient of the ASME Lifetime Achievement Award (2006) and George Wood Award (1997). Research interests include protein-based nano-scale devices, gear system dynamics, robotic manipulation, and creativity in engineering education. He consults for OSIM International (Singapore), Pratt & Whitney, and the Singapore Productivity & Standards Board. Editorial roles include ASME Applied Mechanics Review, Journal of Medical Devices, and Journal of Mechanisms and Machine Theory. Awards: ASME Lifetime Achievement Award (2006), George Wood Award (1997), ABB Outstanding Faculty Award (1997) Consulting: OSIM International, Pratt & Whitney, Singapore Productivity & Standards Board His work bridges mechanical engineering with bio-nano systems, emphasizing interdisciplinary applications in medicine and robotics. Over 150 publications span topics like nanorobotics, orthosis design, and computational protein folding models.

• Nano-Mechanical Systems
• Robotics
• Gear Systems Dynamics
• +4 more

Vahid Behzadan is an Assistant Professor in Data Science and Computer Science at the University of New Haven's Tagliatela College of Engineering. He leads the SAIL Lab, focusing on AI safety and security, particularly in autonomous systems like driverless cars and smart cities. His work addresses adversarial attacks on machine learning and reinforcement learning, with applications in cybersecurity and healthcare. Behzadan has held prior positions at Kansas State University, University of Nevada Reno, and University of Birmingham, UK. He holds a Ph.D. in Computer Science and an M.S. from the University of Nevada Reno, and a B.Eng. from the University of Birmingham. His research spans AI ethics, cybersecurity, and complex systems. Behzadan advises the UNH hacking team and actively participates in policy initiatives, including Connecticut's AI Working Group and the Connecticut AI Alliance. He has contributed to over 30 peer-reviewed articles and frequently engages in media discussions on topics like AI safety, facial recognition, and cybersecurity threats. Key research areas include adversarial machine learning, AI forensics, and ethical AI design. His work bridges theoretical advancements with real-world applications in transportation, healthcare, and national security. Behzadan collaborates with organizations such as the Transportation Research Laboratory (TRL) and Open Web Application Security Project (OWASP).

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Professor Tony Jan leads the Centre for Artificial Intelligence Research and Optimisation (AIRO) at Torrens University Australia's Design and Creative Technology school. He holds a PhD in Computing Science from the University of Technology Sydney (2004) and a Bachelor of Engineering from the University of Western Australia (1999). His research focuses on federated machine learning for IoT security, ensembled machine learning for real-time applications, cognitive machines for human-centric computing, and smart sensor networks for healthcare and security. He has secured ARC grants and industry partnerships with NVIDIA, IBM, and Microsoft. Awards include the 2024 SEI Global Academic Excellence Award and the 2023 Torrens University Excellence Award. Research collaborations span global partners, with contributions to UN Sustainable Development Goals in education and industry. His work bridges academia and industry, expanding AI program enrollments by 2,000+ students and enhancing student satisfaction by 15%. He advises PhD students on topics like IIoT cybersecurity and smart cities, and has produced over 97 publications since 1999. Education: PhD (UTS, 2004), BEng (UWA, 1999) Research Themes: AI for Industry 5.0, Cybersecurity, Smart Cities, Healthcare Technology Key Partnerships: NVIDIA, CIMIC, Palo Alto Networks Recent Projects: Federated learning for health IoT, drone vision intelligence, ransomware detection His work emphasizes ethical AI adoption in design and healthcare, with publications exploring AI ethics, generative AI applications, and sustainable technology integration.

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Christophe Charrier is a Full Professor in Forensics and AI at Université de Caen Normandie, affiliated with GREYC UMR CNRS 6072 and IUT Grand Ouest Normandie's Multimedia and Internet Department (Dept. MMI). He obtained his PhD in Computer Science from Université Jean Monnet (Saint-Etienne) in 1998, followed by an HDR (Habilitation à Diriger des Recherches) in 2011 from Université de Caen Normandie. His academic journey includes roles as a Postdoctoral Researcher at Université Laval (1998-2001), Associate Professor at IUT Saint-Lô (2001), and Visiting Scholar/Professor positions at University of Texas at Austin (2008) and University of Sherbrooke (2009-2011). His research focuses on Digital Image and Video Forensics (e.g., deepfake detection), Image/Video Quality Assessment , Computational Vision , and Biometrics (fingerprint quality, template update, presentation attack detection). He leads the SAFE research group since 2016 and collaborates with the E-payment & Biometrics team at GREYC. His work integrates machine learning for quality metrics, biometric system evaluation, and forensic analysis. Recent publications highlight advancements in deepfake detection , 3D mesh quality assessment , and biometric security . Articles span journals like Intelligent Service Robotics (2024), IEEE Access (2024), and conferences such as CORESA (2024) and Cyberworlds (2023-2024). His studies on fingerprint systems, behavioral biometrics, and environmental impacts on data quality underscore his interdisciplinary approach. Scientific Awards : Best PhD Paper Award (ASONAM 2022) Best Full Paper Award (CW2022) He has mentored 14 PhD students since 2003, including notable alumni like Xinwei Liu (Zhejiang Wanli University) and Antoine Cabana (ALTEN, Toulouse). His projects span biometric certification, latent space manipulation, and 3D mesh evaluation, often in collaboration with institutions in Canada, Norway, and Morocco.

• Digital Image Forensics
• Video Forensics
• Biometrics
• +7 more