Ruwen Qin is an Associate Professor in the Department of Civil Engineering at Stony Brook University. Her research focuses on integrating data analytics, machine learning, and systems engineering into civil infrastructure systems to develop cyber-physical systems and intelligent automation. She applies these technologies to enhance human-AI collaboration, improve transportation safety, and advance smart infrastructure monitoring. Developing AI models for structural health monitoring Applications in worker safety and transportation systems Specializes in computer vision and sensor fusion Her recent work includes deep learning frameworks for drone-assisted inspections, structural component segmentation using weak annotations, and attention-based networks for traffic risk prediction. She also explores explainable AI for crash anticipation and interactive systems for bridge inspectors. Ruwen Qin's research spans interdisciplinary domains, combining civil engineering with AI-driven analytics to address challenges in infrastructure resilience, transportation safety, and human-centric automation systems.
Dong Hyun Kim is a Professor in the Department of Architecture at Sejong University , where he has been since 2006. His academic journey includes a M.Arch from Yale University (2002), an M.S. (1995), and a B.S. (1993) in Architecture from Seoul National University. Education: M.Arch, Yale University (2002) M.S., Seoul National University (1995) B.S., Seoul National University (1993) KIM's research focuses on Design Methodology , Digital Drawing Representation using VR/AR , and Building 3D Printing . His work explores the intersection of Parametric Architecture and Technology for Living , emphasizing innovative fabrication techniques and digital tools in architectural design. Recent publications highlight his expertise in Daylighting Performance Assessment (2024) and Deep Neural Network-Based Parameterization Frameworks (2023). His 2018 study on 3D printing technologies and 2009 work on digital design methodologies underscore his long-term commitment to advancing architectural fabrication. KIM's professional experience includes roles at major firms like Daewoo Corp/Construction (1995-1999) and Pei, Cobb, Freed and Partners (2003-2005), prior to his academic career.
Giuseppe Iannaccone is a full Professor at the University of Pisa , Department of Information Engineering. His research focuses on quantum electronics , neuromorphic computing , and 2D materials for advanced applications in analog circuits and high-temperature electronics. Lead researcher in QUEPE Quantum Engineering and QUEFORMAL projects Pioneer in neuromorphic chip design using silicon and 2D materials Active in developing high-temperature integrated circuits for industrial applications His recent work explores twisted transition metal dichalcogenides for spintronics, inkjet-printed 2D electronics on paper substrates, and wireless power transfer systems for medical devices. The Google Scholar articles show consistent contributions to analog neuromorphic engines , quantum transport modeling , and steep-slope transistor architectures . Collaborations include Gianluca Fiori and Benjamin Zambrano in neuromorphic hardware development. He actively promotes student well-being through institutional initiatives like the Ufficio Benessere at University of Pisa and has taught RFID and IoT courses for PhD students. Current research integrates MoS2/graphene heterostructures and van der Waals junctions for next-generation electronics.
António Fernando Macedo Ribeiro is an Associate Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho. He is also a Senior Researcher at the Algoritmi Research Center and a member of both the IE R&D Group and CAR R&D Lab. He graduated in Computer Science (1988), earned an MSc in Industrial Robotics (1992), and a PhD in Industrial Robotics and Advanced Manufacturing Technology (1995). His academic career includes roles as department director (2013-2016) and co-director of Algoritmi (2006-2010). He founded the Robotics Laboratory (LAR) at the University of Minho and the spin-off SAR (botnroll.com). His research focuses on mobile robotics , autonomous systems , computer vision , and industrial automation . He has led over 50 projects, including RoboParty (since 2007) and RoboCup participation (since 1999). His work spans robot localization , gesture recognition , and adaptive control . Recent publications highlight trends in autonomous navigation , deep learning for robotics, and human-robot interaction . Key subfields include hexapod locomotion, multi-agent systems, tactile sensing, and 3D recognition. He has organized over 30 events like RoboCup editions and RoboParty. He actively promotes robotics education for youth through TEDx talks, school visits, and robotics clubs.
Tomoko Hashida is a Professor at Waseda University's School of Fundamental Science and Engineering , where she explores the intersection of Human-Computer Interaction , Interactive Media , and Speculative Design . Her work bridges art , technology , and psychological insight , focusing on interfaces that challenge conventional human-environment relationships. Education: PhD in Interdisciplinary Information Studies (The University of Tokyo), MSc in Interdisciplinary Information Studies (The University of Tokyo), BA in Musicology (Tokyo University of the Arts) Hashida's research centers on redefining interaction through systems that reveal hidden aspects of familiar environments. Key projects include: Floatio : Levitating tangible interfaces rapoptosis : Self-destructive prototyping Photochromic Sculpture : Light-reactive 3D displays Peaflet : Personalized museum souvenirs atmoRefractor : Heat haze-controlled spatial visuals Her publications across ACM , SIGGRAPH , and Virtual Reality Society of Japan journals demonstrate a commitment to innovative display technologies and human-centric design . Awards like the Funai Academic Award and Entertainment Computing Best Paper recognize her contributions to interactive experiences . She has contributed to 15 major publications between 2015-2019, spanning disciplines from computer science to art-science synthesis .
Melvyn L. Smith serves as Professor of Machine Vision and Director of the Centre for Machine Vision (CMV) at the University of the West of England (UWE), where he has held academic positions since completing his Ph.D. in 1997. His leadership extends to editorial roles for four international journals including Computers in Industry , and he contributes to national research strategy as a member of the EPSRC Peer Review College (since 2003) and NERC College (since 2020). His educational qualifications include: B.Eng. (Hons) in Mechanical Engineering from University of Bath (1987) M.Sc. in Robotics and Advanced Manufacturing Systems from Cranfield Institute of Technology (1988) Ph.D. from University of the West of England (1997) Professor Smith's research centers on machine vision and deep learning applications across diverse domains. He pioneers computer vision solutions for agricultural challenges including crop monitoring, plant phenotyping, and insect welfare assessment, while simultaneously advancing medical diagnostics through neuroimaging analysis for multiple sclerosis, diabetes prediction frameworks, and cardiac health studies. His work consistently bridges theoretical innovation with real-world deployment, evidenced by patents in photometric stereo imaging and optical devices for industrial applications. Analysis of his 15 most recent publications (2021-2025) reveals a strategic expansion into interdisciplinary problem-solving, with 60% focused on agricultural robotics and 30% on medical applications. Key methodological trends include convolutional neural networks for low-resolution image analysis, 3D reconstruction techniques for plant phenotyping, and machine learning frameworks for clinical diagnostics – all emphasizing robustness in uncontrolled environments. His scientific recognition includes: Fellow of the Institution of Engineering and Technology (FEIT) As Director of CMV, Professor Smith mentors early-career researchers and leads collaborations with InnovateUK and industry partners. His grant portfolio includes EPSRC-funded projects in machine vision for outdoor environments and NERC-supported environmental monitoring systems, with recent work securing patent protection for crop monitoring apparatus. He actively assesses research proposals for UKRI councils and advises government bodies on agricultural robotics strategy. The Centre for Machine Vision operates as a hub for cross-sector innovation, partnering with agri-tech firms on precision farming systems and healthcare providers on diagnostic imaging tools. Current initiatives include the EU-funded 'Agricultural Robotics' white paper implementation and development of contactless 3D biometric identification systems for transportation infrastructure.
Martin Slepicka is a researcher at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich. His work focuses on bridging Building Information Modeling (BIM) with additive manufacturing and digital twinning technologies. Department: Civil and Building Engineering Research Group: Digital Twinning, Construction Robotics Research Highlights: Slepicka specializes in: Integrating BIM with digital fabrication workflows Developing closed-loop systems for additive manufacturing Real-time data exchange in construction robotics Automated parameter calibration using machine learning Semantic enrichment of BIM through multi-sensor platforms Academic Contributions: Recent publications demonstrate expertise in: Extrusion-based additive manufacturing control Non-planar path planning for 3D-printed components Autonomous robot grasping solutions From fabrication models to simulation frameworks Laboratories: Active in: BIM-Lab Robotic Fabrication Lab Mobile Machinery development
Patrizia Scandurra is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. Her academic appointment in Computer Science (01/B1) spans from 2022 to 2033. She previously held roles as a researcher at the University of Bergamo (2009-2017) and postdoctoral fellow at the University of Milan (2006-2008). She earned her PhD in Computer Science (2006) and Bachelor's degree (2002) from the University of Catania. Research Focus : Software architectures and formal methods for modeling, validation, and verification of software-intensive systems. Specializations : Runtime analysis of self-adaptive, autonomous, and uncertain systems including IoT-Edge-Cloud applications, embedded systems, and system-on-chip. Collaborations : STMicroelectronics, Atego, Bialetti, and ENEA. Conference Involvement : Program/organizing committees for ICSE, ASE, ISSRE, ICSA, ECSA, SEAMS@ICSE, ABZ, SA-TTA@SAC, FAACS@ECSA. Research Projects : Model-driven development for robotics, adaptive architectures for pervasive systems, big data in smart cities, and digital twins for medical systems. Notable Contributions : Development of the ASMETA formal method community tools and frameworks for rigorous system design. She has published over 100 peer-reviewed works in international journals and conferences.
Professor Zhu Qi is a faculty member in the Department of Electrical and Computer Engineering at Northwestern University's McCormick School of Engineering, with courtesy appointment in Computer Science. He leads the IDEAS Lab (Design Automation of Intelligent Systems Lab) where his research focuses on design automation for intelligent cyber-physical systems and Internet-of-Things applications. His research interests include safe and robust machine learning for embodied AI systems, cyber-physical security, energy-efficient CPS, and system-on-chip design. Professor Zhu's work particularly addresses safety, robustness, security, adaptability, resiliency, and energy challenges in the design and operation of embodied AI systems. His applications span connected and autonomous vehicles, robotics, advanced manufacturing, wearable computing, smart buildings and infrastructures, and IoT. Professor Zhu's recent publications reveal a strong focus on safety verification of neural network controlled systems, robust reinforcement learning methods, and applications of large language models in autonomous systems. His work often combines formal verification techniques with machine learning approaches to provide safety guarantees for AI-enabled cyber-physical systems. DATE 2022 Best Paper Award AutoSec 2021 Best Short Paper Award ACM TODAES 2016 Best Paper Award IEEE TCCPS Early-Career Award (2017) Humboldt Research Fellowship for Experienced Researchers (2017) NAE US Frontiers of Engineering participant (2020) Professor Zhu has secured multiple research grants from NSF (including FM, DESC, and Fuse grants), DOE, ONR, and industry partners including GM and Toyota. His advising includes PhD students Shuyue Lan and Hengyi Liang, and postdoc Chao Huang who became a Lecturer at University of Liverpool. He leads the IDEAS Lab which focuses on cross-layer design, verification, and adaptation of learning-enabled cyber-physical systems.
Professor Dagou Zeze is a Professor of Nanotechnology & Microsystems and Director of International Engagement in the Department of Engineering at Durham University. He also serves as Deputy Executive Dean for Research in the Faculty of Science. Professor Zeze has established himself as a leading researcher in nanotechnology and microsystems, with significant contributions to the field of nanomaterials device integration. His educational background includes a BSc in Physics from the University of Abidjan, Ivory Coast (1990), followed by MPhil and PhD in Electronics from the Université of Clermont-Ferrand, France (1996). He completed postdoctoral research at the University of Ulster (2000) on thin amorphous carbon films and at the University of Surrey (2003) on microfabrication. Professor Zeze's research focuses on nanostructured materials, micro and nanofabrication, and the integration of nanomaterials (particularly carbon nanotubes and semiconductor nanowires) in devices. His current research themes include integration of nanostructured materials in device fabrication, nanofabrication & microfabrication, carbon nanotubes, smart devices, semiconductor nanowires, and multifunction devices. He has also explored thin films technology, organic electronics, and liquid handling robotic system design. His publication record shows a strong focus on nanomaterials for electronic and sensing applications, with recent work emphasizing piezoelectric sensors, ZnO nanowires, metasurfaces for structural color, and in-materio computing approaches. His research demonstrates a consistent trajectory toward practical applications of nanotechnology in sensors, electronics, and energy conversion devices. Senior Research Fellow of the Royal Academy of Engineering/The Leverhulme Trust (2013-14) Fellow of the World Academy of Materials and Manufacturing Engineering (2015-) Fellow of the Institute of Engineering and Technology External Degree Programme Examiner: University of Exeter (2016-2020) External Degree Programme Examiner: University of Bangor (2017-21) Professor Zeze has supervised numerous postgraduate students including Grainne Gilleece, Luis Ceron Oliver, Mana Saeed, and Shixian Sun. He has secured substantial research funding, having contributed to seven European Framework programme FP7 and Horizon 2020 projects totaling over €12.5 million. He serves as the scientific coordinator for three Marie Curie Actions international consortia on semiconductor nanowires (FUNPROB, NanoEmbrace, and H2020 INDEED ITN), which involve significant international academic and industrial collaboration across Europe. His leadership extends to his role as Chair of the Durham University EU Liaison Group (2018-2023) and as Director of Postgraduate Studies (2014-2017). Professor Zeze leads research activities in the Next Generation Materials & Microsystems Research Challenge and has established collaborative networks across Europe through his involvement in major EU-funded projects.
Hassan Shirvani is a Professor of Engineering Design and Simulation at the School of Engineering and the Built Environment, Anglia Ruskin University. He serves as Director of the Engineering Analysis Simulation and Tribology (EAST) Research Group, focusing on industry collaborations to solve engineering challenges. PhD in Mechanical Engineering, University of Bath MSc in Mechanical Engineering, University of Birmingham Member, Institute of Mechanical Engineers (IMechE) His research spans mechanical engineering, artificial intelligence, and biomedical applications, including: Thermal system optimization Machine learning in clinical decision-making Composite metal foil manufacturing Virtual reality medical training systems Flow dynamics in heat exchangers and nozzles AI-assisted diagnostics Hybrid manufacturing processes Hassan's publications reflect expertise in computational modeling, multi-physics simulations, and industrial applications. Notable areas include deep learning for suicide prediction, thermodynamic analysis of sustainable energy systems, and tribology in mechanical components.
Professor Johan Stahre is affiliated with Chalmers University of Technology, where he leads the Division of Production Systems and serves as Assistant Head of Department. His expertise spans industrial digitalization, automation, and the human role in future manufacturing systems. Codirector of Produktion2030 (2013–present) Central figure in EIT Manufacturing development (2016–present) Chalmers representative in European Factories of the Future Research Organisation His research focuses on: Manufacturing resilience and uncertainty navigation Human-Robot Collaboration in restricted environments 5G-enabled smart maintenance systems Sustainability through digital servitization Skill gaps in Industry 4.0/5.0 Computer vision applications in assembly systems Recent publications highlight trends in immersive technologies for manufacturing and resilience frameworks. While no formal awards are listed, his leadership in national and European innovation programs underscores his impact.
Megan Hofmann is an Assistant Professor holding dual roles at Northeastern University's Khoury College of Computer Sciences and the Department of Mechanical and Industrial Engineering (College of Engineering). She earned her PhD in Human-Computer Interaction from Carnegie Mellon University in 2022. Her research focuses on accessibility and digital fabrication, particularly in healthcare contexts, including automated machine knitting and medical making. She leads the Accessible Creative Technologies (ACT) Lab, which develops tools like Maptimizer (custom tactile maps), OPTIMISM (collaborative optimization frameworks), and KnitGIST (generative knitting design). Her work addresses challenges in assistive technology fabrication, such as creating accessible medical devices and optimizing rapid prototyping in healthcare. Recent projects include NSF-funded research on interactive smart textiles and studies on distributed manufacturing during the COVID-19 pandemic. Hofmann’s contributions span interdisciplinary domains, blending computer science, mechanical engineering, and healthcare innovation. Grants & Awards: Recipient of a $550,000 NSF grant for smart textile tools (2024). Labs: ACT Lab focuses on inclusive digital fabrication systems.
Gerardo Aragon Camarasa is a Senior Lecturer at the School of Computing Science, University of Glasgow, where he leads research in the Computer Vision and Autonomous Systems group. His work focuses on solving real-world challenges in robotic perception, manipulation, and grasping using advanced AI techniques. Research Interests: Robotics and AI for advanced manufacturing systems Perception and manipulation of deformable objects Autonomous robotic systems for chemical and domestic applications Robot behavior modeling and self-awareness His publications demonstrate strong emphasis on robotic vision (garment perception, hand-eye calibration), AI integration (multimodal LLMs, reinforcement learning), and industrial applications (chemical robotics, Industry 5.0 ethics). Recent work shows growing focus on foundation models for robotics and simulation frameworks. Research Leadership: He leads multiple grants including an EPSRC programme grant for chemical robotics and a Royal Society project on robotic teleoperation. Actively supervises 7+ PhD students and has graduated 8+ doctoral researchers in robotics and computer vision. Infrastructure: Leads research using dual-arm robots and maintains active GitHub repositories and YouTube channels demonstrating robotic manipulation systems. Regular contributor to top robotics conferences (ICRA, IROS) and journals.
Dr. Ali Kosar is a Professor at Sabanci University's Mechatronics Engineering Program , with affiliations in Materials Science & Nanoengineering and Molecular Biology, Genetics & Bioengineering. As Co-Director of the Center of Excellence for Functional Surfaces and Interfaces for Nano Diagnostics (EFSUN) and Senior Researcher at SUNUM Nanotechnology Center, he leads a multidisciplinary research group spanning 30+ members. His work bridges microfluidics, heat transfer , and biomedical device design , focusing on cavitation-on-a-chip systems and microscale thermal management. Key research themes: Micro/Nanoscale Heat Transfer, Cavitation Dynamics, Biomedical Microdevices, Energy Applications Labs: Microfluidics and Microthermal Systems Laboratory, EFSUN, SUNUM His 175+ journal articles (h-index: 33) appear in journals like Physics of Fluids and Lab on a Chip , with recent work featured in Advanced NanoBioMed Research and Biosensors . He serves as Associate Editor of Applied Thermal Engineering and Subject Editor for Advanced Materials Interfaces . Scientific awards include ASME Fellow , TÜBA Membership , and multiple conference honors. His team has secured substantial national/international grants and developed technologies like the SUTAB (Sabanci University Tissue Ablating Bubbles) system.
