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Ewan PearsonView profile

Clinical Professor

• Type 2 Diabetes
• Monogenic Diabetes
• Pharmacogenetics
• +7 more

Ewan Pearson is a Clinical Professor of Diabetic Medicine at the University of Dundee, with adjunct and visiting roles at the University of Lund and University of Edinburgh. He serves as an Honorary Consultant in Diabetes and Endocrinology at Ninewells Hospital and Medical School and leads the BHF Data Science Centre’s Diabetes Data Catalyst. Doctor of Medicine (PhD), Peninsula Medical School (2005) Wellcome Trust Clinical Training Fellowship, University of Exeter Chief Scientist Office Clinician Scientist Fellowship in Dundee Research Interests: Ewan focuses on phenotypic and genotypic determinants of drug response in diabetes , especially metformin and sulfonylurea , and stratified approaches to diabetes management . He leads the IMI-DIRECT project on type 2 diabetes stratification and the £2.8M iDiabetes programme for precision care in Tayside. Recent Articles highlight trends in precision diabetes treatment , including AI-driven drug response prediction , metformin pharmacogenetics , and cardiovascular risk stratification in type 2 diabetes. Collaborative projects like SOPHIST and ADMISSION address multimorbidity and obesity outcomes . Scientific Awards include the EASD Minkowski Award (2017), Diabetes UK Dorothy Hodgkin Lecture (2020/2021), and Fellowship of the Royal Society of Edinburgh (2022). He received multiple Diabetes UK/Servier Type 2 Diabetes Research Awards (2003, 2006, 2007). Grants and Leadership: Ewan co-chaired the Wellcome Early Career Awards Committee and holds major grants from the Wellcome Trust , Health Data Research UK , and Juvenile Diabetes Research Foundation . His public engagement includes Cafe Science Dundee and Discovery Days presentations.

Patrick SkebaView profile

Academic

• Internet Privacy
• Artificial Intelligence
• Data Ethics
• +3 more

Patrick Skeba is a Teaching Assistant Professor at the University of Pittsburgh's Department of Computer Science within the School of Computing and Information. He holds a PhD in Computer Science from Lehigh University (2022) and bachelor's degrees in Cognitive Science and Computer Science from Johns Hopkins University (2017). His research focuses on internet privacy, AI ethics, and the responsible use of data. He teaches courses in machine learning and programming. Research Interests: Skeba's work bridges technology and societal impact, emphasizing privacy risks in data systems, algorithmic fairness, and user-centric privacy frameworks. His recent studies explore informational friction in data collection, community-based privacy strategies, and lay-expert disparities in understanding privacy-enhancing technologies (PETs). Publications: His articles analyze privacy dynamics in digital spaces, from pandemic-era discourse on r/privacy to methodological approaches for categorizing technology non-use. His earlier work includes breakthroughs in sleep disorder diagnostics, particularly periodic leg movement (PLM) analysis and telemedicine applications for neurological conditions. Awards: No scientific awards listed. Grants and advising details are currently unspecified. Labs/Teams: No specific lab affiliations mentioned in provided materials. His teaching and research emphasize collaboration across computational and social domains.

Ross OttoView profile

Associate Professor

• Behavioral Neuroscience
• Cognition
• Cognitive Neuroscience
• +3 more

Ross Otto is an Associate Professor in the Department of Psychology at McGill University. He holds an office at 2001 McGill College, 711, and can be reached via email at ross.otto@mcgill.ca. His research focuses on understanding the mechanisms underlying reflective versus reflexive decision-making, particularly how cognitive resources, stress, and contextual factors influence effort-based choices. He employs computational modeling, behavioral experiments, and neuroimaging techniques. Notable contributions include studies on stress-induced cognitive avoidance and the neural correlates of effort evaluation. His work is affiliated with the Otto Lab, and he collaborates widely across disciplines such as neuroscience and behavioral economics.

• Physical Chemistry
• Theoretical and Computational Chemistry
• Chemical Engineering
• +6 more

Professor George Jackson, FRS, holds the position of Professor of Chemical Physics at the Department of Chemical Engineering, Imperial College London (since 2001), and has affiliations with multiple institutions including the University of Sheffield and Cornell University. His academic career spans roles from Lecturer (1989–1994) to Reader (1994–2001) in Physical Chemistry and Chemical Physics. He leads the Molecular Systems Engineering group and chairs the journal Molecular Physics . Research focuses on theoretical and computational chemistry, thermodynamics, and fluid phase equilibria. Key contributions include the SAFT (Statistical Associating Fluid Theory) equation of state, applied to CO2 capture, polymer physics, and pharmaceutical processes. He has pioneered models for electrolytes, solvents, and complex fluids, emphasizing sustainability and industrial applications. Notable accolades include the Rossini Award (2023), Fellowship of the Royal Society (2020), and the Bakhuis Roozeboom Medal (2019). His work has been recognized through Imperial College's President's Medal (2016), the Guggenheim Medal (2014), and over 400 citations in Google Scholar. Collaborations span institutions globally, including the Sargent Centre for Process Systems Engineering and the Thomas Young Centre. Current initiatives include the HiRECORD project for CO2 capture technology scaling and the development of phase-change solvents. His research integrates molecular simulation, process design, and sustainability assessment, addressing challenges in energy, environment, and pharmaceuticals.

Tim ColoniusView profile

Professor

• Fluid Dynamics
• Cavitation and Bubble Dynamics
• Aerodynamic Sound
• +5 more

Tim Colonius is the Frank and Ora Lee Marble Professor of Mechanical Engineering and Medical Engineering and holds the Cecil and Sally Drinkward Leadership Chair at the California Institute of Technology. He has been affiliated with Caltech since 1994 and currently serves as Executive Officer for Mechanical and Civil Engineering . Colonius earned his B.S. from the University of Michigan (Ann Arbor), and both his M.S. and Ph.D. from Stanford University. Research Interests: His work focuses on fluid dynamics (global instabilities, cavitation, aerodynamic sound), flow control (closed-loop control, reduced-order modeling), and biomedical applications (shock waves, lithotripsy, ultrasound). He also develops advanced numerical methods for interface capturing, immersed-boundary techniques, and high-order accuracy. Scientific Contributions: Recent publications highlight his research in multiphase flows, vortex ring collisions, turbulent jet analysis, GPU-accelerated simulations, and biomedical applications. His group uses computational and data-driven approaches to study turbulence, instabilities, and flow optimization. Scientific Awards: AIAA Aeroacoustics Award Fellow of the Acoustical Society of America Fellow of the American Physical Society (APS) NSF and DoD research grants

• Decarbonization of Built Environments
• Bio-Based Materials Engineering
• Structural Systems Optimization
• +3 more

Dr. Bhavna Sharma is an Associate Professor and Director of the Chase L. Leavitt Master of Building Science Program at the USC School of Architecture. Her work focuses on decarbonization, bio-based materials innovation, and sustainable healthcare infrastructure. She leads the Keck USC Sustainable Healthcare Initiative (KUSHI) to advance environmentally conscious healthcare systems. Dr. Sharma holds a Ph.D. in Civil and Environmental Engineering from the University of Pittsburgh, with additional degrees in Art History and Architecture. Her research spans structural systems optimization from material harvesting to building-scale applications, emphasizing bio-composites like bamboo and timber. She co-chairs USC's Presidential Working Group on Sustainability, contributing to Assignment: Earth climate goals. Courses taught include seismic design, structural systems, and building science integration. Key research areas include lifecycle assessment in healthcare, seismic-resistant designs, and interdisciplinary standards for non-conventional materials. Her work bridges material science, architectural practice, and policy to address global sustainability challenges.

• Digital Hardware Design
• Reliability Engineering
• Reconfigurable Devices
• +3 more

Eleonora Vacca is a PhD student and Research Fellow in the Department of Automatic Control and Computer Science (DAUIN) at the Polytechnic University of Turin. She holds a B.S. in Electronic Engineering from the University of Palermo (2018) and an M.S. in Electronic Engineering-Embedded Systems from Politecnico di Torino (2021). Her research focuses on digital hardware design, reliability engineering, reconfigurable devices, and AI applications in aerospace and safety-critical systems. She is a member of the Aerospace and Safety Computing Lab and the CAD - Electronic CAD & Reliability Group (DAUIN). Her work addresses challenges such as radiation effects mitigation in space missions, fault-tolerant AI accelerators, and real-time anomaly detection in satellite telemetry. She has contributed to projects like the RAMSES CubeSat-1 Development (2025-2026), funded by commercial contracts. In 2024, she won the Best Student Paper Award at the NEWCAS Conference for her research on radiation effects in space missions. Vacca collaborates on teaching, including assisting in the course 'Electronic Calculators' for Computer Engineering students. Her recent publications explore AI resilience in RISC-V ecosystems, radiation environment analysis for space missions, and gesture recognition systems for smart cities. She actively contributes to conferences such as the ACM International Conference on Computing Frontiers and the IEEE International Smart Cities Conference.

• Algorithm Theory
• Algorithms and Data Science
• Economics and Computation
• +6 more

Stefano Leonardi is a Full Professor in the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza Università di Roma. His research focuses on Algorithm Theory, Algorithms and Data Science, and Economics and Computation. He leads the ERC Advanced Grant project AMDROMA, exploring algorithmic mechanisms for online markets. He has held roles as Conference Chair for STOC 2021, WWW 2015, and FUN 2018, and coordinates the Sapienza School of Advanced Studies (2016-2018). His work spans approximation algorithms, online algorithms, and mechanism design. Awards include the ERC Advanced Grant and EATCS Fellowship. His research interests emphasize foundational algorithmic problems in web-based markets, leveraging rigorous design and large-scale data analysis. Recent projects include ALGADIMAR (PRIN 2019-2022) for digital market algorithms. He chairs the Highlights of Algorithms conference series and serves on program committees for top venues like EC, ICALP, and SODA. His lab focuses on web algorithmics and data mining, addressing challenges in online labor markets and fair division. Leonardi's academic contributions include over 100 publications, with recent work on fair algorithms, prophet inequalities, and mechanism design in auctions. He has pioneered methods for submodular optimization, online learning, and multi-agent systems. Grants and awards reflect his leadership in bridging theory with real-world applications, particularly in digital economies. Grants: ERC Advanced Grant (2018-2023), PRIN ALGADIMAR (2019-2022) Leadership: Chair of ACM STOC 2021, WWW 2015, and 9th FUN Conference Labs/Teams: Laboratory on Web Algorithmics and Data Mining Key Projects: AMDROMA (algorithmic mechanisms), ALGADIMAR (digital markets)

Christoph FreiView profile

Professor

• Quantitative Finance
• Risk Management
• Mathematical Economics
• +4 more

Christoph Frei is a Professor and Chair of the Department of Mathematical and Statistical Sciences at the University of Alberta. He holds a PhD in mathematical finance from ETH Zurich and previously worked as a researcher at École Polytechnique in Paris. His research focuses on quantitative finance, risk management, and mathematical economics, with applications to algorithmic trading, credit risk, and digital currencies. Education: PhD in Mathematical Finance, ETH Zurich Postdoctoral Researcher, École Polytechnique (Paris) Bachelor/Master in Mathematics, ETH Zurich His work bridges academia and industry through collaborations with institutions like ATB Financial, Canadian Western Bank, and the Federal Reserve System. Key research interests include over-the-counter markets, financial regulation, and machine learning applications in risk prediction. Frei has received notable recognition, including the Best Paper in Asset Pricing Award (2019). Current industry partnerships include AI-driven customer risk prediction projects with ATB Financial and credit risk analysis with Canadian Western Bank. He actively contributes to professional organizations like PRMIA Edmonton and advises on financial technology innovation. Research grants come from NSERC, SSHRC, and Mitacs. His consulting roles have spanned risk modeling at UBS and Credit Suisse, emphasizing practical applications of theoretical frameworks.

Majid GhaderiView profile

Professor

• Network Algorithms
• Secure Communication
• Machine Learning in Network Control
• +3 more

Majid Ghaderi is a Professor in the Department of Computer Science at the University of Calgary, Faculty of Science. His expertise spans network algorithms, secure communication, and machine learning applications in network control. He holds a Ph.D. in Computer Science from the University of Waterloo (2006), and M.Sc. and B.Sc. degrees in Software Engineering from Sharif University of Technology (2001 and 1999). Education: Ph.D. Computer Science, University of Waterloo, 2006 M.Sc. Software Engineering, Sharif University of Technology, 2001 B.Sc. Software Engineering, Sharif University of Technology, 1999 Research Interests: Dr. Ghaderi focuses on optimizing network algorithms, securing communication in distributed systems, and leveraging machine learning for network control. His work addresses challenges such as secure wireless protocols, SDN-based network management, and efficient resource allocation in data centers. He explores proactive traffic scheduling and anomaly detection in critical infrastructures like industrial control systems and vehicular networks. Publications Trends: His recent work emphasizes covert communication in heterogeneous networks, adaptive federated learning in edge environments, and low-overhead diagnostic systems for cloud networks. He also investigates cybersecurity defenses against hardware vulnerabilities and dynamic threat landscapes. Awards: Best in-session Presentation Award, IEEE INFOCOM 2018 Municipal Excellence Award, Government of Alberta 2018 Faculty of Science Excellence in Teaching Award 2012 Advising & Grants: While no specific advisees are listed, his research has been supported by grants focusing on network security, edge computing, and IoT applications. He teaches CPSC 441 (Computer Networks) and maintains an active lab focused on network systems and cybersecurity. Labs & Teams: His research group collaborates on projects involving software-defined networks, vehicular communication, and industrial IoT security. The team develops open-source tools for network monitoring and anomaly detection.

Mohsen Taheri AndaniView profile

Assistant Professor

• Advanced Materials
• Additive Manufacturing
• Materials Science
• +5 more

Mohsen Taheri Andani is an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. He holds a Ph.D. in Mechanical Engineering from the University of Michigan (2022), an M.Sc. in Materials Science and Engineering from the University of Michigan (2018), an M.Sc. in Mechanical Engineering from the University of Toledo (2015), and a B.Sc. in Mechanical Engineering from Isfahan University of Technology (2012). His research focuses on the processing-structure-properties relationships of advanced materials, additive manufacturing, physical/ mechanical metallurgy, and mechanical behavior of materials, with a particular emphasis on grain boundary engineering and crystallographic texture control in metals processed via additive manufacturing methods. Dr. Andani has received prestigious awards including the 2022 Robert M. Caddell Memorial Award for Research, the 2021 Richard and Eleanor Towner Prize for Outstanding Ph.D. Research, and the 2020 Ivor K. McIvor Award, all from the University of Michigan. His work bridges fundamental materials science with advanced manufacturing technologies, aiming to optimize material performance through multiscale control of microstructures. His research group, the Multiscale Manufacturing and Mechanics of Materials (M4) Lab, explores the interface between additive manufacturing and materials mechanics. Current projects include the Center for Scientific Machine Learning for Material Sciences (AFSOR), reducing qualification time in additive manufacturing (America Makes), and structural evaluation via non-contact sensors (DARPA). He actively seeks motivated Ph.D. students for Fall 2025 and welcomes undergraduate/master’s students to join his team. Dr. Andani’s publications emphasize experimental and computational studies of microstructural evolution in additively manufactured metals, including grain boundary effects on dislocation dynamics, crystallographic texture control in NiTi alloys, and thermomechanical property optimization of materials like 316L stainless steel and Cu-Cr-Zr alloys. His work integrates in situ characterization techniques with advanced modeling to predict and enhance material performance.

• Materials Engineering
• Electrical and Electronic Engineering
• Nanotechnology
• +7 more

Yongxiang Li is a Professor in the School of Engineering at RMIT University, Australia, specializing in advanced materials and nanotechnology. His research focuses on piezoelectric materials, 2D functional materials, and energy harvesting systems. He is actively involved in supervision of PhD and Master’s projects, including topics like flexible piezoelectric nanogenerators, 2D heterostructures, and low-temperature co-fired ceramic (LTCC) sensors. Research Interests: Materials Engineering, Electrical Engineering, Nanotechnology, Condensed Matter Physics, and Functional Ceramic Design. Key projects include developing lead-free piezoelectric materials, integrating sensors for lithium-ion batteries, and exploring gas sensors using liquid metal-derived oxides. Teaching Interests: Dielectric materials, ferroelectric systems, sensor technologies, and LTCC applications. His interdisciplinary work bridges materials science with optoelectronics and energy storage. Publications span over 400 outputs, emphasizing machine learning-driven materials discovery, defect engineering in 2D materials, and sensor innovation. He leads projects in collaboration with industry, focusing on practical applications of advanced ceramics and nanomaterials.

Abdullah MuzahidView profile

Associate Professor

• Computer Architecture
• Systems
• Artificial Intelligence
• +5 more

Abdullah Muzahid is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University (since August 2024), previously serving as an Assistant Professor there since August 2018. Prior, he held an Assistant Professor role at the University of Texas at San Antonio (2012-2018). He earned his Ph.D. from the University of Illinois at Urbana-Champaign (2012), focusing on architectural support for debugging concurrency bugs under Prof. Josep Torrellas. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (2012) M.S., Computer Science, University of Illinois at Urbana-Champaign (2009) B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology (2005) Research Interests: His work spans Computer Architecture , Systems , and Artificial Intelligence , with focus on multiprocessor architecture, parallel programming, debugging, and applying machine learning to system optimization. Recent projects include cache indexing via entropy estimation, DNN training acceleration, and hardware-software co-design for security. Awards: NSF CAREER Award (2017) Excellence in Research Award (UTSA, 2015 & 2017) W. J. Poppelbaum Award (UIUC, 2012) Intel Ph.D. Fellowship (2011) Grants & Advising: He leads NSF-funded projects on robust deep learning and stream processing systems. Advised 5 PhD graduates and currently mentors 4 PhD students. Served on program committees for ISCA, HPCA, MICRO, and as NSF panelist. Labs/Teams: Active in Texas A&M’s Computer Architecture group, collaborating on machine programming, hardware security, and AI-driven systems optimization.

• Artificial Intelligence
• Battery Technology
• Digitalization
• +7 more

Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.

Christian F. DoellerView profile

Professor

• Cognitive Neuroscience
• Memory Psychology
• Spatial Navigation
• +6 more

Professor Christian F. Doeller is a leading cognitive neuroscientist serving as Director of the Department of Psychology at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) in Leipzig and Vice President of the Max Planck Society (since 2023). His roles include honorary professorships at the University of Leipzig (2019) and TU Dresden (Cognitive Neuroscience of Learning and Memory). He holds a PhD in Psychology from Saarland University (2005) and has held positions at institutions such as UCL (London), Radboud University (Nijmegen), and NTNU (Trondheim). His research focuses on spatial navigation, memory systems, and cognitive mapping in the human brain, leveraging neuroimaging (fMRI, EEG) and computational modeling. Key areas include hippocampal/entorhinal cortical function, grid cells, and the neural basis of spatial and conceptual representations. Recent work explores non-Euclidean spatial cognition, value-based decision making using grid-like maps, and hormonal influences on navigation. His lab combines experimental psychology, neuroimaging, and theoretical neuroscience to understand how brains build predictive models of environments and concepts. Publications emphasize cognitive maps, neural representations of space/value, and memory formation mechanisms. Over 100 journal articles span high-impact journals like Nature Neuroscience , Neuron , and Current Biology . His work bridges basic research and translational applications in neurodegenerative disorders and spatial cognition deficits.