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.
John Rowan is a Professor of Physical Geography and Director of the UNESCO Centre for Water Law, Policy & Science at the University of Dundee. His roles include advancing sustainable development, particularly SDG6 (water and sanitation), and leading interdisciplinary initiatives. Previously, he served as Vice Principal for Research and inaugural Dean of the School of Social Sciences. His research focuses on environmental change, climate impacts on water resources, and policy-driven solutions, with global collaborations in Bangladesh, India, and Kenya. He has held advisory roles in Scottish Government’s Centres of Expertise and chairs UNESCO’s UK International Hydrological Committee. Research Interests: Environmental change, climate-water-food nexus, river basin management, sediment dynamics, and policy integration. His work bridges academic and applied domains, emphasizing governance and sustainable practices. Key projects include enhancing water security under climate uncertainty, developing risk frameworks for drinking water, and addressing the water-food-energy nexus. Publications: Over 111 articles, focusing on climate adaptation, water resource vulnerabilities, and ecohydrological modeling. Recent highlights include studies on the Karakoram Anomaly’s hydrological tipping points and frameworks for climate-resilient water safety plans. Awards: Gold Engage Watermark Award (2020), United Nations Risk Award (2019). Projects span international collaborations and policy advisory roles. He has supervised 12 students and led over 33 research projects, including the Hydro Nation Scholars Programme. Labs/Teams: UNESCO Centre for Water Law, Policy & Science; Centre for Environmental Change and Human Resilience (CECHR), collaborating with the James Hutton Institute. Active in global forums like the UNFCCC Climate Assembly and World Water Forum.
Dr. Anna Raffoni serves as a Senior Lecturer in Accounting and Finance at Loughborough Business School, Loughborough University, and holds the strategic role of Programme Lead for Social Science Research (Business and Management Studies). She joined the institution in January 2015 after accumulating academic experience at the University of East Anglia, Cranfield University School of Management, and the University of Bologna, establishing herself as a key contributor to the Accounting and Finance research group. Her academic foundation includes a PhD in Management Accounting (specializing in customer value management) awarded by the University of Florence in 2009, which continues to inform her interdisciplinary research trajectory. Raffoni's scholarly work centers on performance management, business analytics, and strategic management accounting, with publications appearing in premier journals including the European Journal of Operational Research, British Accounting Review, Production, Planning & Control, and Omega. Her research uniquely bridges quantitative operations research methods with accounting frameworks, particularly examining how data analytics transforms traditional performance measurement in banking and service sectors through techniques like machine learning and data envelopment analysis. Analysis of her 15 most recent publications (2012-2024) reveals a clear evolution toward integrating advanced analytics with performance management systems. She has pioneered multidimensional efficiency measurement in banking branches, explored total cost of ownership in supply chains, and investigated strategic performance measurement adoption, consistently demonstrating how operational research methods solve real-world accounting challenges while advancing theoretical models. Her scientific recognition features the Dean’s Award for Early Career Teacher of the Year (2017), acknowledging her excellence in undergraduate and postgraduate instruction. In her capacity as Programme Lead, Raffoni shapes research strategy and supports faculty development across Business and Management Studies. While specific supervisees and grant details aren't documented in available materials, her leadership role and active publication record indicate substantial engagement in research mentorship and academic community building. She actively collaborates within Loughborough's Accounting and Finance research group, contributing to interdisciplinary projects that address contemporary challenges in financial management through analytical approaches, with emerging work suggesting increasing focus on artificial intelligence applications in performance systems.
Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.
Professor Steven V. Ley leads the Yusuf Hamied Department of Chemistry at the University of Cambridge, focusing on transformative research in flow chemistry, organic synthesis, and green chemistry. His work emphasizes sustainable methodologies and the integration of advanced technologies like microcontrollers and automation to revolutionize chemical processes. In 2018, he received the prestigious Arthur C. Cope Award—the first UK-based recipient—recognizing groundbreaking contributions to organic chemistry. Research interests include developing continuous flow systems for hazardous reaction management, immobilized reagents, and machine-assisted synthesis. Collaborations span academia and industry, notably through spin-off company New Path Molecular , which applies cutting-edge synthesis techniques to pharmaceuticals and agrochemicals. Key publications highlight innovations in flow chemistry applications, sustainable process design, and automation. His work bridges chemistry with engineering, aiming to address global challenges in resource efficiency and environmental impact. Awards: Arthur C. Cope Award (2018) Lab/Teams: Active research group at the University of Cambridge; collaborates with New Path Molecular on commercial applications.
Professor Maja Pantic is a Professor of Affective & Behavioural Computing at the Department of Computing, Faculty of Engineering, Imperial College London. Her research focuses on artificial intelligence, image processing, and audio-visual speech recognition. She leads projects in multimodal systems, including facial analysis, emotion recognition, and speech-driven animation. Affiliations include the AI for Healthcare initiative, the Artificial Intelligence Network, and the Machine Learning Network. Her work addresses challenges in real-time speech enhancement, cross-modal learning, and synthetic data generation. Recent publications emphasize advancements in audiovisual speech synthesis, lip-reading, and emotion-aware systems. She has contributed to datasets like KAN-AV and SEWA DB, advancing research in face analysis and affective computing.
Onur Mutlu is a Professor of Computer Science at ETH Zurich, affiliated with the Department of Information Technology and Electrical Engineering. He also holds adjunct professorships at Carnegie Mellon University and Bilkent University. His research focuses on computer architecture, systems security, bioinformatics, and energy-efficient computing. He has pioneered work on memory-centric computing paradigms, RowHammer security vulnerabilities, and bio-inspired computing systems. He teaches courses such as Digital Design & Computer Architecture and supervises the SAFARI research group, which explores cutting-edge topics in memory systems, AI accelerators, and genomics. Recent activities include keynote talks at ISCA, HiPEAC, and IEEE conferences, emphasizing emerging hardware-software co-design principles. Key contributions include foundational work on memory reliability, cross-layer system design, and accelerating genomic data analysis. His research has been showcased in over 200 publications and industry collaborations with tech leaders like Intel, Huawei, and Micron.
Simon Yang is a Professor in the School of Engineering at the University of Guelph, part of the College of Engineering and Physical Sciences. His research focuses on artificial intelligence, robotics, sensors, control systems, and bio-inspired intelligence. He has contributed to advanced robotics applications, including mobile robot navigation, underwater vehicle control, and agricultural automation. Dr. Yang holds editorial roles for journals such as the International Journal of Robotics and Automation and IEEE Transactions on Cybernetics . His work bridges theoretical advancements with practical implementations in areas like sensor networks, machine learning, and multi-agent systems. Recent projects include developing robust control frameworks for autonomous systems, digital twin applications, and bio-inspired neural network algorithms. His research emphasizes real-world challenges in robotics, environmental monitoring, and precision agriculture, with a focus on integrating AI-driven solutions for enhanced decision-making and system reliability. Professional contributions include advisory roles in multiple journals and conference committees, reflecting his leadership in the field.
Kok Sheik Wong is a Professor and Deputy Head (Research) at the School of Information Technology, Monash University Malaysia. He holds a Doctor of Engineering from Shinshu University, Japan, and Master’s and Bachelor’s degrees in Computer Science and Mathematics from Utah State University, USA. His academic leadership and research excellence are central to his role at Monash. B.S. Computational Mathematics, Utah State University (2002) M.S. Computer Science, Utah State University (2006) M.S. Mathematics, Utah State University (2004) Doctor of Engineering, Shinshu University, Japan (2009) His research focuses on multimedia signal processing and cybersecurity , particularly in data hiding , reversible data hiding , coverless steganography , and multimedia encryption . He is also expanding into digital health , applying AI to mental health in workplace environments. His work aligns with UN SDGs, particularly in health and education. The recent publication trends show a strong emphasis on reversible data hiding , image watermarking , and AI-driven health applications . His interdisciplinary work spans computer science, engineering, and public health, with increasing focus on real-world impact through EU and national grants. He has received several honors, including: Academic of Science Malaysia - Young Scientist Network (2020) Best Paper Award, IWDW 2019 ITEX 2021 Gold Medal for BAITRADAR School of IT Excellence in Research Award (2022) Dr. Wong actively supervises PhD students and leads major research projects, including the EU-funded WAge project. He has served as an associate editor for IEEE Signal Processing Letters and the Journal of Information Security and Applications, and is a member of IEEE IFS and APSIPA technical committees. His grants reflect strong external collaboration and funding in cybersecurity and digital health. He is involved in key research labs and teams through Monash University and international consortia, particularly in the areas of multimedia security and digital health innovation. His leadership in the WAge project connects him with European and Asia-Pacific research networks, enhancing global impact.
Sageev Oore is an Associate Professor in the Faculty of Computer Science at Dalhousie University, a Research Faculty Member at the Vector Institute for Artificial Intelligence, and a Canada CIFAR AI Chair. He previously served as Associate Professor and Chairperson in the Department of Mathematics & Computer Science at Saint Mary’s University and spent 2016–2018 as a Visiting Research Scientist at Google Brain, working on the Magenta team. Faculty of Computer Science, Dalhousie University Vector Institute for Artificial Intelligence Google Brain (2016–2018) Saint Mary’s University (former) Sageev Oore's research centers on machine learning and deep learning, with a strong focus on creative applications in music, audio processing, and computational creativity. His work bridges the gap between technical innovation and artistic expression, developing systems that generate and interact with music using neural networks. He has made significant contributions to generative models for music, including the development of PerformanceRNN and other interactive systems. His recent publications highlight advancements in out-of-distribution detection (Gram-OOD), interactive music generation, and deep learning tools for creative domains. These works reflect a consistent trend toward building intelligent, user-centered systems that enhance human creativity through AI. Canada CIFAR AI Chair (2018) Best Paper Award, CVPR ISIC Workshop (2020) Outstanding Demonstration Award (Runner-up), NeurIPS (2020) Best Demonstration Award, AAAI (2017) Best Demonstration Award, NeurIPS (2016) Sageev Oore actively mentors graduate and undergraduate students, with well-funded research positions available for motivated candidates. His collaborations span academia and industry, including major projects with Google Brain and interdisciplinary work with artists. He leads research initiatives in AI-driven creativity and is deeply involved in the Canadian AI ecosystem through the Vector Institute and CIFAR. His work is supported by significant grants and affiliations, including the Canada CIFAR AI Chair program, which funds his research in foundational AI and its applications. He is also part of the Magenta project at Google, contributing to open-source tools for art and music generation. Sageev Oore leads a research group focused on deep learning for creative applications, with projects in music generation, audio synthesis, and human-AI interaction. His lab collaborates with musicians, artists, and healthcare researchers, fostering a transdisciplinary approach to AI innovation.
Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.
Arun Rai serves as Regents’ Professor and Howard S. Starks Distinguished Chair at Georgia State University's Robinson College of Business, where he co-founded and directs the Center for Digital Innovation. His career spans interdisciplinary research bridging information systems with societal impact through industry-university collaborations across global sectors. His educational foundation includes: Ph.D. from Kent State University MBA from Clarion University of Pennsylvania M.S. from Birla Institute of Technology & Science Rai's research explores digital innovation , AI governance , and societal impacts of technology through investigations of platform ecosystems, supply chain transformation, and digital solutions for poverty and health disparities. His work uniquely connects technical systems design with behavioral and organizational outcomes across contexts from rural India to global corporations. Recent publications (2023-2025) reveal intensifying focus on AI-human collaboration , digital risk assessment , and platform governance tensions , with growing emphasis on healthcare applications and equity implications. The trajectory shows evolution from organizational IT adoption toward complex sociotechnical systems addressing global challenges. His scientific recognition includes: Fellow of the Association for Information Systems Distinguished Fellow of the INFORMS Information Systems Society LEO Award for Lifetime Exceptional Achievement Rai has mentored over 60 doctoral students (30+ as chair) with alumni now holding leadership positions globally. His research attracts major funding from Apollo Hospitals, China Mobile, IBM, Intel, UPS, and federal agencies, enabling real-world implementations like the Global Supply Chain Solutions Program during UPS's digital transformation. Current initiatives focus on generative AI in education and healthcare IT policy impacts. As director of the Center for Digital Innovation, he cultivates cross-sector partnerships advancing digital transformation through collaborative research on AI governance, platform ecosystems, and societal impact measurement.
Lukas Engelmann is a Senior Lecturer at the University of Edinburgh , specifically within the Science, Technology and Innovation Studies department under the School of Social and Political Science . His research focuses on the history and sociology of biomedicine , with particular interest in epidemiological reasoning , visual cultures of disease , digital epidemiology , and decolonial approaches to medical history . The Epidemy Lab , which he founded, explores the historical development of epidemiology and its contemporary influence on data-driven public health and pandemic policy-making . Engelmann's work has been funded by prestigious grants including an ERC Starting Grant (2021-2025) for his research on the history of epidemiological reasoning, and support from the Wellcome Trust for projects examining the social dimensions of digital health . His book 'Mapping AIDS' (2018) established him as a leading scholar in medical visualization , while 'Sulphuric Utopias' (2020) with Christos Lynteris explores the technological history of maritime sanitation and its political implications. Recent publications emphasize the visual and data practices that have shaped epidemiology, including works on epidemic modeling during the COVID-19 pandemic , the history of plague mapping , and the ethical implications of digital phenotyping . He has also contributed to interdisciplinary discussions on syndemics , co-infection epistemology , and the commercialization of bacteriology in the early 20th century. His scientific contributions have earned recognition through editorial roles in journals like Big Data and Society , and collaborative projects such as 'Working with Diagrams' (2022) which investigates the epistemological role of visual tools in medical knowledge production. Scientific Awards and Funding: ERC Starting Grant (2021-2025) Wellcome Trust Institutional Support Fund British Academy/Leverhulme Small Research Grant Chancellor's Fellowship (University of Edinburgh) 'Sulphuric Utopias' listed in The Guardian's 30 Books to Understand the World (2020)
Mengdi Wang is a Professor at Princeton University with primary appointments in the Department of Electrical and Computer Engineering and the Center for Statistics and Machine Learning, and courtesy appointments in the Department of Computer Science and Omenn-Darling Bioengineering Institute. She co-directs Princeton AI for Accelerated Invention and is affiliated with the Princeton ML Theory Group and Princeton Language+Intelligence Initiative, with prior visiting roles at DeepMind, IAS, and Simons Institute. Her educational background includes a PhD in Electrical Engineering and Computer Science (with Mathematics minor) from MIT (2013), advised by Dimitri P. Bertsekas at LIDS, and undergraduate studies in Automation at Tsinghua University: PhD: MIT, Electrical Engineering and Computer Science (2013) Bachelor: Tsinghua University, Automation Her research establishes theoretical foundations for machine learning with emphasis on reinforcement learning algorithms, generative AI, and large language models. She investigates data-driven stochastic optimization, statistical limits of reinforcement learning, representation learning, and diffusion models, developing provably robust algorithms for complex systems. Her work bridges theoretical guarantees with real-world applications in healthcare, biotech drug discovery, fintech, and scientific acceleration, focusing on how AI can transform discovery processes across disciplines. Her scientific contributions are recognized by prestigious awards: Young Researcher Prize in Continuous Optimization (Mathematical Optimization Society, 2016) Princeton SEAS Innovation Award (2016) NSF Career Award (2017) Google Faculty Award (2017) MIT Tech Review 35-Under-35 (China region, 2018) WAIC YunFan Award (2022) Donald Eckman Award (American Automatic Control Council, 2024) Professor Wang actively mentors students and recruits undergraduate interns, visitors, and postdocs for her research group. Her work is supported by major grants from NSF, AFOSR, NIH, ONR, Google, Microsoft C3.ai, FinUP, RVAC Medicines, MURI, and GenMab. She serves as Program Chair for ICLR 2023 and Senior Area Chair for NeurIPS, ICML, and COLT, while editing for Harvard Data Science Review and Operations Research. She leads Princeton AI for Accelerated Invention, which develops AI-driven solutions for scientific discovery, collaborating closely with Princeton's ML Theory Group and Language+Intelligence Initiative to advance algorithmic innovation and interdisciplinary applications.
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.
