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Johnny T. OttesenView profile

Professor

• Mathematical Modelling
• Mathematical Physiology
• Applied Mathematics
• +5 more

Professor Johnny T. Ottesen is affiliated with Roskilde University's Department of Science and Environment Mathematics and Physics (IMFUFA), where he leads the Centre for Mathematical Modeling - Human Health and Disease. His research focuses on applying mathematical modeling to biomedical systems, particularly in hematology, immunology, and physiological processes. He has published extensively on topics including cancer dynamics, inflammation mechanisms, and clinical decision-support systems. Education background includes a PhD in mathematical modeling with a focus on biomedical applications. His work integrates mathematical analysis with clinical data to address challenges in personalized medicine, disease progression modeling, and systems biology. Notable contributions include models for hematopoietic stem cell dynamics, endotoxin-induced inflammation responses, and intracranial pressure regulation. His research outputs (132+ articles) emphasize interdisciplinary approaches, with recent work analyzing myeloproliferative neoplasms, kidney function biomarkers, and immunotherapy optimization. He actively collaborates internationally, organizing conferences like the 12th European Conference on Mathematical and Theoretical Biology and leading the Nordic Biomathematics community. Media engagements highlight his innovative 'mathematical microscope' methodology, which provides novel diagnostic tools for conditions like depression. Despite no listed awards, his work has received attention for bridging clinical and computational sciences through dynamic models predicting treatment outcomes and disease behavior. He has supervised numerous interdisciplinary projects and participates in initiatives like Greater Copenhagen Health Science Partners. His activities span peer review, academic leadership, and public engagement, emphasizing the translation of mathematical insights into clinical practice.

Dick BotteldoorenView profile

Professor

• Acoustic Modeling
• Noise Mapping
• Environmental Sensor Networks
• +8 more

Dick Botteldooren is a full Professor of Acoustics at Ghent University, Belgium, leading the WAVES (Wireless, Acoustics, Environment & Expert Systems) research unit. He serves as I-INCE vice-president for Europe and Africa and previously held leadership roles as Editor-in-Chief of Acta Acustica (2004-2013) and president of the Belgian Acoustical Society (until 2018). His educational background includes: MSc in Electronic Engineering (1986, Ghent University) PhD in Applied Science (1990, Ghent University) Professor Botteldooren's research spans acoustic modeling, noise mapping, environmental sensor networks, computational intelligence, and human-inspired machine listening. His work integrates biomonitoring (particularly EEG), health impact assessment of sound, urban sound planning, and soundscape design with strong policy implications. Recent focus areas include AI-driven analysis of animal vocalizations and therapeutic soundscape design for dementia care. Analysis of his 2021-2025 publications reveals three dominant trends: (1) Machine learning applications in bioacoustics (especially broiler chicken vocalization monitoring for welfare assessment), (2) EEG-based attention detection systems using spiking neural networks and cross-modal transfer, and (3) Soundscape augmentation for dementia care through auditory processing-driven environmental interventions. His work consistently bridges computational methods with real-world acoustic challenges. His scientific recognition includes: Fellow of the Acoustical Society of America Professor Botteldooren has advised national and international health councils and noise policymakers, translating research into practice. His work has received sustained funding from the Belgian National Fund for Scientific Research and other international bodies, supporting both fundamental acoustics research and applied policy development. The WAVES research unit under his leadership conducts interdisciplinary work combining wireless sensor networks, computational intelligence, and human-centered acoustics, with active projects in urban noise monitoring, bioacoustic surveillance, and neuroacoustic applications.

Xianwen KongView profile

Associate Professor

• Parallel Robots
• Reconfigurable Robots
• Mechanism Design
• +5 more

Dr. Xianwen Kong is an Associate Professor at the Institute of Mechanical, Process and Energy Engineering within the School of Engineering and Physical Sciences at Heriot-Watt University. He is an ASME Fellow and member of the Edinburgh Centre for Robotics. Dr. Kong has authored over 200 publications including a Springer monograph on parallel manipulators (with translations in Russian and Chinese) and holds two U.S. patents. He has secured multiple research grants from EPSRC and Innovate UK focusing on parallel robots and reconfigurable manufacturing systems. Research Focus Dr. Kong's research specializes in creative design methodologies for parallel and reconfigurable robots with applications spanning advanced manufacturing, renewable energy, and biomedical engineering. He developed systematic approaches for parallel manipulator design and pioneered disassembly-free reconfigurable parallel manipulators. Current projects include: Machine Learning-empowered Responsive Manufacture Of Industrial Laser Systems (EPSRC EP/V051164/1) Multiscale digital twin-driven smart manufacturing system (EP/T024844/1) Research Publication Trends Analysis of recent publications reveals strong focus on: type synthesis of variable-DOF mechanisms, kinematic analysis of parallel manipulators, reconfigurable robotic systems, and industrial applications including precision assembly and optical system alignment. Computational methods feature prominently with geometric modeling, screw theory, and machine learning approaches applied to mechanism design and robotic perception. Honors and Recognition 2024 ASME Leonardo Da Vinci Award 2020 ASME A.T. Yang Memorial Award in Theoretical Kinematics 2012 ASME Freudenstein/General Motors Young Investigator Award Multiple best paper awards at international robotics conferences Professional Service Dr. Kong serves as associate editor for leading journals including Mechanism and Machine Theory , IEEE Robotics and Automation Letters , and ASME Journal of Mechanisms and Robotics . He has chaired major conferences including ASME IDETC and organized the ASME/IEEE ReMAR conferences. As an elected member of ASME's Mechanisms and Robotics Committee, he contributes to the advancement of kinematic research.

Laura Luna CastilloView profile

Assistant Professor

• Digital Art
• Immersive Media
• XR/VR/AR
• +9 more

Laura Luna Castillo is an Assistant Professor in the Department of Digital Arts and Experimental Media (DXARTS) at the University of Washington. She holds a PhD in DXARTS (2024), an M.A. in Visual Arts from the University of Sussex (2017), and a B.A. in Fine Arts and Interactive Media from Teesside University (2015). Her work bridges multimedia art, technology, and performance, focusing on themes of memory, displacement, and the perception of space through immersive media, VR/AR, and generative processes. Research interests include the intersection of digital technologies with traditional craft, the documentation of domestic spaces through 3D scanning, and the creation of interactive installations that explore human migration and identity. Notable works include The Kaleidoscope of the Eternal Now (2020), awarded first place at Mov en Mov Festival, and Comprehension of Spaces (2019), showcased at Cube Fest. She has been a SHAPE 2016 artist and has collaborated internationally with institutions like EMPAC and Rensselaer Polytechnic Institute. Key awards include recognition at CYNETART, Unsound Krakow, and the Hello World Festival, alongside residencies at Kamiyama, Japan, and the Mexican Consulate in Montreal. Her work frequently combines motors, sensors, and algorithmic systems to create dynamic, audience-responsive environments. Current projects include From habit to in-habit , an expanded theater project exploring migration narratives through virtual doubles, and Production of the Ordinary , a participatory archive of everyday life using mobile 3D scanning.

• Control Systems
• Cybersecurity in Control Systems
• Distributed Optimization
• +3 more

Xiao Tan is a Postdoctoral Scholar Research Associate in Mechanical and Civil Engineering at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. Their research focuses on control systems, cybersecurity in control systems, distributed optimization, robotics, aerospace engineering, and safety-critical systems. Key research interests include developing secure control strategies under sensor attacks, designing safety filters for flight control systems, and advancing distributed optimization algorithms for multi-agent systems. Xiao Tan has also explored control barrier functions for safety verification in interconnected systems and human-in-the-loop planning for precision agriculture robotics. Recent publications emphasize computational efficiency in safe control, violation-free distributed optimization, and the application of control theory to aerospace and robotics challenges. Their work bridges theoretical control design with practical implementations in cyber-physical systems. Xiao Tan’s contributions span algorithm development, safety verification, and the integration of human interaction with automated systems. Current research trends highlight a focus on robustness, real-time implementation, and interdisciplinary applications of control systems in safety-critical domains.

Strahinja DosenView profile

Professor

• Rehabilitation Engineering
• Robotics
• Myoelectric Control
• +6 more

Strahinja Dosen is a Professor and Head of Research Group in the Department of Health Science and Technology at Aalborg University's Faculty of Medicine. His research focuses on neurorehabilitation systems, particularly in rehabilitation engineering, robotics, and human-machine interfaces. He holds a PhD in Biomedical Engineering from Aalborg University (2009) and serves as a Visiting Professor at the University of Novi Sad. His work addresses cutting-edge topics like myoelectric control, brain-machine interfaces, artificial sensory feedback, and functional electrical stimulation. Key projects include the development of closed-loop robotic prostheses and sensory feedback systems for amputees. Dosen has led over 17 research projects, including the PERSONIFY initiative on powered ankle prosthesis control and the DexterHand bionic prosthetics platform. With 216+ publications, his research emphasizes improving prosthetic control through electrotactile/haptic feedback, 5G-enabled bionic limbs, and stroke rehabilitation robotics. He collaborates internationally on neurorehabilitation technologies and has been featured in media for innovations like thought-controlled prosthetics and robotic rehabilitation systems. Grants and collaborations include EU-funded projects and industry partnerships. His team's work contributes to UN Sustainable Development Goals related to health and innovation. Dosen advises on 6 PhD students and actively participates in academic workshops and editorial roles in haptics and prosthetics.

• Visual Analytics
• Machine Learning
• Digital Geometry Processing
• +6 more

Dr. Gary KL Tam is a Senior Lecturer in the Department of Computer Science at Swansea University's School of Mathematics and Computer Science. He has been with Swansea University since 2012, initially as a Lecturer (2012-2018) and promoted to Senior Lecturer in 2018. He is based at The Computational Foundry on Bay Campus and is actively involved in research through the Visual Computing Group and RIVIC. Dr. Tam's research spans several key areas in computer science, with a strong focus on visual analytics, machine learning, and digital geometry processing. His work demonstrates expertise in analyzing multidimensional data, information retrieval, and pattern recognition. He has developed substantial research in 3D reconstruction techniques, point cloud processing, and their applications in medical imaging and urban modeling. His publication record shows a clear evolution from foundational work in 3D shape matching and non-rigid registration to current applications in medical diagnostics (particularly Chronic Kidney Disease classification), Welsh language processing (CymruFluency project), and industrial applications. Recent publications demonstrate strong interdisciplinary work bridging computer vision, machine learning, and healthcare applications. Best VAST Paper Award at VIS 2016 Conference for 'Analysis of Machine- and Human-Analytics in Classification' Excellence in Learning and Teaching Award (ELTA) from Swansea University (2018) Dr. Tam actively supervises numerous PhD students across diverse research topics including explainable AI for economic growth, 3D city reconstruction, medical diagnostics, and human-in-the-loop systems. He has secured multiple research grants totaling over £50,000 from sources including CHERISH-DE, EPSRC, and Swansea University funds, supporting projects in medical AI, Welsh language processing, and computational infrastructure. His research group maintains strong collaborations with Cardiff University, National University of Singapore, and various medical research institutions, focusing on applying advanced computational techniques to real-world problems in healthcare, language processing, and industrial applications.

• Machine Learning
• Causal Reasoning
• Mechanism Design
• +7 more

Dr. Shanfeng Hu is an Assistant Professor in the Department of Computer and Information Sciences at Northumbria University, UK. He obtained his PhD from the same department in 2020 and joined the faculty as a Lecturer immediately after. During his PhD (2018-2020), he worked as a Senior Data Scientist in the financial sector. His research focuses on machine learning, causal reasoning, and mechanism design, with funded projects in advanced manufacturing (Innovate UK KTP), supply chain optimization (Digital Catapult, Innovate UK ISCF), and digital health (EU Erasmus+, EU MSCA). Education: PhD in Computer Science (2020) from Northumbria University, specializing in Metric Representations for Shape Analysis and Synthesis. Research interests include computer vision applications (e.g., defect detection, pose estimation), predictive maintenance, inventory management, health monitoring systems, and human-in-the-loop machine learning. He has collaborated on projects involving 3D printing (KTP-funded), steel surface analysis, and elderly health monitoring. His recent work addresses challenges in digital transformation for manufacturing, integrating predictive maintenance with inventory systems, and developing explainable AI for control systems. Projects are supported by Innovate UK, EU programs, and Digital Catapult. Lead researcher on Innovate UK KTP project: 3D printed Models Contributions to UN Sustainable Development Goals through education and healthcare projects Labs/Teams: Collaborates with industry partners in manufacturing, healthcare, and robotics sectors through funded initiatives.

Iestyn PierceView profile

Professor

• Wireless Sensor Networks
• Optical Communications
• Control Systems
• +5 more

Professor Iestyn Pierce is a faculty member at Bangor University's School of Computer Science and Engineering, specializing in electronic engineering. His academic qualifications include a PhD in Wavelet Theory of Optical Pulse Propagation (1998) and an MEng in Electronic Engineering from the University College of North Wales (1994). He holds Chartered Physicist status from the Institute of Physics. His research encompasses numerical modeling of engineering systems, with current focus areas including: Design and implementation of distributed wireless sensor networks for environmental monitoring LoRaWAN deployments in remote ecosystems Hardware-in-the-loop simulation for low-carbon energy control systems Optical communications and nuclear power systems cybersecurity Publication analysis reveals consistent focus on optical communications (OFDM systems, laser dynamics), control systems (battery monitoring, grid management), and interdisciplinary applications (marine robotics, nuclear cybersecurity). Recent work shows increased emphasis on environmental monitoring technologies and industrial control security. Professor Pierce leads significant initiatives including the EU-funded SEEC nuclear power project (£4.6m) and the Global Wales Mekong Delta monitoring collaboration. He co-supervises international engineering student projects with institutions in Mexico, Switzerland, Hong Kong, and Vietnam, focusing on sustainable solutions. He chairs the Engineering Centre for North and Mid Wales, delivering engineering outreach programs, and co-chairs the Science panel for the Coleg Cymraeg Cenedlaethol, promoting Welsh-medium education. His team projects often explore sustainable product development through cross-border academic collaboration.

Ashwin VenkataramanView profile

Assistant Professor

• Operations Management
• Demand Prediction
• Choice Models
• +6 more

Ashwin Venkataraman is an Assistant Professor of Operations Management at the Naveen Jindal School of Management, University of Texas, Dallas. He holds a Ph.D. in Computer Science from NYU's Courant Institute, advised by Srikanth Jagabathula and Lakshminarayanan Subramanian. His research focuses on demand prediction, choice modeling, and machine learning applications in operations management and retail analytics. Education: Ph.D. in Computer Science (NYU, 2018); Master's and Bachelor's degrees not explicitly stated Research interests include nonparametric demand estimation, feature-based choice models, and leveraging unobserved factors in decision-making systems. His work spans commodity pricing forecasting, crowdsourcing system optimization, and educational technology platforms like CollectiveTeach. Recent articles explore advancements in tree logit models, stochastic preference frameworks, and data-driven demand prediction techniques. These contributions address scalability challenges in large-scale systems and improve accuracy through algorithmic innovations. Awards: Honorable Mention for INFORMS Dantzig Dissertation Award (2019), NYU GSAS Dissertation Fellowship (2017-18), Jacob T. Schwartz Fellowship (2015) His work integrates theoretical rigor with applied impact, including collaborations on retail analytics and commodity market forecasting. No explicit grant details or lab affiliations are mentioned, but contributions to the TreeLogitEstimation repository indicate active engagement in collaborative research.

Kevin Godin-DuboisView profile

Researcher

• Reinforcement Learning
• Human-AI Interaction
• Evolutionary Robotics
• +3 more

Kevin Godin-Dubois is a Researcher at the Faculty of Science, Vrije Universiteit Amsterdam (VU), with affiliations to the Network Institute. His work focuses on advancing artificial intelligence (AI) through interdisciplinary research, particularly in reinforcement learning, human-AI interaction, and evolutionary robotics. He leads projects involving modular frameworks for AI experiments and benchmark generators for agent prototyping. Research Interests: His primary areas include reinforcement learning frameworks, human-AI collaboration systems, neuroevolutionary techniques, and embodied evolution in robotics. His work bridges theoretical AI advancements with practical applications in socially adept agents and modular system design. Recent Trends: His 2024-2025 publications emphasize modular frameworks (e.g., SHARPIE and AMaze), which enable scalable experimentation and benchmarking of AI agents. Earlier work (2017-2020) explored long-term evolutionary dynamics in artificial ecosystems and plant communities, showcasing adaptability in changing environments. Collaborations: Active in international workshops (e.g., ALIFE 2024) and open-source projects (ci-group/revolve2), emphasizing reproducibility and community-driven AI development.

• Electrical Power Systems
• Renewable Energy Integration
• Microgrids
• +7 more

Dr. Augustine Egwebe is a Senior Lecturer in the School of Electronic and Electrical Engineering at Swansea University's Faculty of Science and Engineering. He specializes in electrical power systems, renewable energy integration with microgrids, energy management, modern control systems, and robotics. His work contributes significantly to Swansea University's research in sustainable energy systems and power electronics. Dr. Egwebe received his PhD and BEng degrees in Electrical and Electronic Engineering (EEE) from Swansea University. His academic career at Swansea progressed from Academic Teaching/Research Assistant (2016-2019), to Lecturer (2019-2021), and currently Senior Lecturer (2021-Present). He is a Fellow of the UK's Advance Higher Education Academy (FHEA) and a member of the Institute of Electrical Technology (IET). His research focuses on developing novel and cost-effective dynamic control and power electronics solutions for integrating renewable energy systems with microgrids. Key areas include: Electrical power systems and microgrid integration Renewable energy resource management Modern control systems and robotics applications Energy forecasting and real-time scheduling Electrical machines modeling and control Power electronics interface design His recent publications demonstrate a strong focus on power systems stability, microgrid control strategies, and renewable energy integration. The research shows increasing sophistication in control algorithms for power electronics interfaces and growing interest in machine learning applications for energy prediction, particularly in photovoltaic systems and small spacecraft power management. Professional recognition includes: Fellow of the UK's Advance Higher Education Academy (FHEA) Active membership in the Institute of Electrical Technology (IET) Regular reviewer for academic transactions in his field As an educator, Dr. Egwebe supervises multiple PhD and MSc students, with recent completions in solar energy forecasting, microgrid energy management, and power electronic control techniques. He teaches core engineering modules including EG-243 Control Systems, EG-241 Electrical Machines, and developed the EGA222 Electrical Machines Laboratory module using Arduino-based hardware-in-the-loop experiments. He champions technology-enhanced learning to inspire lifelong learning among students.

• Electroacoustic music
• Composition
• Live performance with electronics
• +6 more

Simon Emmerson is a Professor in Music, Technology & Innovation at De Montfort University’s Leicester Media School , with a career spanning nearly five decades. He founded the Electroacoustic Music Association of Great Britain (EMAS) and served on Sonic Arts Network/Sound and Music boards. His DAAD Edgard Varese Visiting Professorship at TU Berlin and Silver Jubilee Visiting Professorship at Western Australian Academy of Performing Arts highlight his global influence. Current research student supervisor at DMU Co-PI on AHRC-funded project New Multimedia Tools for Electroacoustic Music Analysis Editorial Board member for Organised Sound , Radical Musicology , and Journal of Sonic Studies His research focuses on electroacoustic music’s live performance practices, spatial composition, gender dynamics in electronic music institutions, and machine-human listening symbiosis. He pioneered ‘concert installation’ formats like Aeolian , where looping structures create non-linear temporal experiences. Key publications include foundational texts The Language of Electroacoustic Music (1986), Living Electronic Music (2007), and The Routledge Research Companion to Electronic Music (2018). His AHRC-supported project (2010-2013) produced innovative analysis tools for hybrid genres. Scientific contributions: 2019 Oxford Handbook chapter on imagination in performance 2018 ICLI collaboration on crossadaptive processing 2016 EMAS institutional history analysis 2015 Organised Sound article on machine listening 2007 Living Electronic Music monograph As composer, he has created over 50 electroacoustic works performed at festivals in Paris, Berlin, Lisbon, and Birmingham. His advising includes supervising PhD/Masters students at DMU, though specific names aren’t listed. He maintains active performance presence with concerts in 2020 celebrating his 70th birthday.

• Evolutionary Computation
• Swarm Robotics
• Optimisation Algorithms
• +4 more

Professor Emma Hart is a leading academic at Edinburgh Napier University , affiliated with the School of Computing Engineering and the Built Environment and the Centre for Algorithms, Visualisation and Evolving Systems . Her research focuses on evolutionary computation , swarm robotics , and optimisation algorithms , with applications in ecology, cybersecurity, and AI-driven design. Education: 1 st Class Honours in Chemistry (Oxford), MSc and PhD in AI (Edinburgh) Leadership: Former Editor-in-Chief of Evolutionary Computation (MIT Press, 2017–2023), ACM SIGEVO Board member, and key contributor to Scotland’s AI Strategy (2021). Her research spans evolutionary robotics, lifelong learning systems, and explainable AI. Recent work includes using novelty search to engineer diverse robot swarms, XAI for algorithm configuration, and LLM-evolved heuristics for bin packing. She explores fitness landscapes and attractor analysis to improve optimisation model robustness. Scientific Awards include the ACM SIGEVO Outstanding Contribution Award (2023) Fellow of the Royal Society of Edinburgh (2022) Bronze Humies Award (2018) Best Paper Award@GECCO 2019 She supervises PhD students such as Grant Anderson Kirsty Montague Kelly Hunter Magnus Janson Fiona Stewart and has led over £2M in grants, including EPSRC , Innovate UK , and EU projects on autonomous robot evolution and lifelong learning systems.

Andrea De LorenzoView profile

Associate Professor

• Evolutionary Computation
• Machine Learning
• Computer Security
• +3 more

Andrea De Lorenzo is an Associate Professor of Computer Engineering at the University of Trieste. His research focuses on evolutionary computation, machine learning, computer security, information extraction, and natural language processing. He has authored over 40 peer-reviewed publications and holds an h-index of 15, with over 700 citations in the last five years (as of 2022). Education: PhD in Information Engineering, University of Trieste (2014) MEng in Computer Engineering, University of Trieste (2010) BSc in Computer Engineering, University of Trieste (2006) Research interests include applying machine learning to engineering problems, genetic programming for algorithm design, and cybersecurity. Notably, he won the Silver Medal at the 13th Human-Competitive Awards (2016) for human-competitive results in genetic and evolutionary computation. Teaching: He has taught courses such as 'Basi Di Dati' (Database Systems), 'Programmazione Web' (Web Programming), and 'Introduction to Machine Learning' since 2020. Recent courses include 2025 iterations of these subjects. Awards: 2016: Silver Medal at 13th Human-Competitive Awards Grants and Labs: No specific grants or labs mentioned, but his work involves collaboration with international journals and conferences on evolutionary computation.