Shaun Lui is Professor and Head of Mathematics at the University of Manitoba's Faculty of Science. His research develops advanced numerical methods for partial differential equations with applications in fluid dynamics and electromagnetics. Education includes B.Sc./M.Sc. from University of Toronto and Ph.D. from Caltech. Research focuses on spectral collocation methods in space-time, domain decomposition, and finite volume schemes. Recent work establishes spectral accuracy for Stokes flows and matrix singularity bounds. Supervises graduate students in numerical PDE projects.
Dr Xinchen Zhang is a Grant-Funded Researcher (A) at the University of Adelaide's Department of Mechanical Engineering within the School of Electrical and Mechanical Engineering. His research focuses on integrating machine learning with computational fluid dynamics (CFD) to enhance predictive capabilities for multiphase flow solutions, particularly in sustainable energy applications like decarbonization technologies. He holds a PhD (2022) with a Dean's Commendation for Doctoral Thesis Excellence, emphasizing fluid and particle dynamics in particle-laden flows. His work addresses challenges in net-zero industrial processes such as limestone calcination and hydrogen production via methane pyrolysis, leveraging advanced CFD and ML-augmented methodologies. Key research areas include turbulence modeling, particle dispersion in jets, and flow regime analysis in horizontal particle-laden pipe systems. He is eligible to supervise Masters and PhD students as a co-supervisor. Dr Zhang's publications span 2018–2024, with recent trends focusing on physics-informed machine learning for turbulence modeling and multiphase flow optimization. His contributions advance computational efficiency and accuracy in predicting complex fluid-particle interactions.
Thomas Cohen is a Professor and Associate Chair in the Department of Physics at the University of Maryland. He holds a B.A. from Harvard College (1980) and a Ph.D. from the University of Pennsylvania (1985). A Fellow of the American Physical Society, he was also an NSF Presidential Young Investigator from 1990 to 1995. His teaching accolades include the Celebrating Teaching Award, Dean's Award for Excellence in Teaching, and Distinguished Scholar-Teacher Award. Cohen's research focuses on quarks, hadrons, and nuclei, with affiliations to the Maryland Center for Fundamental Physics. His work explores QCD dynamics, exotic hadrons, and quantum algorithms for particle physics. Recent contributions include studies on gauge invariance, heavy-ion collisions, and adiabatic quantum computing. His research spans theoretical particle physics, nuclear physics, and computational methods, with notable publications on QCD phase diagrams, tetraquark states, and adiabatic state preparation. Cohen actively collaborates on projects involving quantum simulations and high-energy physics phenomena. His awards reflect both scholarly and pedagogical excellence.
Jay D. Sau is a Professor of Physics at the University of Maryland, College Park, and Co-Director of the Joint Quantum Institute (JQI). His research focuses on theoretical condensed matter physics, particularly topological quantum computing, quantum many-body systems, and Majorana fermions. He holds affiliations with the Condensed Matter Theory Center (CMTC) and JQI. Sau received his Ph.D. from UC Berkeley in 2008. His work bridges theoretical concepts in topological materials, superconductivity, and quantum information processing. Research Interests: Sau's primary interests include applying topological principles to solid-state and cold-atomic systems for quantum computation. Key areas include topological superconductivity, Majorana fermions, quantum Hall effects, and spin-orbit coupled systems. His group explores phenomena like topological degeneracy, Weyl semimetals, and cold atomic gases. Awards: He has been recognized with the National Science Foundation CAREER Award (2016) and the Sloan Research Fellowship (2016). His work has been published extensively in high-impact journals and covers topics ranging from Majorana physics to quantum phase transitions. Advising & Labs: Sau mentors graduate students including Tamoghna Barik, Stuart Thomas, Huan-Kuang Wu, and Shuyang Wang. His research group collaborates on projects at JQI and CMTC, focusing on experimental realizations of topological qubits and quantum devices.
Dr. Catherine Rychert is an Associate Professor in the Department of Geology and Geophysics at the University of Southampton, where she conducts cutting-edge research in seismology and marine geophysics. She is a member of both the Geology and Geophysics research group and the Southampton Marine and Maritime Institute, contributing significantly to our understanding of Earth's interior structure and dynamics through advanced seismic imaging techniques. Her research focuses on several key areas: Seismic imaging of lithosphere-asthenosphere boundary Subduction zone dynamics and slab structure Continental rifting processes Seafloor spreading mechanisms Mantle flow patterns and upwellings Development of novel seismic sensing technologies Dr. Rychert's recent publications (2023-2025) demonstrate a strong focus on applying advanced seismic techniques across diverse tectonic settings including subduction zones (Lesser Antilles, Cascadia, Hikurangi), mid-ocean ridges (Mid-Atlantic Ridge), and continental rift systems (East African Rift). A notable trend is her increasing use of distributed acoustic sensing technology for both terrestrial and planetary applications, showing interdisciplinary reach beyond traditional Earth science. Dr. Rychert actively supervises PhD students, including William Arnold Buffett working on the INSPIRE project. She has secured significant research funding from diverse sources including the European Union (EURO-LAB project), National Geographic Society, and Natural Environment Research Council (NERC). Her collaborative network includes Dr. Nicholas Harmon and Professor Derek Keir, with whom she frequently publishes. Her research team conducts fieldwork and data analysis focused on understanding fundamental Earth structure and processes through innovative seismic methodologies, contributing to both theoretical understanding and practical applications in hazard assessment and resource exploration.
Guang Lin is the Associate Dean for Research and Innovation in the College of Science and a Full Professor in the School of Mechanical Engineering and Department of Mathematics at Purdue University. He leads the Data Science Consulting Services and has dual appointments in Statistics and Earth, Atmospheric, and Planetary Sciences. His research focuses on AI, machine learning, uncertainty quantification, and computational science, with applications in fluid mechanics, materials science, and healthcare. Lin holds a Ph.D. from Brown University (2007) and has received numerous awards, including the NSF CAREER Award and Purdue’s University Faculty Scholar distinction. He has authored over 250 publications and secured grants totaling millions, including DOE and NIH funding. His interdisciplinary work bridges academia and industry, emphasizing AI-driven solutions for complex systems. Education: Ph.D. Applied Mathematics (Brown, 2007), M.S. Applied Mathematics (Brown, 2004), M.S. Mechanics (Peking University, 2000), B.S. Mechanics (Zhejiang University, 1997). Research Grants: Includes DOE-funded projects on machine learning for plasma-wall interactions and NSF grants for multiscale modeling. Service: Editorships in SIAM MMS, ASME Journal, and leadership in Purdue’s AI initiatives. Teaching: Courses on Uncertainty Quantification, Fluid Mechanics, and Data Science.
Professor Mehmet Atlar is a Research Professor in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, Faculty of Engineering. He joined in May 2016 via the Global Talent Platform initiative. Previously, he served as Professor of Ship Hydrodynamics and director of the Emerson Cavitation Tunnel at Newcastle University. His work spans experimental and computational naval hydrodynamics with a focus on ship propulsion, energy efficiency, and marine sustainability. His educational background includes a BSc and MSc in Naval Architecture & Marine Engineering from the Technical University of Istanbul and a PhD from the University of Glasgow on the dynamic motion responses of semi-submersibles. Mehmet Atlar’s research centers on ship performance, propulsion systems, cavitation, underwater noise, and marine biofouling. He is particularly interested in novel hull forms, propulsor design, and biomimetic applications for renewable energy and drag reduction. His recent work emphasizes energy-saving devices and sustainable shipping technologies. The most recent publications highlight a strong trend in experimental and computational analysis of advanced propulsion systems like the gate rudder, with attention to real-world conditions such as ageing, fouling, and oblique wave interactions. There is also a clear focus on sustainability, including carbon footprint assessments and retrofitting energy-saving technologies using CFD. Honorable Mention for the 2022 Vice Admiral E. L. Cochrane Award Professor Atlar has supervised over 28 PhD students as principal supervisor and has led numerous research projects funded by the EC Framework Programme, EPSRC, industry, and defense agencies. He has been a principal or co-investigator in major projects such as the Oldendorff Sustainable Shipping Research Centre and initiatives on hydrogen-fueled zero-emissions vessels. His leadership extends to organizing international conferences, including the bi-annual AMT Conference Series since 2009. He is actively involved in research teams focusing on sustainable shipping, hydrogen propulsion, and advanced measurement technologies. He leads the HTF & AMT25 Management project and contributes to national and international technical committees, including ITTC, RINA, and SNAME.
Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.
Dr. Susan D. Hovorka is a Research Professor at the Bureau of Economic Geology, The University of Texas at Austin, specializing in geological techniques for environmental applications. She focuses on subsurface permeability dynamics in both tight and highly transmissive systems, with a primary emphasis on geological carbon sequestration and CO₂ storage security. Ph.D. in Geology (1990), The University of Texas at Austin M.A. in Geology (1981), The University of Texas at Austin B.A. in Geology (1974), Earlham College Her research addresses critical challenges in carbon geological storage, including: Characterizing salt formations as containment materials Analyzing carbonate fabrics for karst aquifer flow understanding Field CO₂ injection experiments for sequestration assessment Developing composite confining systems for secure CO₂ retention The articles she has contributed to since 2002 demonstrate a consistent focus on: Carbon capture and storage (CCS) technologies Reservoir pressure dynamics and fault permeability Permit-ready site workflows and risk mitigation Geological analogs from petroleum systems Dr. Hovorka actively collaborates with institutions like the Gulf Coast Carbon Center (GCCC) and participates in international CCS initiatives. Her work integrates sedimentology, geophysics, and environmental policy to advance subsurface carbon management solutions.
Dr. Arman Khoshghalb is a Senior Lecturer in Geotechnical Engineering at the School of Civil and Environmental Engineering, UNSW Sydney, where he has been a faculty member since 2012. His academic credentials include a PhD in Geotechnical Engineering from UNSW (2012), an MSc from Sharif University of Technology (2005), and a BSc in Civil Engineering from the same institution (2003). His research focuses on numerical modeling of multi-phase porous media , with emphasis on unsaturated soils, large deformation analysis, and dynamic soil behavior. Key areas include meshfree computational methods, soil-structure interaction, bio-cementation, and thermo-hydro-mechanical processes in geotechnical systems. His work bridges theoretical advancements with practical applications in slope stability, foundation engineering, and sustainable ground improvement. Dr. Khoshghalb's publications predominantly explore geomechanical modeling, experimental soil mechanics, and computational techniques. Recent trends highlight innovations in bio-cemented soils, thermal properties of unsaturated soils, and adaptive numerical methods for complex geotechnical simulations. Awards & Honors: IACMAG Excellent Paper Award (2017) UNSW Research Excellence Award (2012) Advising & Grants: He has supervised 7+ PhD students on topics ranging from weak rock mechanics to computational geomechanics. Funded projects include: ARC Discovery Project (2019–2021): "Non-isothermal dynamic strain localisation in unsaturated porous media" ($298,257) ARC Linkage Infrastructure Grant (2015): "Earthquake shaking table for soil-structure interactions" ($320,000) ARC Linkage Project (2014–2017): "Constitutive modelling of weak rocks" ($314,280) He leads research within UNSW's geotechnical engineering group, collaborating on large-scale experimental testing and computational frameworks for infrastructure resilience.
Yusuf Altintas is a Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, holding the NSERC–P&WC-Sandrik Coromant Industrial Research Chair and coordinating the Mechatronics Option. An internationally acclaimed scholar, he is a Fellow of 10 prestigious academies including the National Academy of Engineering (NAE), Royal Society of Canada (RSC), and ASME. His academic credentials include a Ph.D. from McMaster University, an Honorary Doctor of Engineering from the University of Stuttgart, and a Doctor of Technical Sciences from Budapest University of Technology and Economics. Professor Altintas's research pioneers the integration of physics-based modeling and data-driven approaches for machining systems. His work spans virtual high-performance machining simulation, machine tool dynamics, chatter stability prediction, and intelligent process control for CNC systems. Current projects focus on digital twin development for machining processes, spindle health diagnostics, ultrasonic vibration-assisted tooling, and adaptive damping systems for aerospace manufacturing applications. His methodologies bridge theoretical mechanics with industrial implementation in die/mold and aerospace sectors. Analysis of his 2022-2025 publications reveals dominant trends in physics-informed machine learning for spindle fault detection, topology-optimized tool design, and chatter avoidance in thin-walled component machining. Key thematic clusters include digital twin implementation (28% of recent work), dynamics modeling of multi-axis systems (35%), and intelligent monitoring algorithms (22%), with growing emphasis on anisotropic material machining and 3D printing process control. Georg Schlesinger Award (2016) NSERC Strategic Research Network in Virtual Machining Grant (2016) NSERC Synergy Award (2013) ASME Blackall Machine Tool and Gage Award (2013) Special Distinguished Scientist Award from Turkey's Scientific and Technical Research Council (2013) He directs the Manufacturing Automation Laboratory at UBC, leading an international research consortium on virtual machining systems supported by NSERC and industry partners including Sandvik Coromant and Pratt & Whitney Canada. His team develops real-time process monitoring frameworks and physics-based simulation tools that have been adopted in aerospace manufacturing for blade machining and die/mold production. The laboratory maintains advanced testbeds for five-axis machining dynamics, spindle health monitoring, and ultrasonic vibration-assisted tooling, serving as a hub for industry-academic collaboration in next-generation manufacturing technologies.
Andrea J. Liu is the Hepburn Professor of Physics and Professor of Chemistry at the University of Pennsylvania, within the School of Arts & Sciences. She is based in the Department of Physics and conducts interdisciplinary research at the intersection of theoretical physics, soft matter, and biophysics. Her education includes a Ph.D. from Cornell University (1989) and a B.A. from the University of California, Berkeley (1984). Dr. Liu's research focuses on soft matter physics and biophysical self-assembly . She investigates the universal framework of jamming in disordered systems such as glass-forming liquids, foams, and granular materials. Her work explores how these systems develop yield stress or long relaxation times under varying conditions. On the biological side, she studies the mechanical reorganization of actin networks in the cytoskeleton during cell crawling, modeling polymerization, branching, crosslinking, and force generation at the leading edge of cells. Her research combines analytical theory and numerical simulations to uncover the dynamical principles governing morphology and mechanical properties in complex soft and biological materials. Scientific Awards: Hepburn Professor of Physics Dr. Liu leads an active research group focused on theoretical and computational modeling in soft condensed matter and biophysics. Although specific grants are not listed, her position and named professorship imply sustained funding and academic leadership. She advises graduate students and contributes to advanced research training in physics and interdisciplinary sciences. The research group maintains a website, though access to the '/liugroup/' directory is currently restricted (403 Forbidden). However, her curriculum vitae is publicly accessible, indicating ongoing scholarly activity.
Thomas K. Uchida is an Associate Professor in the Department of Mechanical Engineering at the University of Ottawa, a position he has held since May 2024. Prior to this promotion, he served as an Assistant Professor at the same institution from October 2018 to May 2024. Before joining the University of Ottawa, Dr. Uchida was an Engineering Research Associate (April 2015-August 2018) and Simbios Distinguished Postdoctoral Fellow (July 2012-April 2015) in the Department of Bioengineering at Stanford University. Dr. Uchida's research focuses on the modeling and simulation of dynamic systems, with particular emphasis on human movement biomechanics. His work spans multiple areas including: Simulation-guided design of assistive devices for improving mobility Modelling musculotendon dynamics and energy expenditure Parameter identification and model reduction methods Impact and contact dynamics Development of computational tools for biomechanical analysis He is a co-author of the book "Biomechanics of Movement: The Science of Sports, Robotics, and Rehabilitation" published by MIT Press, and actively contributes to the development of OpenSim, an open-source software platform for modeling musculoskeletal systems and generating simulations of human and animal movement. His work on OpenSim was featured on the cover of PLoS Computational Biology. Dr. Uchida's recent publications demonstrate strong activity in biomechanics, robotics, and computational modeling. His work bridges engineering principles with biological applications, particularly in understanding human movement mechanics. Key trends include applying machine learning to gait analysis, developing enhanced spine models, analyzing human balance stability with time delays, and advancing musculoskeletal simulation techniques. As an academic advisor, Dr. Uchida currently supervises seven graduate students: Firas Baklouti (expected completion August 2025) Shahin Sharafi Kazem Alambeigi Jiawei Gao Yuzhen Yan Manuel Lucas De Oliveira Blake Scott Miller Dr. Uchida collaborates with research teams focused on biomechanics and movement science. His work with OpenSim places him within an international community of researchers developing computational tools for biomechanical analysis, connecting mechanical engineering with biomedical applications in sports, robotics, and rehabilitation.
Dr. Olga Zinovieva is a Lecturer in Mechanical Engineering and Program Coordinator at UNSW Canberra's School of Engineering and Technology. Her research focuses on computational modeling in metal additive manufacturing, particularly on processing-microstructure-property relationships. She has held research positions at the University of Bremen, Russian Academy of Sciences, and Tomsk Polytechnic University, and visiting roles in Australia, Germany, Brazil, and France. Research Interests: Modeling for additive manufacturing Multiscale methods Computational materials science Computational mechanics Microstructure evolution in 3D printing Mechanical behavior under dynamic loading Recent research trends from her publications emphasize predictive modeling of mechanical properties in additively manufactured metals, microstructure simulation, and digital solutions for advanced manufacturing. Her work integrates ICME approaches and high-performance computing to optimize alloy performance and process parameters. Scientific Awards and Grants: ARC Discovery Early Career Researcher Award (2025–2028) NSW DIN Pilot Project (2024–2025) CSIRO ON Prime Performance Bonus (2024) UNSW Start-up Grant (2022–2024) DFG-RFBR Project (2017–2022) Multiple travel and research grants from RFBR, University of Bremen, and Tomsk State University Supervision and Grants: Dr. Zinovieva actively supervises PhD and undergraduate research students in projects related to additive manufacturing modeling. She has secured over 20 grants as a Chief Investigator, including leadership in international collaborations between Germany and Russia. She mentors students through UNSW’s HDR programs and industry-linked research initiatives. Labs and Teams: She leads computational research in metal additive manufacturing at UNSW Canberra, utilizing high-performance computing resources. She collaborates with international teams at the University of Bremen and participates in editorial and advisory roles for journals such as Metals and Journal of Materials Informatics .
Jun Xiao is an Assistant Professor in the Department of Materials Science and Engineering at the University of Wisconsin-Madison since August 2021. He holds additional affiliations with the Physics and Electrical & Computer Engineering departments. His research focuses on quantum materials, light-matter interactions, and terahertz optoelectronics. Ph.D. in Applied Science and Technology from UC Berkeley (2018) Postdoctoral scholar at Stanford University and SLAC National Accelerator Laboratory Bachelor's degree in Physics from Nanjing University Research interests include structure-property relationships in quantum materials, ultrafast optical engineering, and THz device development. His lab explores non-equilibrium phase transitions, quantum collective excitations, and photocarrier dynamics for energy and computing applications. Recent publications emphasize topological semimetals for THz sensing, stacking order engineering in 2D materials, and spin-mechanical coupling in antiferromagnets. His group integrates ultrafast lasers, quantum transport measurements, and in-situ strain control to study ferroelectricity, magnetism, and electron correlations. Scientific awards include Nature Communications Editor's Suggestion (2018) Nature Nanotechnology publication (2015) Jun Xiao's lab operates 2D material preparation and multimodal characterization facilities, including ultrafast laser systems, CW light sources, and cryogenic strain cells. He teaches courses on quantum materials and device physics, including MS&E 803 and MS&E 456.
