Find Academic Supervisors

Vincent RocaView profile

Researcher

• Privacy
• Robust Content Distribution
• Transport Protocols
• +6 more

Vincent Roca is a permanent researcher at Inria , a French national research institute for digital science and technology. Since 2019, he leads the Privatics research team focusing on privacy, previously part of the Planete team (2000-2012) for Internet protocols and applications. His work spans Privacy in smartphones, IoT, and web browsers Design of the ROBERT and CLEA protocols for the French TousAntiCovid app Standardization in IETF working groups, notably on FEC and network coding Co-author of Inria's cybersecurity white book (2019) Instructor of the popular Privacy in the digital world MOOC (14,006 participants) Research Interests include privacy risks in digital technologies, robust content distribution via FLUTE/ALC transport protocols and LDPC-Staircase FEC codes, and network coding for scalable services. His articles focus on privacy in LoRaWAN, contact tracing protocols, GDPR compliance, and FEC optimization. Scientific Awards include the Third Applied Research Price from FIEEC (2014) Knight Medal of the French Order of Merit (2020) Students supervised include PhD candidates in privacy-preserving IoT, secure authentication, and alumni like Samuel Pelissier (LoRaWAN privacy) and Michael Toth (GDPR compliance). Software Contributions include openfec.org (AL-FEC codes) and FLUTE/ALC implementations .

• Geophysics
• Remote Sensing
• Computer Vision
• +2 more

Scott Staniewicz is a researcher at the University of Texas at Austin in the Department of Aerospace Engineering and Engineering Mechanics. His work focuses on geophysical applications of computer vision and remote sensing, particularly using Interferometric Synthetic Aperture Radar (InSAR) to detect surface deformation and tropospheric noise features. Academic Affiliation: University of Texas at Austin Research Focus: Surface deformation analysis, InSAR data processing, tropospheric noise mitigation Email: scott.stanie@utexas.edu Staniewicz's research employs computer vision techniques like Laplacian of Gaussian (LoG) filtering to identify spatially coherent deformation features (e.g., subsidence/uplift in oil-producing regions). His methods integrate noise spectrum estimation from real data and simulations to distinguish true deformation signals from atmospheric artifacts. Recent work includes software development for automated InSAR analysis and large-scale studies of anthropogenic deformation in the Permian Basin. He has contributed to open-source tools such as Blobsar (2025a) and Troposim (2025b) for deformation detection, and collaborated on studies analyzing seismic sequences (Skoumal et al., 2020), tropospheric delay corrections (Li et al., 2019; Yang et al., 2024), and statewide seismic networks (Savvaidis et al., 2019). His publications demonstrate expertise in combining computer vision with geophysical data analysis.

• Quantum Computing
• Quantum Information Science
• Quantum Simulation
• +3 more

Martin Ringbauer is an Associate Professor at the Department of Experimental Physics , University of Innsbruck . His research focuses on advancing quantum computing and quantum simulation through innovative applications of trapped ion qudits and high-dimensional quantum systems . Affiliation: Department of Experimental Physics, University of Innsbruck Research Areas: Lattice gauge theories, symmetry-protected topological phases, quantum verification protocols, and fidelity estimation Key Contributions: Development of qudit-based quantum processors for simulating complex physics, experimental demonstrations of quantum error correction and joint measurements His recent publications highlight advancements in quantum simulation (lattice gauge theories, Haldane phases), quantum verification (fidelity estimation, classical validation), and qudit engineering (mixed-dimensional frameworks, entanglement optimization). These works leverage trapped ion technology as a platform for scalable and precise quantum operations.

Mila N. KoevaView profile

Associate Professor

• Geospatial Technologies
• Digital Twinning
• 3D Urban Modeling
• +6 more

Mila N. Koeva is a Vice Dean Research and senior Associate Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), Department of Urban and Regional Planning and Geo-Information Management. Her research focuses on 3D modeling and Digital Twins for land management and urban planning, integrating geospatial technologies, UAV data, and AI/ML methods. PhD in architectural photogrammetry MSc in Engineering (Geodesy) Research Themes: Digital Twinning for urban ecosystems AI-driven cadastral boundary extraction 3D modeling with LiDAR and satellite data Global partnerships in Rwanda, Kenya, and Ethiopia Interoperability standards for local digital twins Scientific Contributions: Geospatial World Innovation Award 2021 Copernicus Masters Competition (3rd place 2016) Editorial roles in Photogrammetric Records and MDPI journals Keynote speaker at 3D GeoInfo, GI Forum, and FIG events Her educational impact includes developing courses, lecturing, and supervising students whose work has received top awards in The Netherlands and international competitions.

Pavel P. KuksaView profile

Academic

• Bioinformatics
• Computer Science
• Functional Genomics
• +5 more

Pavel P. Kuksa is a Research Assistant Professor in the Department of Pathology and Laboratory Medicine, specializing in bioinformatics, computer science, and functional genomics. His work focuses on high-throughput sequencing analysis, chromatin interaction data, and developing scalable software platforms for genomics research.

• digital transformation
• strategy
• visualisation
• +4 more

Gordon Fletcher serves as Associate Dean: Research and Innovation at Salford Business School, University of Salford, where he leads the development of the School's research presence and profile while guiding bidding activities, staff development, and impact initiatives. With extensive experience since 2002 teaching programming, digital transformation, and information systems, Fletcher employs a hands-on, interactive pedagogical approach. University: University of Salford School: Salford Business School Academic Rank: Professor Research Focus: Digital business, culture, and practice Fletcher's research explores digital transformation through multiple lenses including conflict within online finance communities, virtual game economies, and digital grieving practices. His scholarly work connects theoretical frameworks with practical applications in business environments, particularly examining how organizations navigate digital change while maintaining strategic coherence. His recent publications (2022-2025) demonstrate a consistent focus on practical frameworks for digital transformation, with particular attention to organizational readiness, leadership approaches, and strategic implementation. The recurring themes across his work include visualization techniques for strategic planning, responsive business model design, and the cultural dimensions of digital adoption. Awards and Professional Recognition: Emerald Literati Award (2017) for Outstanding Paper Claudio Ciborra Award for most provocative paper (2011) Vice-Chancellor's Distinguished Teaching Award (2014) Fellow of the Higher Education Academy (2012) Fellow of the Royal Society for the Arts (2011) Chartered Manager designation (2015) Fletcher actively supervises doctoral research in digital transformation topics and has contributed to multiple Knowledge Transfer Partnerships with organizations including the Greater Manchester Chamber of Commerce. His professional service includes committee roles with the International Federation of Information Processing and editorial responsibilities for major information systems conferences.

Lucas IntronaView profile

Professor

• Technology Ethics
• Information Technology and Society
• Phenomenology of Technology
• +5 more

Lucas Introna is a Distinguished Professor of Organisation, Technology, and Ethics at Lancaster University's Management School. He holds a BCom, BA (Hons), MBA, and PhD. His research focuses on the ethical and social implications of technology, particularly information systems, informed by phenomenology and process philosophy. He has served as Associate Dean for Research (2010-2016) and Head of the Organisation, Work and Technology Department (2007-2010). **Research Interests:** Sociomateriality and performativity Ethical implications of IT (privacy, surveillance) Political studies of technology design Plagiarism and cultural values Virtuality and embodiment **Recent Work Trends:** His publications explore algorithmic governance, digital ethics, and the interplay between technology and social structures. Notable themes include blockchain trust dynamics, refugee precarity, and the ethical dimensions of facial recognition systems. **Awards:** IFIP Outstanding Service Award **Grants & Roles:** Co-founder of the Centre for the Study of Technology and Organisation Member of multiple ethics committees and editorial boards Visited professor at University of Amsterdam **Labs/Groups:** Affiliated with the Centre for Technological Futures and the Society Management and Society group.

• Geotechnical Engineering
• Seismic Analysis
• Soil Mechanics
• +3 more

Youssef M A Hashash is the W. W. Grainger Chair and Professor in the Department of Civil and Environmental Engineering at the University of Illinois. His research focuses on geotechnical and earthquake engineering, with emphasis on seismic site response analysis, soil-structure interaction, and advanced computational methods like the Discrete Element Method (DEM). He has led projects on infrastructure resilience, including studies of buried water reservoirs, railway systems, and post-earthquake reconnaissance. Hashash has developed influential models for site amplification in Central and Eastern North America, contributing to seismic hazard assessments. His work integrates experimental centrifuge testing, numerical simulations, and field data. Notable contributions include guidelines for implementing NGA-East ground motion models and advancements in pore-water pressure generation models for liquefaction evaluation. Key Research Areas: Ground movement, seismic response, soil dynamics, and geotechnical data systems Major Projects: NGA-East Geotechnical Working Group, Beirut Explosion Analysis, and LA Metro Tunnel Projects Recipient of prestigious awards including the NAE Membership (2022), PECASE (2000), and Walter L. Huber Prize (2006), he collaborates internationally on earthquake engineering and geotechnical innovations. His lab develops tools like the DEEPSOIL software for nonlinear site response analysis and explores AI applications in geotechnical data interpretation.

• Virtualization
• Operating Systems
• Concurrency
• +4 more

Gaël Thomas is a Senior Researcher at Inria Saclay and a part-time Professor at École Polytechnique. He leads the Benagil team, a joint initiative between Inria and Telecom SudParis/IP Paris. His research focuses on virtualization, operating systems, concurrency, and runtime systems, with an emphasis on improving system performance and safety. He holds a PhD and Habilitation from Sorbonne Université and has extensive academic experience, including roles as a Professor at Telecom SudParis (2014–2023) and an Associate Professor at UPMC (2006–2014). Education: PhD in Computer Science, 2005, UPMC Sorbonne Université Habilitation à Diriger les Recherches (HDR), 2012, UPMC Sorbonne Université MSc in Computer Science, 2001, MIAIF Program Research Interests: Gaël’s work spans virtualization techniques, NUMA architecture optimization, garbage collection scalability, lock-free algorithms, and persistent memory systems. He has pioneered solutions like J-NVM for Java NVMM and NumaGiC for big data systems. Grants & Awards: Principal Investigator of DiVA (PEPR Cloud, 868k€) and Maplurinum (ANR PRC, 184k€) Contributions to VMKit and infra-web-cours development Labs/Teams: Benagil Team (Inria/Telecom SudParis) focuses on systems and runtime optimization.

• Longitudinal Modeling
• Psychometric Modeling
• Developmental Cognitive Neuroscience
• +3 more

Ethan McCormick is an Assistant Professor in the School of Education at the University of Delaware, specializing in longitudinal and psychometric modeling. He holds a Ph.D. in Psychology from the University of North Carolina at Chapel Hill (2020) and a B.S. in Biochemistry from the University of Arkansas (2013). His research focuses on integrating short-term and long-term longitudinal models to study behavioral and cognitive changes across the lifespan, with recent emphasis on educational data analysis and nonlinear random effects modeling. He is a Resident Faculty member of the University of Delaware’s Data Science Institute and previously served as an Assistant Professor of Methodology & Statistics at Leiden University (2022–2024). Dr. McCormick’s grants include the NWO Veni SSH Grant (2024–2027) for tracking educational outcomes via statistical modeling and the Jacobs Foundation Fellowship (2024–2026) for studying complex growth in math ability. His work bridges methodological rigor with applied neuroscience, examining brain-behavior relationships in developmental contexts through large-scale collaborations. Professional Experience : Assistant Professor, University of Delaware (2024–present); Assistant Professor, Leiden University (2022–2024) Key Research Themes : Longitudinal modeling, time series analysis, psychometrics, developmental cognitive neuroscience Awards : NWO Veni SSH Grant, Jacobs Foundation Fellowship His recent articles emphasize improving time-series methodologies, addressing limitations of two-time-point studies, and advancing models for asymmetric temporal dynamics. He collaborates internationally on projects simulating developmental datasets and analyzing neural correlates of behavior.

Zoe LiView profile

Associate Professor

• Uncertainty Analysis
• Risk Management
• Stochastic Modelling
• +7 more

Dr. Zoe Li is an Associate Professor in the Department of Civil Engineering at McMaster University, with an additional role as an Associate Member in the Department of Computing and Software. She specializes in developing modeling and decision-support tools to address challenges in water resources management, environmental systems analysis, and climate change impacts. Her research focuses on hydrological modeling, probabilistic forecasting, risk analysis, and environmental systems optimization. She holds a B.Eng. from China and M.A.Sc./Ph.D. degrees from the University of Regina. Her work spans interdisciplinary collaborations, including studies on dam safety under climate change, wastewater treatment plant optimization, and AI-driven environmental monitoring. She has been actively involved in projects such as CityDNA, a digital tool to model urban environments for decision-making during crises like the pandemic. Dr. Li teaches courses in environmental systems engineering and principles of environmental engineering, emphasizing uncertainty quantification and sustainable practices. Her research publications (15+ recent articles) address topics like machine learning applications in environmental systems, climate change impacts on water resources, and infrastructure resilience. She advises graduate students in environmental engineering and systems optimization. Notable grants include funding from Roche Canada for pandemic-related urban modeling. Her work is frequently published in high-impact journals like Journal of Environmental Management and Water Resources Research .

Andrea SantilliView profile

Researcher

• Natural Language Processing
• Representation Learning
• Machine Intelligence
• +10 more

Andrea Santilli is a Research Scientist at Nous Research and holds a PhD in Computer Science from GLADIA at Sapienza University of Rome. His research focuses on large language models (LLMs), robustness, reliability, and multimodal learning. He previously worked at Apple MLR, Hugging Face’s BigScience, and Pi School. He earned his MSc and BSc in Computer Science from Tor Vergata University and Sapienza. Education: PhD in Computer Science, Sapienza University of Rome (2024) MSc in Computer Science, University of Roma Tor Vergata (2020) BSc in Computer Science, University of Roma Tor Vergata (2018) Research Interests: Santilli’s work spans LLM robustness , mechanistic interpretability , multimodal neural databases , and instruction-tuning . He introduced Parallel Jacobi Decoding and contributed to projects like BLOOM, Camoscio, and Fauno. His research bridges syntax-aware NLP, privacy-preserving LLMs, and cross-modal alignment. Publications: His work includes advancements in 3D-text latent space alignment (CVPR 2025), evolutionary merging (ICML 2025), and efficient decoding (ACL 2023). Over 15+ peer-reviewed papers span venues like ACL, CVPR, and ICLR. Awards: Received the Emanuele Pianta Award for his MSc thesis on continual language learning with syntax-based episodic memory. Grants & Projects: Winner of ‘Machine Learning Algorithms for Translation’ grant (2022), developing Parallel Decoding Co-PI for ‘Multimodal AI for 3D Analysis’ (2021) with Ecole Polytechnique Labs & Teams: Active in GLADIA (Sapienza), Apple MLR, and Hugging Face’s BigScience initiative. Core contributor to open-source projects like PromptSource and BLOOM.

Marjan AlaviView profile

Assistant Professor

• Fault Diagnosis
• Prognosis
• Power Electronics
• +3 more

Dr. Marjan Alavi is an Assistant Professor at McMaster University's W Booth School of Engineering Practice and Technology, affiliated with the Mechanical Engineering department as an Associate Member. She holds a Professional Engineer (P.Eng.) license in Ontario and has over 15 years of academic and industrial experience in electrical engineering. Her research focuses on model-based and data-driven approaches for fault diagnosis, prognosis, and fault-tolerant control in hybrid systems, with applications in power electronics, energy systems, and smart infrastructure. Education: B.Sc. (2004) from K.N. Toosi University of Technology, M.Sc. (2007) from Sharif University of Technology, Ph.D. (2014) from Nanyang Technological University (Singapore), and a Postdoc (2015) at the University of Toronto's Energy Systems Group. Teaching: Instructs courses on Real-Time Systems (SEP 6ES3, SFWRTECH 4ES3), Smart Cities and Communities (SMRTTECH 4SC3), integrating real-world engineering challenges with theoretical frameworks. She emphasizes hands-on learning through remote labs and experiential projects. Professional Contributions: Serves as IEEE Toronto Section Executive Member, Technical Reviewer for IEEE Transactions on Industrial Electronics, and Vice Chair of IEEE Industrial Applications Society (2015). Founded Intelligent Diagnosis Corporations, a Canadian startup focused on research and innovation in diagnostics technologies. Key Projects: Developed fault diagnosis strategies for electro-hydraulic actuators, vehicle-mounted infrastructure monitoring systems, and remote laboratory platforms for emergency traffic control. Research spans predictive maintenance, smart city technologies, and railway systems certification benefits. Awards: Recipient of the Singapore International Graduate Award (SINGA) 2010. Recognized for her work in bridging academic research with industrial applications, particularly in enhancing system reliability through advanced control methodologies.

Yulia GelView profile

Professor

• Uncertainty Quantification
• Artificial Intelligence
• Topological Data Analysis
• +6 more

Yulia Gel is a Professor in the Department of Statistics at Virginia Tech and serves as a Part-Time Program Director-Expert at the National Science Foundation (NSF). She holds a MSc (summa cum laude) and PhD in Mathematics from Saint Petersburg State University (Russia) and completed a postdoc in Statistics at the University of Washington. Her research focuses on uncertainty quantification in AI, statistical foundations of data science, spatio-temporal processes, and applications in climate science, healthcare, and blockchain analytics. She has received prestigious awards including the NSF Director’s Award (2023), ASA Distinguished Achievement Medal (2018), and TIES Abdel El-Shaarawi Award (2014). Gel has led grants on wildfire prediction, climate informatics, and blockchain data science. She serves on editorial boards of Statistica Sinica, Electronic Journal of Statistics, and Technometrics, and organizes workshops on AI for climate sustainability and fragile Earth systems. Her research group develops topological and geometric methods for graph neural networks, with applications to digital twins, environmental justice, and public health. Education: MSc (1997), PhD (2000) in Mathematics from Saint Petersburg State University; Postdoc in Statistics at University of Washington (2001–2003). Past roles include Professor at University of Texas at Dallas (2015–2024) and Associate Professor at University of Waterloo (2004–2014). Selected visiting positions include NASA Jet Propulsion Lab (2016–2017) and Isaac Newton Institute (2016–2017). She has pioneered statistical software packages like snowboot and funtimes for network inference and time-series analysis. Awards highlight her contributions to environmetrics and statistical methodologies. Current projects include NSF-funded research on AI-driven wildfire prediction and blockchain analytics for climate resilience. Her lab’s recent work emphasizes topological methods (e.g., zigzag persistence) for graph-based forecasting and adversarial robustness.

• Nonlinear Dynamics
• Structural Dynamics
• Vibration Control
• +3 more

Professor David Wagg is a Professor of Nonlinear Dynamics and Departmental Director of Research and Innovation at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. His research focuses on nonlinear structural dynamics, digital twins, vibration suppression, and real-time hybrid testing. He holds a BEng and PhD from University College London and previously served as a Professor at the University of Bristol (2008–2013). Notable awards include the EPSRC Advanced Research Fellowship (2004–2009). Education: BEng and PhD in Nonlinear Dynamics from University College London. Research Interests: Digital twins for dynamics applications, nonlinear structural dynamics, vibration control, real-time hybrid testing, and identification methods for nonlinear dynamics. His work emphasizes applying nonlinear models and control strategies to engineering challenges like wind turbines and large civil infrastructure. Grants & Leadership: Co-Investigator for EPSRC grants on CITCoM and Digitwin, coordinator of the Marie Curie ETN DyVirt, and PI for the EPSRC programme on Engineering Nonlinearity (2012–2017). He co-authored Nonlinear Vibration with Control (2015) and edited books on structural dynamics. Lab/Teams: Involved in the Laboratory for Verification and Validation (LVV) and leads research groups focused on digital twin applications, inerter-based systems, and structural health monitoring.