Yan Delaure is Associate Professor of Fluid Mechanics at Dublin City University's School of Mechanical and Manufacturing Engineering and Deputy Director of the DCU Water Institute. His research focuses on multiphase flows, environmental hydraulics, and computational fluid dynamics applications in wastewater treatment and marine systems. Research includes microbubble dynamics for aeration, fluid-structure interactions in deformable systems, and biomimetic antifouling solutions. Recent publications explore advanced simulation methods for turbulent flows and additive manufacturing process optimization.
Dr. Mohamed Youssef is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University. He holds a PhD (Electrical and Computer Engineering) from Queen’s University (2005). His primary affiliation is the Faculty of Engineering and Applied Science, with research focusing on propulsion systems, power electronics, railway systems, and renewable energy technologies. Education: PhD, Electrical and Computer Engineering, Queen’s University (2005) MSc, Power Electronics, Concordia University (2001) MSc, Electric Power and Machines, Ain Shams University (1999) BSc, Electric Power and Machines, Ain Shams University (1995) Research Interests: Dr. Youssef’s expertise spans propulsion systems for automotive and hyperloop technologies , power electronics for IoT and renewable energy , railway electromagnetic compatibility , and power system stability . His work emphasizes practical applications in electric vehicles, smart grid integration, and sustainable energy systems. He leads the PEDAL (Power Electronics and Drives Laboratory) at Ontario Tech. Awards and Recognition: Recipient of the NSERC Post-doctorate Scholarship (2006) Best Paper Award at IECON 2004 Award of Merit from Ontario Center of Excellence (2006) Nominated for the Howard Alper Prize (2007) Professional Activities: He serves as a reviewer for IEEE Transactions on Power Electronics , IEEE Transactions on Industrial Electronics , and others. He has held roles as Technical Chair at IEEE SEGE 2015 and Track Chair at IEEE SEGE 2016. Current affiliations include Senior Member of IEEE and Chair of the IEEE Power Electronics Chapter in Toronto. Labs and Teams: He directs the PEDAL Lab , focusing on advanced power electronics and electric vehicle technologies. Collaborations include Bombardier Transportation and Armstrong Pumps.
Mario Romero is an Associate Professor in Visualization at the Department of Computational Science and Technology (CST), KTH Royal Institute of Technology. He leads the InfraVis national research infrastructure for data visualization and is a Digital Futures Faculty member. His roles include national technical manager of InfraVis, member of the Executive Committee of Digital Futures, and Associate Director for Seminars & Workshops. Education: PhD in Computer Science (Georgia Tech, 2009), MSc in Computer Science (UIUC, 2001), and dual BSc degrees in Industrial Engineering and Construction Engineering (Universidad San Francisco de Quito, 1996). He is a Fulbright Scholar from Ecuador and holds postdoctoral experience at Uppsala University. Research focuses on Human-Computer Interaction, Visualization, and Ubiquitous Computing. Key projects include: TENT: Technology-Enhanced Neurosurgical Training VisBac: Visualizing airborne bacteria in ORs PSP: Platform for Smart People (autism support) SMART: Predictive maintenance in pharmaceuticals Homo Colossus: Energy footprint visualization Awards: Selected for IVA's 100 research2business projects (2021). Co-founded BrailleTouch (blind-friendly keyboard) and Anymaker (3D sketching app). Supervised students in C-Awards-winning projects (e.g., Yue Liu's thesis defense in 2024). Teaching: Responsible for courses like Information Visualization (DH2321) and Advanced Graphics & Interaction (DH2413). Active in organizing conferences (e.g., Eurographics 2020 Education Track Chair).
Klas Hjort is a Professor of Materials Science at Uppsala University's Ångström Laboratory , specializing in Microsystems Technology . He leads the microsystems technology program and has pioneered research in heterogeneous microsystems on stainless steel, flexible foils, and elastic substrates for biomedical applications and wireless sensor/actuator systems . Key projects: SSF robotic textiles , PERSIMMON smart patches Research themes: Microfluidic actuation , Liquid metal patterning , Stretchable electronics His recent publications focus on soft robotics , smart patches , and high-pressure microfluidic systems , with keywords spanning Microfluidics , Biomedical Engineering , and Stretchable Electronics . He collaborates extensively in robotic textiles , microvalve design , and liquid metal composites . Contact: klas.hjort@angstrom.uu.se
Chris Fuller, Ph.D., is the Samuel Langley Distinguished Professor of Engineering at the College of Engineering , Virginia Tech. He leads the Vibrations and Acoustics Laboratory (VAL) , focusing on active/passive noise control systems, metamaterials, and their application to aerospace, medical devices, and industrial machinery. Education: Ph.D. (1979) and B.E. (1974) from the University of Adelaide, Australia. Research Interests: Structural acoustics, adaptive materials, machine learning in noise prediction, and biomedical acoustics (e.g., neonatal incubators). Awards: ASME Rayleigh Award (2017), NASA Team Achievement Award (1996), and Fellow of the Acoustical Society of America. Recent Publications: Highlight advancements in drone noise reduction using neural networks, metamaterials for HVAC systems, and poro-elastic materials for low-frequency noise control.
Dr. Charles Rougé is a Senior Lecturer in Water Resilience at the Department of Civil and Structural Engineering, School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. He holds an MSc and PhD, and his career spans top institutions in France, the US, Canada, and the UK. 2018–present: University of Sheffield (Lecturer → Senior Lecturer) 2023–2026: Principal Investigator, EPSRC-funded project on water-energy systems under climate change and energy transition Research Focus: Modelling complex water resource systems to enhance resilience against climate change, with a growing emphasis on water-energy nexus challenges. His work integrates hydrology, power systems engineering, economics, and decision theory. Key Trends: 15 most recent articles span climate-perturbed hydrological models, water-energy system coupling, socio-hydrology applications, and transboundary water governance. Many showcase interdisciplinary approaches to water infrastructure flexibility and uncertainty quantification. Scientific Awards: 2019 Quentin Martin Best Practice Award (JWRPM) 2015 Editor's Citation for Excellence (WRR) Grants: EPSRC grant (UKRI) for 'Flexible design and operation of water resource systems' (2023–2026) Team Leadership: Leads the 'Water resilience' research group at Sheffield, mentoring early-career researchers in water system sustainability and low-carbon energy transition.
Paul Mativenga is a Professor of Mechanical and Aerospace Engineering at The University of Manchester, leading research in sustainable and advanced manufacturing. His roles include strategic leadership of Social Responsibility and Equality, Diversity, and Inclusion within the Faculty of Science and Engineering. He holds a PhD from the University of Liverpool and is a Member of the CIRP Academy for Production Engineering. Research focuses on resource-efficient manufacturing, laser processing, and circular economy strategies. Key interests include sustainable manufacturing technologies, energy reduction in machining, and recycling systems. He leads the Laser Processing Research Centre (LPRC) and collaborates on projects like the RE3 initiative for plastic recycling optimization. Recent work emphasizes carbon emission modeling in manufacturing, additive manufacturing optimization, and policy frameworks for industrial sustainability. He has supervised multiple PhD students and received the 2014 A M Strickland Prize for contributions to mechanical engineering. Active editorial roles include associate editorships at Elsevier and Sage Publications. His laboratory, the Laser Processing Research Laboratory, supports cutting-edge research in laser-material interactions and sustainable processes.
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
Francine Battaglia is a Professor and Chair of the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. She directs the Advanced Simulations for Computing ENergy Transport (ASCENT) Laboratory. Her research focuses on computational fluid dynamics (CFD) applications in building energy systems, renewable energy, turbulent multiphase flows, and combustion. She holds a PhD in Mechanical Engineering from Pennsylvania State University (1997), and MS/BS degrees from SUNY Buffalo (1992, 1991). Research interests include CFD modeling for HVAC optimization, natural ventilation design, pathogen dispersion mitigation, and biomimetic aerodynamics inspired by insect flight. Her work bridges engineering, biology, and environmental science, addressing challenges in energy efficiency, public health, and sustainable architecture. Key contributions include developing predictive models for hydroplaning safety, solar chimney systems, and microbial fuel cells. She has received accolades such as the ASME Fellow distinction (2009), MAC Academic Leadership Fellowship (2019-2020), and Virginia Tech’s Teaching Excellence Award (2016). Her articles span CFD advancements in fluidization, combustion, and ventilation strategies, emphasizing practical applications in energy systems and public health. The ASCENT Lab collaborates on adaptive HVAC technologies and eco-friendly building designs, reflecting her dedication to interdisciplinary innovation. Awards: MAC Leadership Fellow, ASTFE Fellow, ASME Dedicated Service Award Education: PhD (Penn State), MS/BS (SUNY Buffalo) Labs: ASCENT Lab (focusing on CFD and energy transport)
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Dr. David Wright is a Professor in the Department of English and Technical Communication at Missouri University of Science and Technology (Missouri S&T). He joined the faculty in 2007 after prior roles at NASA’s Education Project, Oklahoma state government, and the software industry. He holds a Ph.D. in Technical Communication (Oklahoma State University, 2007), an M.S. in Higher Education Administration (1996), and a B.S. in Organizational Psychology (1993), all from Oklahoma State University. His research focuses on smart home technology and artificial intelligence, particularly examining human-AI interaction through usability and user experience (UX) testing. He also explores technology diffusion, technical communication practices in emerging technologies, and educational methodologies for technical fields. His work integrates interdisciplinary approaches, blending engineering, sociology, and computer science. Recent publications highlight his contributions to IoT usability, smart home adoption challenges, and the intersection of AI ethics with virtual assistants. He has also authored studies on knowledge graph design, technical documentation in software development, and educational initiatives in computer science and healthcare. Dr. Wright teaches courses in technical writing, usability studies, and web-based communication. His academic service includes curriculum development and advising on technical communication pedagogy. While no specific awards are listed, his extensive publication record reflects sustained scholarly impact in his fields.
Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.
Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.
Dr. Anna Baldycheva is a Senior Lecturer in Electronic Engineering at the University of Exeter, within the College of Engineering, Mathematics and Physical Sciences. She leads the interdisciplinary STEMM Laboratory, focusing on applied R&D in smart materials, photonics, AI, and IoT. With prior research experience at MIT, Trinity College Dublin, and Tyndall National Institute, she has established herself as an internationally recognized innovator and entrepreneur in emerging technologies. PhD in Electronic and Electrical Engineering, Trinity College Dublin (2008–2012) BSc (Hons) in Physics, St. Petersburg State University (2003–2008) Postgraduate Certificate in Academic Practice, University of Exeter (2016–2017) Postgraduate Certificate in Technology Management, Smurfit Business School (2009–2010) Her research spans Nano-Engineering, Opto-Electronics, Photonics, AI, and IoT , with a strong emphasis on real-world applications. She pioneers work in fluid opto-electronics , graphene nanocoatings , and AI-driven emotion recognition and early cancer detection . Her lab develops smart composite materials for flexible electronics, e-textiles, and structural applications, integrating machine learning into healthcare, education, and communications systems. The recent publications highlight a strong trend toward applied interdisciplinary innovation , combining materials science with AI and photonics for healthcare diagnostics, energy-efficient computing, and educational technology. Her work frequently bridges fundamental physics with commercialization potential, as seen in spin-out technologies like GSurf and the Electronic-Nose for lung cancer detection. Fellow, Royal Microscopical Society (RMS) Fellow, Higher Education Academy (FHEA) Expert, Future and Emerging Technologies, European Commission Featured in Forbes and Forbes Tech Council Editor-in-Chief, InSTEMM Journal Associate Editor, Nature Scientific Reports and Discover Nano Trustee, Royal Microscopical Society Founder, STEMM Global Scientific Society Founder, It’s Her! Women in STEMM Initiative Dr. Baldycheva actively supervises PhD students and has secured industrial collaborations with organizations such as Qinetiq and Lumentum. She leads multiple outreach initiatives, including STEMM Junior for underprivileged children, and serves on the committee for the Jocelyn Bell Brunel PhD Scholarship. She has raised significant research funding through national and international grants, though specific grant names are not listed. She leads the STEMM Laboratory , a multidisciplinary research group with divisions in Smart Composite Materials, Machine Learning & AI, and Opto-Electronics & Photonics. The lab emphasizes industry collaboration and technology transfer, having produced a university spin-out (GSurf) and multiple media-highlighted innovations.
R. Luke DuBois is an Associate Professor and Co-Chair of the Technology, Culture and Society Department at the NYU Tandon School of Engineering, where he also directs the Integrated Design & Media program and the Brooklyn Experimental Media Center. He holds a DMA in music composition from Columbia University and is a renowned artist, composer, and performer whose work explores intersections between technology, sound, and visual media. His research focuses on digital media, human-computer interaction, and emerging technologies applied to artistic expression and accessibility. Key roles include directing the SONYC initiative (addressing urban noise pollution via AI) and leading the NYU Ability Project (advancing disability studies through technology). He has collaborated with institutions like the Smithsonian and artists such as Maya Lin, and his work has been exhibited globally, including at the Sundance Film Festival and the Aspen Institute. DuBois co-developed the Jitter software suite for real-time data manipulation and performs in avant-garde groups like Bioluminescence and Fair Use. His artistic practice combines time-lapse phonography, interactive installations, and interdisciplinary projects that critique cultural ephemera while advancing accessibility in STEM and the arts. Recent contributions include browser-based tools for accessible music notation (SoundCells) and sonification techniques for calculus education. He serves on the Board of the ISSUE Project Room and has been featured in major publications like the New York Times and TED Conference talks.
