Find Academic Supervisors

YAN WentaoView profile

Associate Professor

• Additive Manufacturing
• Computational mechanics

Dr. YAN Wentao is an Associate Professor at the Department of Mechanical Engineering, National University of Singapore (NUS), where he joined in August 2018. He holds a PhD from Tsinghua University (2017) and a Bachelor's degree from the same institution (2012). Prior to NUS, he was a postdoctoral fellow at Northwestern University and a guest researcher at the National Institute of Standards and Technology. His research focuses on Additive Manufacturing and Computational Mechanics , specifically developing multi-scale models for process-structure-property relationships in metal 3D printing. His work integrates experimental validation with high-fidelity simulations to optimize manufacturing processes. Analysis of his 15 most recent publications (2016-2021) reveals a strong emphasis on: Powder dynamics and defect mechanisms in laser/electron beam processes Multi-physics modeling of melt pool behavior and microstructure evolution Data-driven approaches for process optimization and quality control Novel applications in functional materials and composites Awards include: 9 awards in the 2022 AM-Bench Simulation Challenges Materials Research Letters Impact Award (2022) He has supervised doctoral students to graduation, including Dr. Chen Fan. Leads the Yan Research Group at NUS, which collaborates internationally and has hosted visiting scholars like Dr. Shinji Sakane.

Sterling OrtegaView profile

Assistant Professor

• Neuroimmunology
• Multiple Sclerosis
• Stroke neuropathology
• +3 more

Sterling Ortega, PhD, is an Assistant Professor in the Department of Microbiology, Immunology & Genetics at the University of North Texas Health Science Center (UNTHSC), within the College of Biomedical and Translational Sciences. His research focuses on neuroimmunology, particularly the role of adaptive immunity in brain health and disease. He holds a BS in Biology from the University of Dallas, an MS in Biomedical Sciences from Barry University, and a PhD in Integrative Biology from the University of Texas Southwestern Medical Center. His postdoctoral training included studies on B-cell roles in ischemia-induced brain injury. Research Interests: Dr. Ortega investigates immune-mediated neurological dysfunction, targeting therapies to reverse conditions like multiple sclerosis (MS) and stroke. Key goals include identifying CD8+ T-cell roles in stroke neuropathology, myelin-reactive T-cells in MS recovery, and novel therapeutic applications. Techniques employed include cell culture, flow cytometry, animal models, and cerebral organoids. Projects: He has led seven sponsored projects, including studies on BCAA efficacy in stroke, cerebral organoid technology in neuroimmunology, and brain-targeting immune cells. Notable collaborations explore adaptive immunity in pediatric ECMO patients and stroke immunology. Labs/Teams: His lab integrates immunological and neuroscientific approaches to advance therapies for neuroimmune disorders. Current work emphasizes multi-organismal strategies for functional recovery post-stroke and MS.

Carmela BernardoView profile

Research Fellow

• Opinion Dynamics
• Multi-agent Systems
• Consensus Algorithms
• +3 more

Carmela Bernardo is a Research Fellow in the Department of Engineering at Università degli Studi del Sannio (UNISANNIO). Her academic work focuses on opinion dynamics, consensus algorithms, and multi-agent systems within the field of control theory. She teaches 'LEARNING FOR DYNAMICS AND CONTROL' for the Master's Degree program in Electronics Engineering for Automation and Sensing, with office hours held on Wednesdays from 10:00 to 12:00 at PalaUNISANNIO. Dr. Bernardo's research centers on mathematical modeling of social dynamics, particularly exploring the Hegselmann-Krause opinion dynamics model and bounded confidence frameworks. Her work investigates how confidence thresholds affect opinion clustering, develops mixed logical dynamical models for opinion evolution, and examines consensus achievement in systems with stubborn agents. She has made significant contributions to understanding finite-time convergence in asymmetric models and the synchronization properties of Kuramoto oscillators under bounded confidence constraints. Her publication record demonstrates a clear progression from theoretical foundations to practical applications, with recent work including comprehensive surveys that synthesize knowledge in bounded confidence opinion dynamics. The most recent publications show expansion into experimental verification of theoretical models and applications to complex real-world scenarios. Dr. Bernardo maintains an active collaboration network with researchers including Francesco Vasca, Claudio Altafini, and Trisha Srivastava. Her work appears in high-impact journals such as AUTOMATICA, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, and NATURE COMMUNICATIONS, reflecting the interdisciplinary nature of her research that bridges control theory with social dynamics.

David StanfordView profile

Professor

• Queueing Theory
• Stochastic Processes
• Actuarial Science
• +4 more

David Stanford is a Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He earned his Ph.D. from Carleton University in 1981. His office is located in WSC 211 and he can be contacted via phone (519-661-2111 x83612) or email. Research Focus: Dr. Stanford's research spans several interconnected domains including: Queueing Theory : Specializing in multi-server systems, priority queues, and service optimization Actuarial Science : Risk modeling, ruin theory, and insurance mathematics Healthcare Operations : Applying stochastic models to transplant systems and patient flow Environmental Modeling : Forest fire prediction using compound Poisson processes His work frequently combines theoretical stochastic processes with practical applications in healthcare and environmental systems. Publication Trends: Analysis of recent publications shows a strong focus on queueing theory applications in healthcare systems, particularly modeling patient flow and organ transplant logistics. His actuarial research emphasizes advanced ruin probability calculations and risk process modeling. Environmental applications feature stochastic approaches to natural disaster prediction.

• Multi-phase flow in porous media
• Digital rock physics
• X-ray computed tomography
• +5 more

Zuleima T. Karpyn is a Professor of Petroleum and Natural Gas Engineering and Associate Dean for Graduate Education and Research at the College of Earth and Mineral Sciences, The Pennsylvania State University . She holds the Donohue Family Professorship and has received prestigious awards including the NSF CAREER Award and multiple Fulbright U.S. Scholar Awards . Education: Ph.D., Petroleum and Natural Gas Engineering, Penn State (2005) M.S., Petroleum and Natural Gas Engineering, Penn State (2001) B.S., Chemical Engineering, Universidad Central de Venezuela (1997) Dr. Karpyn's research focuses on multi-phase flow in porous media , digital rock physics , and fluid-rock interactions . Her work addresses critical challenges in carbon sequestration , unconventional reservoir characterization , and enhanced oil recovery through advanced imaging and computational modeling techniques. Recent publications highlight her expertise in X-ray computed tomography and wettability alteration in carbonate rocks. Her research team has pioneered studies on underground hydrogen storage and nanoporous shale transport mechanisms . Scientific Awards: 2024 Fulbright U.S. Scholar Award 2023 SPE Regional Reservoir Description and Dynamics Award 2018-2019 Big Ten Academic Leadership Fellow 2008 NSF CAREER Award Dr. Karpyn has served as Associate Editor for several journals including the Society of Petroleum Engineers Journal and Transport in Porous Media . She leads research projects on CO₂ storage pathways , deep-learning image analysis , and chemically tuned waterflooding .

Vidar SkogvollView profile

Senior Lecturer

• Artificial Intelligence in Education
• Computational Physics
• Topological Defects
• +4 more

Vidar Skogvoll serves as a Senior Lecturer at the Centre for Teaching and Learning in Science (KURT) within the Department of Physics at the University of Oslo's Faculty of Mathematics and Natural Sciences. His work bridges computational physics research and innovative science education methodologies, with particular focus on integrating generative artificial intelligence into academic instruction. He maintains active roles in both the Interface Dynamics in Geophysical Flows (EarthFlows) research group and the Center for Computing in Science Education (CCSE). Skogvoll's research spans computational physics (specializing in topological defects and phase field crystal modeling) and AI-enhanced education . His ComFiT library represents significant contributions to open-source scientific software, while his educational projects explore scaffolding techniques for student use of large language models. He actively develops resources through llmteaching.com and comfitlib.com , and produces educational content through dual podcast platforms focusing on science pedagogy and popular science. His publication record demonstrates consistent output in high-impact physics journals including Physical Review B, Journal of Mechanics and Physics of Solids, and Modeling and Simulation in Materials Science and Engineering. The research exhibits strong methodological continuity in computational approaches to material defects while showing recent expansion into AI applications for education. Key thematic threads include topological defect dynamics, phase field modeling, and computational methodology development. Notable recognitions include: Third place in Norwegian Physics Olympiad (2011) The King's watch awarded by Trondheim Katedralskole (2011) Skogvoll leads multiple educational initiatives including the development of AI-integrated teaching materials and maintains an active blog on AI in education with recent 2025 publications. His podcast work ( Real læring and Under kappa ) extends his science communication efforts to broader audiences. He teaches core physics courses including Mechanics, Oscillations and Waves, Thermodynamics, and Mathematical Methods in Physics, demonstrating comprehensive engagement with the department's educational mission.

• Fluid Dynamics
• Multiphase Flows
• Multiscale Modeling
• +2 more

Harikrishnan Charuvil Asokan is a researcher at the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509) affiliated with Claude Bernard University Lyon 1 and École Normale Supérieure de Lyon. He is a member of the EM³ team (Ecoulements Multi-physiques Multi-phasiques & Multi-échelles) which focuses on multi-physical, multi-phase and multi-scale flows. His research interests include fluid dynamics, multiphase flows, multiscale modeling, computational fluid dynamics, and turbulent flows. The EM³ team investigates complex flow phenomena across various scales and physical conditions, with applications in engineering and environmental systems. The EM³ team is part of the broader Laboratory of Fluid Mechanics and Acoustics which conducts research in acoustics, environmental flows, turbulence, instabilities, and turbomachinery. The laboratory is a joint research unit involving multiple prestigious French institutions including INSA Lyon, École Centrale de Lyon, Claude Bernard University Lyon 1, and École Normale Supérieure de Lyon.

• Fluid Mechanics
• Acoustics
• Turbulent Flows
• +3 more

Alessandro Zarri is a Researcher at the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509) in Lyon, France. His work focuses on multi-physical, multi-phase, and multi-scale fluid flows , with applications in turbulence modeling, aeroacoustics, and environmental fluid dynamics. Research interests include: Experimental and numerical analysis of fluid instabilities Acoustics in compressible shear flows Particle transport in complex flows Development of measurement techniques like PIV and LDV For collaboration or inquiries, contact via email: alessandro.zarri@univ-lyon1.fr

• Fluid Dynamics
• Multi-phase Flows
• Multi-scale Modeling
• +3 more

Simon Bouley is a Lecturer at the Multi-physical, Multi-phase & Multi-scale flows department of the Laboratory of Fluid Mechanics and Acoustics at Ecole Centrale de Lyon, University of Lyon. He works in the INSA building, Office 25A, and can be reached at phone number 04.72.43.82.64. His research focuses on advanced fluid dynamics phenomena involving multiple physical processes, phase interactions, and scale interactions. This work has applications in aerospace, energy systems, and environmental engineering. As part of the Laboratory of Fluid Mechanics and Acoustics (UMR 5509), he contributes to one of France's leading research units in fluid mechanics, which operates under joint supervision of CNRS, Ecole Centrale de Lyon, INSA Lyon, and Claude Bernard University.

• Fluid Mechanics
• Aeroacoustics
• Compressible Flows
• +3 more

Christophe Bogey is a Researcher affiliated with the Fluid Mechanics and Acoustics Laboratory (LMFA - UMR 5509) at Université de Lyon and École Centrale de Lyon . His work focuses on aeroacoustics, particularly the noise generated by rotating machines and compressible shear flows. Research interests include: Computational Fluid Dynamics (CFD) simulations Multi-physical and multi-phase flows Active noise control in fluid dynamics Turbulence and instability analysis The laboratory specializes in experimental and numerical studies of fluid mechanics and acoustics, with applications to turbomachinery, environmental flows, and microfluidics. No specific awards or student advisement details were found in the provided texts.

• Turbulence and Modeling
• Flow Instability
• Geophysical Fluid Dynamics
• +2 more

Justine Giez is a Researcher at the Laboratory of Fluid Mechanics and Acoustics (LMFA) in Lyon, France. She is affiliated with the Turbulence & Instabilities (TI) team, focusing on fundamental and applied research in fluid dynamics. Research Interests: Turbulence and modeling Flow instability analysis Geophysical and astrophysical fluid dynamics Multi-physical, multi-phase, and multi-scale flow phenomena Key Technical Expertise: The TI team explores aerodynamic instabilities, nonlinear flow behavior, and advanced numerical/experimental developments in fluid mechanics.

Babak ShahbodaghkhanView profile

Senior Lecturer

• Computational Geomechanics
• Dynamics of Unsaturated Soils
• Constitutive Modelling of Geomaterials
• +4 more

Dr. Babak Shahbodaghkhan is a Senior Lecturer in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW). He holds a PhD in Civil/Geotechnical Engineering from Kyoto University (2011) and an MSc in Civil/Structural Engineering from the University of Tehran (2008). Currently, he contributes to research and teaching at UNSW while affiliated with the Research Centre for Transport Innovation. PhD in Civil/Geotechnical Engineering, Kyoto University, Japan (2008–2011) MSc in Civil/Structural Engineering, University of Tehran, Iran (2005–2008) His research spans critical areas in geotechnical engineering, including Computational Geomechanics , Dynamics of Unsaturated Soils , and Constitutive Modelling of Geomaterials . His work addresses Seismic Analysis of Geostructures and Dynamic Soil-Structure Interaction , often employing advanced numerical methods and constitutive models. Recent publications highlight his expertise in soil bio-cementation , unsaturated soil dynamics , and sustainable construction materials . Articles from 2025–2023 explore topics like shear wave propagation , hydraulic fracturing in porous media , and rubberized asphalt mixtures , reflecting interdisciplinary applications of computational mechanics, materials science, and sustainable engineering. Scientific Awards : Monbusho Scholarship, Ministry of Education, Japan (during PhD) Dr. Shahbodaghkhan teaches undergraduate and postgraduate courses such as Applied Geotechnics & Engineering Geology (CVEN3203), Advanced Foundation Engineering (CVEN9513), and Numerical Methods in Geotechnical Engineering (CVEN9514). He also leads project-based learning in Civil Engineering Design Practice (CVEN9000). He is affiliated with the Research Centre for Transport Innovation at UNSW, collaborating on projects related to geotechnical systems and sustainable infrastructure.

Yue JinView profile

Assistant Professor

• Thermal-Fluid Sciences
• Nuclear Engineering
• Heat Transfer
• +7 more

Yue Jin is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Missouri (Mizzou), where he also serves as the director of the Advanced Flow and Heat Transfer Lab (AFHTL). He previously held a postdoctoral research associate position at MIT before joining Mizzou in 2022 as part of a cohort of 14 new faculty members. His work is closely tied to the MU Research Reactor (MURR), the highest-powered university research reactor in the U.S., which provides a unique platform for his research in nuclear thermal hydraulics and clean energy systems. PhD, Pennsylvania State University (2019) MS, Shanghai Jiao Tong University BS, Xi’an Jiaotong University Dr. Jin's research focuses on thermal-fluid sciences and nuclear engineering, particularly in fluid flow, heat and mass transfer, reactor thermal hydraulics, and the modeling of advanced energy systems such as compact heat exchangers and next-generation nuclear reactors. He is deeply involved in the development and validation of multi-scale, multi-physics numerical tools enhanced by artificial intelligence and machine learning. His lab conducts high-resolution experiments using advanced imaging techniques like S-PIV/LIF and laser diagnostics to study phenomena such as critical heat flux (CHF), droplet dynamics during reflood transients, and two-phase flow behavior in rod bundles. His recent publications reveal a strong trend toward integrating physics-informed machine learning with traditional thermal-hydraulic modeling to improve prediction accuracy in complex systems. Topics include CHF modeling, reflood safety analysis, accident-tolerant fuels, and thermal striping in advanced reactors. His work bridges experimental validation with code development, particularly using tools like COBRA-TF and TRACE. Development of Innovative Physics-Informed Data-Driven Model for COBRA-TF CHF Prediction (MU Research Council) Advanced Reflood Thermal-Hydraulics for Uncertainty Resolution (NRC/Penn State) Midwest Industrial Assessment Center (Department of Energy) Massive Reflood Data Evaluation Using Machine Learning (NRC/Penn State) Dr. Jin actively collaborates with researchers at MIT, Penn State, and General Atomics. He mentors graduate students and welcomes both graduate and undergraduate researchers to his lab. His research contributes to the global effort in clean energy sustainability and next-generation nuclear safety.

• Energy Storage
• Renewable Energy
• Intelligent Energy Systems
• +6 more

Dr Zuansi Cai serves as an Associate Professor at the School of Computing Engineering and the Built Environment, Edinburgh Napier University. He is a member of the EPSRC Peer Review College and leads the Centre for Artificial Intelligence and Robotic research group. Expertise in Energy Storage and Renewable Energy system integration Developed the GPSFLOW numerical simulator for subsurface hydrogen and gas-mixture storage Research Focus: His work bridges Intelligent Energy Systems with Water Resources & Climate Change , emphasizing subsurface storage solutions for renewable energy. Key areas include Hydrogen Storage , Compressed Air Energy Storage (CAES) , and Lithium-ion Battery Thermal Management . Recent Publications: 15+ articles on hydrogen storage dynamics in salt caverns (2024), machine learning for solar PV forecasting (2022), and aquifer CAES performance (2021). Collaborations span EU Horizon 2020 and Royal Academy of Engineering projects. Scientific Recognition: Royal Academy of Engineering Industrial Fellowship (2021/22) Fellow of The Higher Education Academy and The Geological Society Academic Contributions: Supervises 10+ postgraduate researchers at ENU and international universities. Key projects include the iMARS (European Commission funded) and Rough Reservoir hydrogen adaptation studies.

Zhu LiView profile

Professor

• Point Cloud Compression
• Light Field Compression
• Deep Learning in Visual Compression
• +4 more

Zhu Li is a full professor at the Department of Computer Science & Electrical Engineering (CSEE) at the University of Missouri, Kansas City (UMKC), and director of the NSF Center for Big Learning (CBL). He holds a PhD in Electrical & Computer Engineering from Northwestern University (2004). Previously, he served as an AFRL summer visiting professor at the US Air Force Academy (2016-18, 2020-24), Senior Staff Researcher at Samsung Research America and FutureWei Technology, and Assistant Professor at The Hong Kong Polytechnic University. His research focuses on point cloud and light field compression, deep learning for visual compression, remote sensing, and multimedia systems. Key achievements include 50+ patents and 200+ publications. He is an IEEE Senior Member and serves as Associate Editor-in-Chief for IEEE Trans on Circuits & System for Video Technology, and Associate Editor for IEEE Trans on Image Processing and others. Notable awards include the Best Paper Runner-up at PBVS 2023, Best Poster at ICME 2006, and Best Paper at ICIP 2007. His lab has secured grants from NSF, AFRL, and industry partners, advancing research in neural compaction, SAR image processing, and immersive media communication. Education: PhD in Electrical & Computer Engineering, Northwestern University (2004) Affiliations: NSF I/UCRC Center for Big Learning (Director), IEEE (Senior Member) Grants: NSF Trustee's N.T. Veatch Award (2025), AFRL Phase 2 STTR ($1.2M), NSF 5G/6G Networks Grant (2022) Labs/Teams: Multimedia Computing & Communication Lab, MCC Lab collaborating with global institutions