Amir Asif is a Professor at the Lassonde School of Engineering, York University, and concurrently serves as Vice President, Research and Innovation. His academic leadership roles include Dean of the Gina Cody School of Engineering and Computer Science at Concordia University (2014-2020). He specializes in signal processing, communications, and their applications in healthcare, power grids, and distributed systems. Asif holds a PhD from Carnegie Mellon University and a Harvard certification in executive leadership. Education: PhD, Electrical and Computer Engineering, Carnegie Mellon University (1996) MS, Electrical and Computer Engineering, Carnegie Mellon University (1993) BSc, University of Engineering and Technology Lahore (1990) Harvard Certificate in Leadership for Senior Executives (2018) Research Interests: Asif’s work spans signal processing for medical imaging (e.g., ultrasound elastography), smart grid optimization, and cybersecurity in power systems. His recent publications address hydrogen energy systems, EMG-based gesture recognition, and resilient control frameworks against cyberattacks. Grants & Leadership: He leads NSERC-funded projects on federated learning and resilient algorithms. He chairs the Ontario Council of University Research and serves on TRIUMF Innovations and the Richmond Hill Board of Trade. His grants include SSHRC funding for equity initiatives and NSERC support for distributed signal processing. Teaching & Mentorship: Asif has supervised over a dozen graduate students and taught courses like Digital Communications and Statistical Signal Processing Theory. Notable advisees include Arash Mohammadi (PhD, 2014) and Nick Sajadi (PhD, 2017).
Teresa Cheung is an Adjunct Professor in the Department of Engineering Science at Simon Fraser University’s Faculty of Applied Sciences. Her research focuses on neuroimaging techniques, particularly magnetoencephalography (MEG), and their applications to understanding brain networks in health and disease. She holds a Ph.D. in Physics from SFU (2012) and completed a postdoctoral fellowship at the University of Cambridge (2012–2013). Research interests include: MEG instrumentation and optically pumped magnetometers (OPM) Cortical-cerebellar networks and cerebellar activity localization Neuroimaging of neurological disorders like major depressive disorder and epilepsy Functional and structural connectome analysis across the human lifespan Multimodal integration of MEG, MRI, fMRI, and DTI data Recent work emphasizes the relationship between cardiovascular health, brain aging, and cognitive resilience. Her studies span clinical applications (e.g., depression biomarkers) and technical advancements in neuroimaging systems. Collaborations include multi-site studies on depression and aging cohorts like the Cam-CAN project. Publications highlight innovative methods in MEG system design, neural network dysfunction analysis, and lifespan brain dynamics. Her work bridges engineering, neuroscience, and clinical research to advance non-invasive brain imaging and neurophysiological understanding.
Paul-Eric DOSSOU is a Researcher at ICAM’s Grand Paris Sud campus, specializing in Societal and Technological Transitions of Companies. His work focuses on Industry 5.0, decision-aided systems, logistics optimization, and digital twin applications. He leads projects like Plateforme Life, Urban Logistics, and Healthcare 4.0, aiming to enhance SME efficiency through sustainable digital transformation. Expertise includes AI-driven supply chain management, cybersecurity for legacy systems, and robotic solutions for archaeology. He collaborates with industry partners to bridge theoretical research and practical applications, emphasizing human-centric automation and environmental sustainability. Contact: paul-eric.dossou@icam.fr | Mobile: +33 6 17 81 33 43 Research contributions span over 30 peer-reviewed articles since 2003, addressing topics from energy audits in the nautical industry to multi-agent systems in supply chain optimization.
Brad Campbell is an Associate Professor in the Department of Computer Science and Electrical and Computer Engineering at the University of Virginia, where he is a member of the Link Lab, a cross-disciplinary research group focused on cyber-physical systems. His research centers on designing and building scalable, effective, and unobtrusive embedded systems for the Internet of Things, with applications in smart buildings, smart cities, and personal health. His work spans hardware design, networking, and cloud infrastructure, with a strong emphasis on energy-harvesting systems, low-power wireless communication, and resilient embedded operating systems. He has led projects such as the Living Link Lab, a heavily instrumented smart building testbed, and has developed open-source platforms for self-powered sensing and IoT ecosystems. His recent publications reflect a strong trend toward privacy-preserving federated learning, contactless occupancy sensing using WiFi and light, decentralized edge computing, and sustainable IoT systems. These works are published in top venues including SenSys, BuildSys, MobiCom, and IPSN, indicating a high impact in the systems and networking community. NSF CAREER Award (2022) Best Paper Award at DFHS’19 Multiple graduate fellowships and teaching awards for his students UVA Engineering Endowed Graduate Fellowships Link Lab Seminar Award CPS Rising Star recognition Brad Campbell has advised numerous PhD and master’s students, many of whom have gone on to academic and industry roles. He has secured significant research funding, including from the NSF, and has contributed to curriculum development in cyber-physical systems. He is actively involved in teaching courses on computer networking, IoT, and operating systems, and has co-taught wireless IoT courses across multiple institutions. His lab focuses on real-world deployment of IoT systems, emphasizing scalability, fault tolerance, and long-term sustainability. He continues to push the boundaries of what embedded systems can achieve in everyday environments, from homes to cities.
Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.
Arben Merkoçi is an ICREA Research Professor and leader of the NanoBioelectronics and Biosensors Group at the Catalan Institute of Nanoscience and Nanotechnology (ICN2). He holds a PhD in ion-selective electrodes from the University of Tirana (Albania) and has held research positions at institutions including the Polytechnic University of Budapest, University of Ioannina, and New Mexico State University. His research focuses on integrating biological molecules with micro/nanostructures to design advanced biosensors, with applications in healthcare and environmental monitoring. Education: PhD in Analytical Chemistry (University of Tirana, 1992) Roles: Co-Editor-in-Chief of Biosensors and Bioelectronics , member of the Academy of Sciences of Albania Research interests include nanomaterial-based biosensors (e.g., graphene, MXenes, quantum dots), point-of-care diagnostics, and sensor fabrication technologies. He has pioneered innovations in inkjet-printed sensors, wearable devices, and CRISPR-integrated biosensing. His group collaborates globally to advance nanobiosensor applications in clinical and environmental settings. Over 350 publications (H-index 91) and 40 supervised PhD theses highlight his contributions. He co-founded GraphenicaLab (graphene patterning) and PaperDrop (clinical diagnostics). Active in grant acquisition and policy, he shaped Spain’s first nanoscience undergraduate program at the Universitat Autònoma de Barcelona.
Stéphane Doncieux is a University Professor in Computer Science at Sorbonne University, where he is affiliated with the Institute of Intelligent Systems and Robotics (ISIR), a joint research laboratory with CNRS. Since January 2024, he has served as Director of ISIR, following a term as Deputy Director from 2019 to 2023. He leads the ASIMOV research team and is based at the Pierre and Marie Curie Campus in Paris. His primary research interests lie in cognitive and developmental robotics, with a strong focus on open-ended learning, evolutionary algorithms, and adaptive systems. He investigates how robots can autonomously learn diverse skills through mechanisms such as novelty search, quality-diversity optimization, and intrinsic motivation. His work bridges theoretical foundations in artificial life and practical applications in robotic manipulation, perception, and control. The recent publications highlight a consistent trend in advancing robotic learning under sparse rewards and in open-ended environments. Key themes include quality-diversity optimization for grasping, state representation learning, sim-to-real transfer, and the development of behavioral repertoires. These works are published in high-impact journals such as IEEE Transactions on Robotics, Evolutionary Computation, and Frontiers in Robotics and AI. Coordinator, DREAM FET H2020 project (2015–2018) Principal Investigator, ANR projects on Creative Adaptation by Evolution, Learning Movement Skills, and Grasping with Multimodal Feedback Involved in European initiatives including VeriDREAM and HumanE-AI-Net He has supervised numerous PhD and Master’s students, including Leni Le Goff, Giuseppe Paolo, Alban Laflaquière, and Achkan Salehi, often in collaboration with leading researchers like Olivier Sigaud and Jean-Baptiste Mouret. He teaches computer science and robotics at both undergraduate and graduate levels at Sorbonne University. Doncieux has been instrumental in shaping research directions in evolutionary and developmental robotics, notably through his leadership in the IEEE Task Force on Evo-Devo-Robotics and his editorial contributions. His lab, ASIMOV, fosters interdisciplinary research integrating computer science, neuroscience, and engineering to create more autonomous and intelligent robotic systems.
Wing Ng serves as Alumni Distinguished Professor and Chris C. Kraft Endowed Professor in Virginia Tech's Department of Mechanical Engineering within the College of Engineering. His career spans over four decades with continuous contributions to aerospace thermal systems and fluid dynamics research since joining Virginia Tech in 1984. Dr. Ng's academic foundation includes: Ph.D. in Mechanical Engineering from Massachusetts Institute of Technology (1984) M.S. in Mechanical Engineering from Massachusetts Institute of Technology (1980) B.S. in Mechanical Engineering from Northeastern University (1979) His pioneering research focuses on aeroacoustics of drones and jet engines, where he develops advanced diagnostics for turbine flow measurements and investigates transonic turbine blade aerodynamics. Current work explores aerothermal particle interactions in gas turbines and clean energy applications for wind turbines. His experimental approach bridges fundamental fluid dynamics with practical aerospace engineering solutions, particularly in cooling systems for high-temperature components. Analysis of recent publications (2024-2025) reveals three dominant research thrusts: turbine cooling optimization (film/phantom cooling configurations), particle dynamics in gas paths (impact/rebound mechanics), and novel measurement techniques (strain sensors, multiphase flow diagnostics). These studies consistently target performance enhancement and durability improvement in turbomachinery through experimental validation. Dr. Ng's exceptional contributions are recognized through: Virginia Tech Faculty Entrepreneur Hall of Fame (2017) William E. Wine Award for teaching excellence (2014) Multiple Certificates of Teaching Excellence (1985,1988,2011,2014) Dean's Award for Research Excellence (2013) Consecutive Best Paper Awards from ASME/AIAA (2001-2013) Fellow of ASME (1996) and Associate Fellow of AIAA (1992) As director of the Ng Lab, he maintains active collaborations with industry partners through Techsburg, Inc. (where he serves as Chairman) to translate research into commercial applications. His work on drone aeroacoustics and turbine diagnostics directly informs next-generation propulsion systems while addressing critical challenges in particle ingestion and thermal management.
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Dr. Morten Ibsen serves as an Associate Professor at the University of Southampton's Optoelectronics Research Centre (ORC), a world-leading institution in photonics research. His academic profile demonstrates extensive involvement in cutting-edge optical technologies with significant contributions to fiber optics and laser systems. Dr. Ibsen's research focuses on advanced optical sensing technologies, particularly in fiber Bragg gratings, bi-doped fiber lasers, and optical refractometers. His work spans applications from environmental monitoring (heavy metal detection) to high-speed explosives diagnostics and navigation systems. The research demonstrates exceptional versatility across fundamental photonics and practical engineering applications. His publication record from 2018-2020 reveals consistent high-impact output in top photonics journals, with recurring themes in fiber laser development, optical sensor optimization, and novel measurement techniques. The research shows strong international collaboration patterns with institutions across Europe and Asia. Dr. Ibsen actively supervises PhD candidates including Robin Elliott and Sergei Shevtsov within the ORC's doctoral program. His research projects have attracted substantial funding from major organizations including the Royal Society, EPSRC, and the European Union's FP7 program. As a core member of the Fibre Bragg Gratings and Smart Lasers research groups, he contributes to the ORC's reputation as a global leader in photonics innovation. His experimental work bridges theoretical optics with practical engineering solutions for real-world sensing challenges.
Dr. J. David Frost is the Elizabeth and Bill Higginbotham Professor of Civil Engineering at Georgia Institute of Technology and a Regents' Entrepreneur. He has held academic positions at Purdue University and Georgia Tech, with a focus on geotechnical engineering and disaster response. As founding director of Georgia Tech's Savannah campus and head of the Geosystems Engineering Group, Frost has shaped academic programs and research initiatives. Education: B.A.I and B.A. in Civil Engineering and Mathematics, Trinity College, Dublin (1980) M.S. and Ph.D. in Civil Engineering, Purdue University (1986, 1989) Research Interests span geotechnical engineering, bio-inspired design, and disaster resilience. His work emphasizes digital data collection systems for subsurface hazard assessment, soil-polymeric material interactions, and geotechnical responses to earthquakes, hurricanes, and anthropogenic disasters. Recent projects integrate ant nest geometry, plant root mechanics, and geosynthetic innovations into infrastructure solutions. Scientific Contributions include two U.S. patents for subsurface data systems, leadership in NSF-funded post-disaster reconnaissance missions (e.g., 9/11, Türkiye earthquakes), and co-founding the Geotechnical Extreme Events Reconnaissance (GEER) Association. His articles reflect expertise in bio-inspired geotechnics, machine learning for disaster modeling, and advanced computational simulations. Awards & Recognition: ASCE Huber Civil Engineering Research Prize NSF National Young Investigator Award Georgia Society of Professional Engineers Engineer of the Year in Education Coastal Business & Education Technology Alliance Leadership Innovation Award Professional Engagement includes chairing the Savannah Area GIS board, advising on ASCE Geo-Legislative Committees, and founding a software company serving 350+ global clients. His work bridges academia, policy, and industry innovation.
Professor Sara Bernardini is a leading academic in Artificial Intelligence at the University of Oxford's Department of Computer Science, where she holds a joint appointment as a Tutorial Fellow at Mansfield College. Her research specializes in decision-making for autonomous systems, automated planning, and robotics, with applications in extreme environments like space missions, nuclear decommissioning, and offshore energy. She bridges theoretical AI with real-world challenges through projects funded by Innovate UK, EPSRC, NERC, and the Alan Turing Institute. Her research interests span: Autonomous Systems : Developing agents that support humans in complex cognitive tasks. Automated Planning : Algorithms for goal recognition, pathfinding, and multi-agent coordination. Robotics : Solutions for subterranean exploration, offshore wind farms, and UAV operations. AI Safety : Risk-aware autonomous systems and interpretable decision-making. Bernardini's publications emphasize algorithmic robustness in path planning, multi-agent coordination , and real-world AI deployments . Recent work explores goal legibility in uncertain environments, energy-efficient robotics, and AI education tools. Her 65+ papers in top venues (e.g., AIJ, JAIR, ICAPS) show a trend toward safety-critical applications and human-AI collaboration. Awards & Leadership: ICAPS-2020 Best Paper Honorable Mention Executive Council Member, Association for the Advancement of Artificial Intelligence (AAAI) Program Chair, International Conference on Automated Planning and Scheduling (ICAPS 2024) Associate Editor, Artificial Intelligence Journal She leads interdisciplinary teams for projects like autonomous offshore wind farm maintenance and modular robots for extreme environments. As Principal Scientist at the UK National Oceanography Centre, she advanced marine robotics. She mentors PhD candidates and collaborates globally (e.g., NASA Ames, MIT).
Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.
Christof Lutteroth is a Professor in the Department of Computer Science at the University of Bath and Director of the REal and Virtual Environments Augmentation Labs (REVEAL). His work focuses on Human-Computer Interaction (HCI) with emphasis on eye-gaze interaction and virtual reality (VR), particularly for health, exercise, and learning applications. He leads multiple research projects funded by organizations like EPSRC, The British Academy, and The Royal Society. Research Interests include developing gaze-controlled interfaces, immersive VR systems, and adaptive UI/UX for fitness and cognitive training. He explores affective design tools, emotion recognition in VR exergaming, and biometric data analysis for health applications. Recent Publications highlight advancements in gaze-based text entry, emotion measurement in VR, AI-driven UI development, and cross-European XR innovation networks. His work spans from foundational HCI methodologies to applied projects in rehabilitation and immersive learning. Grants include EPSRC IAA, British Academy, and Royal Society funding for projects like TapGazer, Hyper-immersive XR, and Affective Design Tools for VR. He collaborates with institutions across Europe through the EMIL project. Laboratory : REVEAL Lab at the University of Bath drives research in immersive technologies, motion analysis, and augmentation of human interaction with digital environments.
Dr. Ken Ferens is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. He serves as the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education and directs the Applied Cognitive Intelligence (ACI) Research Group. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE), Chair of the EduManCom Chapter of the IEEE, Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE, and Chair of the Industry, Teaching Assistants, and Student Forums for Engineering Curriculum Review and Improvement. Ph.D. (Computer Engineering), University of Manitoba, 1996 M.Sc. (Computer Engineering), University of Manitoba, 1991 B.Sc. (Electrical Engineering), University of Manitoba, 1989 Dr. Ferens has over 33 years of research experience in computational intelligence, focusing on cognitive machine learning, artificial intelligence, cognitive computational intelligence, chaos theory applications, agent-based models, and various optimization algorithms including simulated annealing, genetic algorithms, artificial neural networks, and particle swarm optimization. His research applies these techniques to develop software and hardware intrusion detection systems for cybersecurity applications. He teaches graduate-level courses on Computer Network Security and Applied Computational Intelligence, providing students with theoretical background and hands-on experience in state-of-the-art security methods. Analysis of Dr. Ferens' recent publications reveals a strong focus on applying cognitive and chaotic computational techniques to cybersecurity challenges, particularly malware detection and network intrusion detection. His work increasingly integrates complexity theory, fractal analysis, and hybrid optimization approaches to enhance security systems' effectiveness. There's a clear progression toward more sophisticated machine learning architectures applied to increasingly complex security scenarios, with growing emphasis on real-world IoT and network security applications. Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2022) Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2015) Best Journal Paper Award for 2013 (Journal of ICT Research and Applications) Best Poster Award at 12th International Conference on e-Health Networking, Application & Services (2010) Best Paper Award at IASTED International Conference on Computer, Electronics, Control, and Communication (1991) Dr. Ferens collaborates with national and international industry partners including the Department of Advanced Information Management, Content Technology Canadian Tire Corporation (CTC), and Magellan Aerospace. His research group has received funding supporting the Cyber-security Research Program, developing practical applications of computational intelligence for security systems. He has supervised numerous graduate students in the Electrical and Computer Engineering department, focusing on research at the intersection of machine learning and cybersecurity. Dr. Ferens leads the Applied Cognitive Intelligence (ACI) Research Group within the Department of Electrical and Computer Engineering, which focuses on applying cognitive, chaotic, and computationally intelligent algorithms to build intrusion detection systems. The group collaborates with industry partners to develop practical security solutions while providing students with hands-on research experience in cutting-edge security technologies. Their work spans both theoretical algorithm development and practical hardware implementation for real-world security applications.
