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Elies DekoninckView profile

Senior Lecturer

• Design Creativity
• Product Development
• Innovation
• +4 more

Dr Elies Dekoninck is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, where she has been employed since 2004. She holds a PhD in Eco-innovation from an unspecified institution, completed in 2003 following industrial experience as a Design Strategy consultant. Her academic leadership includes developing and directing the MEng in Integrated Design Engineering (IDE), which integrates mechanical, electronic, and software engineering through studio-based projects. Research Focus: Her interdisciplinary research spans: Design creativity methodologies and innovation processes User-centered eco-design and sustainable product development Spatial augmented reality applications in co-creative design Human-robot collaboration frameworks for Industry 5.0 Inclusive design principles for neurodivergent populations Research Projects & Grants: Principal Investigator for Horizon 2020 SPARK project on spatial augmented reality in design sessions Led EU project G.EN.ESI on eco-innovation tools and AHRC-funded game-design project resulting in commercial product 'Beasts of Balance' Managed 5 Knowledge Transfer Partnerships (KTPs) with industry partners Secured funding from Arts and Humanities Research Council, EU Horizon 2020, and Designability Academic Contributions: Supervised multiple PhD students in areas including virtual design teams and eco-design Authored 114+ research outputs including journal articles, conference papers, and patents Associated with research centers: The Foundry (Digital Manufacturing & Design), IAAPS (Augmented Human), Centre for Sustainable Energy Systems, and Centre for Regenerative Design

Christof LutterothView profile

Professor

• Human-Computer Interaction
• Virtual Reality
• Eye-Gaze Interaction
• +5 more

Christof Lutteroth is a Professor in the Department of Computer Science at the University of Bath and Director of the REal and Virtual Environments Augmentation Labs (REVEAL). His work focuses on Human-Computer Interaction (HCI) with emphasis on eye-gaze interaction and virtual reality (VR), particularly for health, exercise, and learning applications. He leads multiple research projects funded by organizations like EPSRC, The British Academy, and The Royal Society. Research Interests include developing gaze-controlled interfaces, immersive VR systems, and adaptive UI/UX for fitness and cognitive training. He explores affective design tools, emotion recognition in VR exergaming, and biometric data analysis for health applications. Recent Publications highlight advancements in gaze-based text entry, emotion measurement in VR, AI-driven UI development, and cross-European XR innovation networks. His work spans from foundational HCI methodologies to applied projects in rehabilitation and immersive learning. Grants include EPSRC IAA, British Academy, and Royal Society funding for projects like TapGazer, Hyper-immersive XR, and Affective Design Tools for VR. He collaborates with institutions across Europe through the EMIL project. Laboratory : REVEAL Lab at the University of Bath drives research in immersive technologies, motion analysis, and augmentation of human interaction with digital environments.

Daniel B. VigneronView profile

Professor

• Molecular Imaging
• Hyperpolarized Carbon-13 MRI
• Metabolic Imaging
• +5 more

Daniel B. Vigneron, PhD is a Professor at the University of California, San Francisco (UCSF) Department of Radiology and Biomedical Imaging. He serves as Director of the Hyperpolarized MRI Technology Resource Center (HMTRC), Director of Human Imaging Core Services, Director of Advanced Imaging Technologies SRG, and Operations Director of the Surbeck Laboratory for Advanced Imaging. As a core member of the UCB/UCSF Graduate Group in Bioengineering, Vigneron has established himself as a leader in molecular imaging research with over three decades of experience at UCSF. Vigneron's research focuses on developing advanced functional and metabolic MRI techniques, particularly hyperpolarized carbon-13 technology, for studying prostate cancer, brain tumors, and other diseases. His work enables non-invasive imaging of metabolic processes, allowing clinicians to monitor therapy effectiveness and guide treatments. The HMTRC, which he founded in 2011 with NIH funding and recently secured a 5-year renewal for, has supported 20 external projects domestically and 15 internationally, produced 239 publications, and trained 149 researchers. Vigneron's lab develops novel coil and software techniques for high-field MRI, MR spectroscopy, and diffusion imaging at 3T and 7T for studying brain, prostate cancer, and other organs. His recent publications demonstrate a clear trajectory toward clinical translation of hyperpolarized carbon-13 MRI across multiple organ systems. The research spans abdominal imaging with advanced denoising techniques, cardiac metabolism studies, whole-brain coverage applications, and cerebral perfusion analysis. This work represents a significant shift from basic science toward practical clinical applications in oncology, cardiology, and neurology, with particular emphasis on standardization for multi-center studies. Scientific Awards: 2022 Outstanding Faculty Mentoring Award from UCSF Department of Radiology and Biomedical Imaging Vigneron has mentored 149 trainees throughout his career, with several former students now serving as faculty members including Duan Xu, Peder Larson, and Susan Noworolski. As Principal Investigator overseeing eight grants, he has secured significant NIH funding for the HMTRC and other research initiatives. His administrative leadership extends to co-chairing the department's Safety and Compliance Committee, where he has helped establish robust safety protocols for PET-MR programs. Vigneron's mentoring philosophy emphasizes adapting to individual needs at different career stages, moving from instructor to coach to manager to cheerleader as trainees progress. The Vigneron Lab, located in Byers Hall on the UCSF Mission Bay campus, operates within the Surbeck Laboratory for Advanced Imaging. The lab group develops novel acquisition techniques and hardware for multinuclear MR spectroscopy, with particular focus on hyperpolarized carbon-13 metabolic imaging. The HMTRC serves as a hub for team science, bringing together researchers from diverse disciplines to advance metabolic imaging technology and its clinical applications.

• Hydrological uncertainty
• Climate change impact on hydrology
• Remote sensing applications
• +6 more

Professor Ashish Sharma is a Professor of Hydrology and Water Resources in the School of Civil and Environmental Engineering at the University of New South Wales, Sydney, Australia. With a PhD in Civil Engineering from Utah State University and extensive experience in hydrological research, he has established himself as a leading expert in his field. Dr. Sharma's research focuses on hydrological uncertainty, with particular emphasis on the impact of climate change and variability on hydrological practice. His work spans multiple areas including remote sensing applications, stochastic hydrological modeling approaches, development of hydrological models, and addressing key hydrology challenges such as design flood estimation and water resources management. He has made significant contributions to understanding how climate change affects hydrological extremes and water availability. His publications reveal a strong trend toward advanced modeling techniques for climate change impact assessment, with recent work focusing on spectral transformation methods, multivariate bias correction in climate models, flood forecasting improvements, and the relationship between temperature and precipitation extremes. His research increasingly integrates remote sensing data with hydrological modeling to address challenges in data-scarce regions. Professor Sharma has held significant leadership positions including President of the International Commission of Hydrologic Sciences (IAHS) Commission on Statistical Hydrology (STAHY) since 2016, service on the Australian Research Council's College of Experts twice, and participation on the Technical Committee for the Australian Rainfall and Runoff Design Flood Estimation guidelines (ARR2016). In addition to his research leadership, Professor Sharma actively mentors students and collaborates with researchers globally, as evidenced by his extensive publication record across top hydrology and climate journals. His work bridges theoretical hydrology with practical applications for water resources management under changing climate conditions.

Nicholas BrakeView profile

Associate Professor

• Civil Engineering
• Materials Science
• Recycled Concrete Aggregate (RCA)
• +7 more

Dr. Nicholas Brake is an Associate Professor at Lamar University's Department of Civil and Environmental Engineering, focusing on reclaimed materials, wireless power transfer applications in concrete, and fatigue fracture modeling for pavements. His research spans recycled concrete aggregate, coal ash utilization, and electromagnetic cementitious composites. Education: Ph.D., M.S., B.S. in Civil Engineering from Michigan State University Awards: Anita Riddle Fellowship (2018), Lamar Merit Award (2018), Presidential Faculty Fellowship (2015), and multiple scholarships during his studies. His research emphasizes three key areas: 1) Material reclamation using recycled concrete aggregate, coal combustion residuals, and EAF slag. 2) Electromagnetic transport properties for wireless vehicle charging applications. 3) Fatigue damage modeling in concrete pavements. Through 3D printing integration and design-build-test pedagogy, he enhances student learning outcomes. Recent publications focus on international engineering education (2020), magnetic concrete composites (2019), and advanced testing methodologies for civil infrastructure (2018). His teaching innovation includes developing nine Lamar University courses with active learning strategies that improved student design confidence (p Scientific Awards: Anita Riddle Excellence in Teaching Fellowship (2018) Presidential Faculty Fellowship for Teaching Innovation (2015) Outstanding Teaching Assistant Award at Michigan State (2011) Dr. Brake mentors undergraduate and graduate researchers, including doctoral candidates Mahdi Feizbahr and Hossein Hariri Asli (2023-2024). His lab (LUMS) houses advanced testing systems like Instron 5965/8803, MTS Insight 100SL, and thermal analyzers for material characterization.

• Machine Learning
• Bayesian Inference
• Probabilistic Machine Learning
• +17 more

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.

Rui Pedro Figueiredo MarquesView profile

Professor

• Information Systems for Business
• Artificial Intelligence in Auditing
• Blockchain Applications
• +6 more

Rui Pedro Figueiredo Marques is a Professor at the Higher Institute of Accounting and Administration, University of Aveiro, where he teaches Information Systems across technical, bachelor's, master's, and doctoral programs. He serves as course director for the Professional Higher Technical Course in Organizational Informatics and Communication and holds a board position at the Institute of Accounting and Administration, University of Aveiro. As a Full Researcher at GOVCOPP's Competitiveness, Innovation and Sustainability (CIS) group, his work focuses on Information Systems for Business, with recent emphasis on AI, Blockchain, and Business Intelligence applications in auditing and accounting contexts. Marques' academic credentials include a Ph.D. in Computer Science (2014, Universities of Minho/Aveiro/Porto), a Master's degree (2008), and a Bachelor's in Electronics and Telecommunications Engineering (2005, University of Aveiro). He has authored/co-authored over 50 publications, including journal articles, conference papers, and book chapters on topics ranging from ERP systems in auditing to digital transformation in low-density territories. He is editor-in-chief of the International Journal of Business Innovation and actively participates in funded research projects addressing governance, competitiveness, and public policies. His research explores intersections between technology and business practices, with notable contributions to AI in auditing, blockchain's role in financial transparency, and sustainable development frameworks for social economy entities. Notable projects include evaluations of ERP systems' impact on internal audit maturity and frameworks promoting accountability in private social solidarity institutions. Marques' work frequently emphasizes practical applications of technology in audit processes, education, and public sector modernization. He collaborates with institutions like the Portuguese Social Solidarity Sector and has advised on digital transformation strategies for tourism and hospitality industries.

Rajeev BalasubramonianView profile

Professor

• Computer Architecture
• Memory Systems
• DRAM/NVM Technologies
• +7 more

Rajeev Balasubramonian is a Professor and Associate Director at the School of Computing, University of Utah. He specializes in computer architecture, with a focus on memory systems, emerging technologies, and energy-efficient computing. His research addresses challenges in DRAM/NVM architectures, security, and acceleration for big data and machine learning workloads. Education: PhD in Computer Science (University of Rochester, 2003), M.S. (University of Rochester, 2000), B.Tech in Computer Science (IIT Bombay, 1998). Research Interests: Memory reliability, near-data processing, cache hierarchies, transactional memory, and hardware-software co-design for emerging technologies. He has led projects on crossbar accelerators, secure memory systems, and resistive memory architectures. Recent Trends in Publications: Focus on encrypted inference (Hyena), data prefetching (PATHFINDER), and neuromorphic computing (SpinalFlow). His work bridges hardware and software, emphasizing practical acceleration and security solutions. Awards: IEEE Fellow (2021), Google Faculty Awards (2019/2020), Intel Research Award (2017), and multiple best paper awards (ISCA, ISPASS, PACT). Grants & Students: Over $4M in NSF/industry funding. Advised 15+ PhD students (e.g., Ali Shafiee, Karl Taht) and currently mentors researchers in resistive memory and security accelerators. His lab includes teams like Utah Arch Research Group. Labs & Teams: Leads the Utah Arch Research Group , organizing workshops on near-data processing and memory systems (e.g., ISCA, HPCA).

Brian IngallsView profile

Professor

• Systems Biology
• Synthetic Biology
• Mathematical Modeling
• +3 more

Brian Ingalls is a Professor in the Department of Applied Mathematics and cross-appointed to Biology at the University of Waterloo. His research applies mathematical and control-theoretic approaches to biological systems, including genetic regulatory networks, microbial communities, and cellular metabolism. Institutional Affiliation: Faculty of Mathematics, University of Waterloo Contact: bingalls@uwaterloo.ca His work focuses on systems biology and synthetic biology , particularly sensitivity analysis of biochemical networks, optimal experimental design, and mathematical modeling of cellular processes. Research funding comes from NSERC and CIHR . Notable contributions include the textbook Mathematical Modeling in Systems Biology (MIT Press, 2013) and the Ingalls Quantitative Cell Biology Lab , which investigates intracellular and intercellular network dynamics through computational and experimental methods. Key Collaborations: iGEM Waterloo, Chemical Engineering, and international synthetic biology networks Advising: Mentored 15+ graduate students and postdocs across applied math, biology, and engineering fields

Nikolaus KriegeskorteView profile

Professor

• Computational Neuroscience
• Artificial Neural Networks
• Visual Perception
• +3 more

Nikolaus Kriegeskorte is a Professor of Psychology and Neuroscience, and Director of Cognitive Imaging at the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University. He is affiliated with the Departments of Psychology, Neuroscience, and Electrical Engineering. Institution: Columbia University Academic Roles: Professor of Psychology and Neuroscience; Director of Cognitive Imaging Email: nk2765@columbia.edu Location: Jerome L. Greene Science Center, 3227 Broadway, L3-064 Research Focus: The lab explores the cognitive neuroscience of vision, modeling biological visual systems with artificial neural networks. Key areas include developing statistical inference and visualization techniques to bridge theory and experimental data, understanding representational geometry in neural systems, and optimizing deep learning frameworks for neuroscience. Recent Publications: Highlighted work spans neural network modeling of visual perception, representational similarity analysis, and the topology of brain representations. The lab's methods, such as the TorchLens Python package, enable transparent extraction and visualization of hidden layer activations in neural networks. Grants: Projects are supported by funding from the National Science Foundation (NSF) - Cognitive Neuroscience and the National Institutes of Health (NIH) - NIMH. Laboratory: The Visual Inference Lab (kriegeskortelab.zuckermaninstitute.columbia.edu) is located at Quad 3D, Zuckerman Institute, 3227 Broadway.

Michael BritoView profile

Lecturer

• Digital Marketing
• Social Media Strategy
• Brand Communications
• +12 more

Michael Brito is a Lecturer in Mass Communications and Social Media at the School of Journalism and Mass Communications, College of Humanities and the Arts, San José State University. He is also a seasoned industry leader, currently serving as the Global Head of Data + Intelligence at Zeno Group, where he leads a 50-member analytics team supporting global clients in B2B, consumer, technology, and healthcare sectors. His academic and professional work bridges digital marketing, brand strategy, and data-driven communications. Michael’s research interests include digital marketing, social media strategy, brand communications, narrative intelligence, audience segmentation, and AI applications in PR. He is a recognized thought leader with extensive publications and blog posts exploring brand archetypes, earned media, customer engagement, and the future of digital storytelling. His work emphasizes the integration of data analytics into strategic communications to enhance brand visibility and audience connection. The trends in his recent articles reflect a strong focus on artificial intelligence in public relations, media intelligence, narrative analysis, and the evolution of digital customer journeys. His writings analyze tools like Pulsar and Cision, explore generative AI in search, and critique traditional metrics like earned media value, advocating for more sophisticated, insight-driven approaches. Top 50 Social Intelligence Pioneers by The Social Intelligence Lab Dashboard 25 Class of 2022 by PRWeek Top 25 Digital PR Innovators by PRovoke Media Michael Brito mentors students in digital communications and advises on strategic brand development. He has led major initiatives in media monitoring, social intelligence, and data-informed PR outreach. He founded and contributes to a widely-read blog on social media marketing and is a frequent speaker at industry events, including TEDx. He is also a proud U.S. Marine veteran, bringing leadership and discipline to his academic and professional roles. He is actively involved in the COMM+ lab at SJSU and supports student media through his teaching and mentorship. His work continues to influence both academic curricula and industry best practices in digital communications and brand analytics.

Alexandros DaglisView profile

Associate Professor

• Rack-Scale Computing
• Network-Compute Integration
• Low-Latency Datacenter Architecture
• +5 more

Alexandros Daglis is an Associate Professor of Computer Science at the Georgia Institute of Technology, with an adjunct appointment in the School of Electrical and Computer Engineering. His research focuses on blurring boundaries between network and compute for high-performance, scalable microsecond-scale services in datacenters, particularly through network endpoints and memory-centric computing. Primary Affiliation: Georgia Tech College of Computing, School of Computer Science Adjunct Affiliation: School of Electrical and Computer Engineering Key research areas include: Rack-scale computing and network-compute co-design CXL-based memory systems Low-latency datacenter architectures Transactional memory and concurrency control Edge-cloud continuum and geo-distributed infrastructures He has received prestigious awards including the NSF CAREER Award, Google Faculty Research Award, and Georgia Tech's Outstanding Junior Faculty Teaching Award. His students include Marina Vemmou (network-compute co-design), Albert Cho (memory system design), and Peidi Song (microsecond-scale scheduling). Grants: NSF, IARPA, Intel, Samsung Teaching: High Performance Computer Architecture, Systems and Networks, Datacenter Design

Anomadarshi BaruaView profile

Assistant Professor

• System Design and Security
• Healthcare Assistive Systems
• Industrial Control Systems (ICS)
• +5 more

Anomadarshi Barua is an Assistant Professor in the Department of Cyber Security Engineering at George Mason University, leading the System Design and Security research group. His work spans hardware-software co-design for securing cyber-physical systems (CPS), robotics, and sensors. Prior Affiliation: PhD from University of California, Irvine (2023) Industry Experience: Intel Corporation, Solidigm, Nordic Semiconductor, IDEAS Research Themes: Focuses on multimodal system security (audio, visual, electromagnetic data), analog-digital signal integrity, and quantum-inspired defenses in CPS. Key applications include healthcare systems, smart grids, and industrial control systems (ICS). Recent ACSAC 2024 paper acceptance Best Paper Award at ACSAC 2022 NSF panel reviewer (2024) Labs & Collaborations: Collaborates with University of Louisville on robotics and works on Commonwealth-funded UG research (2024). Publications in ACM CCS, USENIX, CHES, and IEEE Transactions (TDSC, TIFS).

Andrea BurattinView profile

Associate Professor

• Process Mining
• Business Process Management
• Petri Nets
• +6 more

Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.

Alejandro VillaverdeView profile

Research Professor

• Systems Biology
• Control Theory
• Mathematical Modeling
• +5 more

Alejandro F. Villaverde is a Ramón y Cajal research fellow in the Department of Systems & Control Engineering at the School of Industrial Engineering, University of Vigo, Spain. He also serves as a Research fellow at CITMAga since 2022. Previously, he worked as a postdoctoral researcher at IIM-CSIC from 2016-2020. His research focuses on the modeling of dynamical systems with particular emphasis on biological applications. Villaverde earned his PhD in Systems and Control Engineering from University of Vigo between 2005 and 2009. His academic career has centered at Spanish institutions with a strong interdisciplinary approach bridging engineering, mathematics, and biology. His primary research interests include systems biology, control theory, and mathematical modeling, with specialized expertise in structural identifiability, observability analysis, and computational tools for dynamic modeling of biological systems. Villaverde's work addresses fundamental challenges in building reliable mathematical models of complex biological processes, with applications spanning immunology to microbial communities. His theoretical contributions have practical implications for improving model reliability and predictive power in biological research. Villaverde has published extensively in top journals including PLOS Computational Biology, Bioinformatics, and IEEE/ACM Transactions on Computational Biology. His recent publications (2023-2025) reveal a consistent research trajectory focused on developing theoretical frameworks for biological model analysis, creating practical software tools, and applying these methods to cutting-edge problems. His work shows particular strength in identifying and addressing fundamental limitations in modeling approaches, especially regarding parameter identifiability and model observability constraints. Among the top 2% Scientists Worldwide 2024 (Stanford University list) Recognition as one of the EEI's top valued instructors at University of Vigo's School of Industrial Engineering Villaverde leads multiple significant research projects including DYNAMO-bio (funded by Ministry of Science, Innovation and Universities), SICOMORO (focusing on symmetries in biological communities), and PREDYCTBIO. His group actively develops open-source software tools such as STRIKE-GOLDD for structural identifiability and observability analysis. The laboratory, part of the BICO research group, includes several researchers and students working on various aspects of dynamic modeling in biology, with recent additions including Mahmoud Shams Falavarjani, Adriana González Vázquez, and multiple interns working on specialized projects.