Lars Davidson is a Professor in the Department of Fluid Dynamics at Chalmers University of Technology. His research focuses on numerical simulations of fluid flow and heat transfer, with an emphasis on turbulence modeling for Large Eddy Simulation (LES) and hybrid LES/RANS methods. He has developed computational codes CALC-BFC and CALC-LES based on finite-volume techniques, and recently integrated machine learning to enhance wall functions and turbulence models. Key projects include Hybrid LES/RANS for wall-bounded flows Machine learning applications in fluid dynamics Aeroacoustic noise reduction in automotive and aerospace systems Wind turbine load analysis in forested regions . His publications span 302 articles in journals and conferences, with recent work on Neural networks for turbulence closure Plasma actuators for drag reduction Lattice Boltzmann wall-modeled LES . Collaborations include teams at Volvo, Siemens, and international research groups.
Ratnak SOK is an Associate Professor at Waseda University, specializing in thermal engineering, electrified vehicles, and internal combustion engine research. His work spans transportation electrification , CFD modeling , waste heat recovery , and low-carbon/e-fuel ICEs with aftertreatment systems. Doctor of Engineering (2015, Waseda University) MSME (2011, Institut Teknologi Bandung) Diplôme d'Ingénieur (2009, Institut de Technologie du Cambodge) DUT (2006, Institut de Technologie du Cambodge) His research focuses on xEV thermal management , internal combustion engine efficiency , and thermoelectric waste heat recovery , supported by 44 peer-reviewed papers and 340 Scopus citations. Recent work integrates machine learning and CFD simulations for combustion control and battery modeling. Scientific accolades include: Young Investigator Award (2025 Japan Society of Automotive Engineers) SAE International Journal editorial board member Chair, 2025 ASME Rail Transportation Symposium His academic leadership extends to organizing technical sessions at IEEE, SAE, and FISITA conferences.
Alessandro Battaglia is an Associate Professor at the Department of Environmental, Land and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. He specializes in microwave remote sensing of clouds and precipitation, with expertise in Doppler radar, cloud and snow microphysics, and microwave radiometer technology. His research spans atmospheric physics, meteorology, and climate science with applications in Earth observation from space. Dr. Battaglia's research interests focus on remote sensing of atmospheric phenomena, particularly using advanced radar technologies. His work encompasses cloud microphysics, precipitation measurement, and wind observation from space. He is particularly known for his contributions to the development of spaceborne Doppler radar systems for measuring in-cloud winds, which represents a significant advancement in atmospheric observation capabilities. His research bridges engineering, physics, and meteorology to improve our understanding of Earth's atmospheric processes and climate systems. His recent publications demonstrate a strong focus on the WIVERN (Wind Velocity Radar Nephoscope) mission, with research spanning cloud microphysics, snowfall measurement, wind field reconstruction, and innovative radar signal processing techniques. These works highlight the interdisciplinary nature of his research, connecting atmospheric science, engineering, and computational methods to advance space-based Earth observation capabilities. NASA Group Achievement Award (2015) Fellow of the National Center for Earth Observation, UK (2014-present) Dr. Battaglia actively mentors several PhD students including Marco Coppola, Francesco Manconi, Riccardo Rabino, Susmitha Sasikumar, Aida Galfione, and Paolo Martire across Civil and Environmental Engineering and Aerospace Engineering programs. He serves as Principal Investigator for multiple research projects funded by ESA (3 projects), UK-NERC (1 project), UK-NCEO (1 project), and the US Department of Energy (1 project). His current research focuses on the WIVERN mission, EarthCARE mission, and NASA's INCUS mission, with particular emphasis on developing algorithms for spaceborne Doppler radar systems. He leads research teams working on cutting-edge remote sensing technologies for atmospheric observation, with particular focus on developing the next generation of spaceborne instruments capable of measuring in-cloud winds—a capability that has been missing from Earth observation systems until now.
Dr. Adrian Fazekas is a Lecturer at the Institute of Highway Engineering, RWTH Aachen University, and collaborates with the Federal Highway Research Institute (BASt). He holds a Dr.-Ing. in Computer Science from RWTH Aachen (2005–2011), specializing in Media Engineering. His professional trajectory includes roles as a Research Assistant at RWTH Aachen and industry experience as a Software Developer at Continental AG. Research interests focus on traffic data acquisition , microscopic traffic flow simulation , and intelligent transportation systems . Key projects include: DROVA: Drone-based traffic analysis for infrastructure optimization ESIMAS: Real-time tunnel safety management Digital Twin Road: Physical-informational mapping of future highways AUTUKAR: Automated tunnel monitoring systems His publications emphasize real-time traffic detection , safety analytics , and data-driven modeling , with recent work exploring thermal-camera nudging systems and weigh-in-motion accuracy. He actively contributes to the Research Association for Roads, Earth and Tunneling (SETAC). No awards or student advising roles are documented.
Prof. Dr. Jochen Garcke is a faculty member at the Institute for Numerical Simulation, University of Bonn, with a dual affiliation at Fraunhofer SCAI's Department of Numerical Data-Based Prediction. His work bridges numerical simulation and machine learning, focusing on high-dimensional problems, sparse grids, and optimal control. Key research themes: Sparse grids, machine learning for simulations, reinforcement learning, uncertainty quantification Teaching includes courses on Numerical Methods in Science and Technology and Scientific Computing , emphasizing practical machine learning applications. Recent publications explore hybrid models combining data-driven and physics-based approaches in automotive engineering, wind turbines, and geoscientific modeling. His group employs adaptive sparse grids, graph algorithms, and spectral methods to tackle challenges in crash simulations, fluctuating renewable energy systems, and turbulent flow analysis. Collaborations span Fraunhofer SCAI and industry 4.0 initiatives.
Professor Timothy Chen is an academic at The University of Sydney , affiliated with the Brain and Mind Centre and the Charles Perkins Centre . He holds qualifications including a PhD, DipHPharm, BPharm, and professional certifications like MPS, MSHP, ARPharmS, FFIP. Research Focus : Medication management and safety, quality use of psychotropic medicines, and interprofessional collaboration in healthcare. Awards & Leadership : President of the Social and Administrative Section of the International Pharmaceutical Federation (FIP), Australian Award for University Teaching (2017), and key roles in global pharmacy policy. Key Contributions : Led the Home Medicines Review (HMR) program, supervised six PhD students to completion, and secured competitive research funding exceeding $2 million. His work spans clinical pharmacology, mental health, and geriatric pharmacy. Scientific Awards : Australian Award for University Teaching (2017) Elsevier Best Paper Award (2013) SUPRA Supervisor of the Year Finalist (2016) Distinguished Expert, Xi’an Jiaotong University (2017-2022) Current Research includes co-designing dementia care tools, validating Arabic medication burden instruments, and developing quality indicators for community pharmacy services. His team explores medication reconciliation, deprescribing, and mental health stigma reduction through pharmacist-led interventions.
David S. Corti is the Interim Jay and Cynthia Ihlenfeld Head of the Davidson School of Chemical Engineering at Purdue University, where he also serves as a Professor of Chemical Engineering and Director of Undergraduate Studies. His research focuses on thermophysical and kinetic properties of soft condensed-phase systems, including metastable liquids and colloidal dispersions. He employs theoretical and simulation techniques to study phenomena such as bubble nucleation and entropic force fields in colloidal systems. Corti holds a B.S. from the University of Pennsylvania (1991), an M.A. from Princeton University (1993), and a Ph.D. from Princeton (1997). His scientific contributions include advancements in understanding metastable liquid behavior, colloidal stability, and Hamaker constant estimation via atomic force microscopy. Notable honors include the NSF CAREER Award (2002), the 'Teaching for Tomorrow' Award (2002-2003), and University Faculty Scholar designation (2011-2016). Corti collaborates extensively, notably with Prof. Elias I. Franses on dispersion stability projects. His advising includes graduate student Betty Yung-Jih Yang. Research themes span bubble nucleation mechanisms, entropic control of colloids, and surfactant effects on nanoparticle stability. Corti's work bridges fundamental theory with industrial applications, addressing challenges in materials science and chemical engineering.
Sonia A. Fahmy is a Professor of Computer Science and Associate Department Head at Purdue University's Department of Computer Science (College of Science). She holds a PhD from The Ohio State University (1999). Her research focuses on network architectures, protocols, and security, with over 100 refereed publications. Key areas include virtual reality networking, cellular network optimization, and network experimentation tools like NFV-VITAL and ENVI. Her work is supported by NSF, DHS, industry partners, and she leads Purdue's CERIAS cybersecurity initiatives. Education: PhD in Computer and Information Science from The Ohio State University (1999). Research Interests: Network security, distributed systems, wireless sensor networks, and network function virtualization. Notable contributions include the HEED clustering algorithm and Contain-ed latency management system. Awards: NSF CAREER Award (2003), IEEE Fellow. Grants: NSF, DHS, AT&T, Cisco, Juniper, and Meta-funded projects. Professional service includes leadership roles in IEEE ICNP, INFOCOM, and editorial roles in top journals. Advising: Mentored over 20 PhD students and postdocs. Current advisees include Umakant Kulkarni and Yufeng Chen. Research teams collaborate with industry partners like Hewlett-Packard and Sandia National Labs. Labs/Teams: Active in Purdue's CERIAS, leading projects on secure network protocols and experimentation frameworks. Tools developed include EMIST, Testbed Mapping, and iHEED for sensor networks.
Jianqi Xi is an Assistant Professor in the Department of Nuclear, Plasma & Radiological Engineering at the University of Illinois Urbana-Champaign, affiliated with The Grainger College of Engineering. His research focuses on nuclear materials, combining multiscale modeling with experimental techniques to understand material degradation under radiation and corrosive environments. He holds a Ph.D. in Materials Science and Engineering from the University of Tennessee-Knoxville (2017). Before joining UIUC, he held postdoctoral and industry positions at the University of Wisconsin-Madison and ThermoFisher Scientific. Research Interests: Fusion Materials Design Radiation-Corrosion Synergy Multiscale Modeling of Microstructure Evolution Data-Driven Materials Innovation Molten Salt Corrosion Recent publications emphasize atomic-scale mechanisms in silicon carbide (SiC) corrosion, radiation damage mitigation, and advanced ceramics design. His work bridges computational simulations with experimental validation to address challenges in nuclear energy systems. Awards include the Joseph E. Spruiell Award (2017) and recognition as an Outstanding Reviewer (2018). He leads the Modeling of Nuclear Materials (MNM) Group , focusing on interdisciplinary approaches to accelerate material discovery for next-generation nuclear reactors. Current openings exist for researchers interested in computational materials science and experimental collaborations.
Kaliramesh (Kali) Siliveru is an Associate Professor and University Outstanding Scholar in the Department of Grain Science and Industry at Kansas State University. His work focuses on grain processing, food safety, and process modeling , with expertise in milling technologies, particle mechanics, and material handling. He holds a B.S. in Food Science from Acharya N.G Ranga Agricultural University, India, and a Ph.D. in Grain Science from Kansas State University. Dr. Siliveru’s research has produced 75+ peer-reviewed articles, 13 book chapters , and impactful studies on reducing microbial contamination in wheat-based products, optimizing pulse processing, and advancing nonthermal technologies like cold plasma. He has received prestigious awards including the ASABE Early Career Engineer of the Year and the University Distinguished Faculty Award for undergraduate mentoring. He teaches GRSC 310 (Materials Handling) , GRSC 810 (Particle Technology) , and GRSC 840 (Advanced Grain Processing) . His lab affiliations include the BIVAP Feed Quality Assurance Lab and Hal Ross Flour Mill, where he explores milling efficiency, microbial control, and sustainable food processing . Current projects address novel applications for minor millets and engineering solutions for safe, nutritious food production.
Dr. Alan Lloyd is an Assistant Professor in Civil Engineering at the University of New Brunswick, specializing in structural response to extreme loads. He directs experimental research at the Drop Mass Impact Test Facility, focusing on blast-resistant design and retrofit techniques. Education: PhD Civil Engineering, University of Ottawa MASc Civil Engineering, University of Ottawa BEng Civil Engineering, Lakehead University Diploma Civil Engineering Technology, Camosun College Research: Investigates blast/impact effects on structures, structural retrofitting, material behavior under high strain rates, and experimental validation using shock tubes and impact testing. Current projects include developing blast-resistant building components and retrofit solutions for existing infrastructure. Publications: Focus on blast dynamics, FRP composites for structural strengthening, and experimental mechanics. Recurring themes include concrete/wood material performance under explosive loads and design methodologies for blast mitigation. Awards: NSERC Graduate Scholarships National Security Innovation Competition prizes (2010, 2011) ACI Blast Prediction Contest winner Advising: Supervises graduate students researching FRP materials, concrete properties, and structural modeling. Manages industry collaborations on blast-resistant technologies. Facilities: Leads development of the Drop Mass Impact Test Facility for structural component testing under controlled impact conditions.
Dr. M.Z. Naser is an Assistant Professor in the Glenn Department of Civil Engineering at Clemson University. His research focuses on causal and explainable machine learning methodologies applied to structural engineering, materials science, and fire safety. He holds a PhD from Michigan State University and an M.S. from the American University of Sharjah. Naser teaches courses such as Machine Learning for Civil Engineers and Structural Fire Engineering, emphasizing interdisciplinary innovation. His work bridges data-driven analysis with domain-specific knowledge to address challenges in resilient infrastructure design, including fire-resistant materials, structural retrofits, and AI-driven decision-making. Education: PhD, Michigan State University; M.S., American University of Sharjah Research Themes: Explainable AI, Fire Engineering, Structural Materials, Causal Inference Key Projects: Developing SPINEX framework, wildfire classification models, and cognitive infrastructure systems Recent publications analyze over 1000 fire tests to uncover spalling mechanisms, explore synthetic fire tests via GANs, and benchmark automated ML platforms. His work on causal diagrams for civil engineers and firefighter algorithms highlights contributions to both theory and practical applications. Naser also advocates for integrating AI into engineering education, emphasizing ethical and transparent model deployment.
Dr Sudip Mittal is an Assistant Professor in Computer Science & Engineering at Mississippi State University and Associate Research Director of the PATENT Lab. His research spans cybersecurity, artificial intelligence, and cyber-physical systems, with a focus on building self-protecting systems and predictive security for unmanned vehicles. He leads the SECRETS Lab and has published over 70 papers in top venues, with work featured in The LA Times and WIRED. Research interests include: Autonomous intrusion response systems AI-driven threat detection in IoT/CPS Adversarial machine learning His publications (2019-2025) show a strong emphasis on AI security applications, particularly in malware detection, healthcare compliance, and anomaly detection using large language models. Recent articles explore MLOps security, adaptive cyber defense, and synthetic data generation for critical systems.
Eric Nauman is the Dane A. and Mary Louise Miller Professor of Biomedical Engineering at the University of Cincinnati and director of the Human Injury Research and Regenerative Technologies (H.I.R.R.T.) Lab. Previously, he held academic roles at Purdue University and Tulane University. He earned his Ph.D., M.S., and B.S. in Mechanical Engineering from UC Berkeley and the University of Delaware. Research Focus: The H.I.R.R.T. Lab investigates mechanisms of traumatic brain injury, spinal cord injury, musculoskeletal damage, atherosclerosis, and cancer metastasis. It develops protective and reconstructive treatments, including FDA-approved engineered tissue products for tendon repair. Collaborative projects emphasize translational research in injury prevention and treatment delivery. Grants & Awards: Lead Principal Investigator (PI) on federal grants totaling $4.7M for projects like AFRL teeming agreements and DoD biomathematical models. Recipient of prestigious awards including the Purdue Book of Great Teachers, Innovators Hall of Fame, and multiple teaching excellence recognitions. Key Contributions: Co-authored landmark TBI studies, holds 14 U.S. patents, and pioneered protective equipment innovations. His work bridges biomechanics, materials science, and clinical applications.
Ronald D. Haynes is a Full Professor and Chair of Scientific Computing Graduate Programs in the Department of Mathematics and Statistics at Memorial University of Newfoundland. He leads research in numerical methods for PDEs and industrial-scale optimization problems. His work develops advanced domain decomposition techniques, adaptive mesh methods, and parallel computing approaches for solving complex physical systems. Applications include modeling pitting corrosion of materials, predicting rock strength for drilling optimization, and simulating multiphase fluid flows in porous media. Recent publications demonstrate innovations in mesh adaptation, parallel algorithms, and machine learning applications for industrial problems. Collaborative projects have addressed reservoir simulation, drill bit analysis, and corrosion prediction through integrated computational approaches. Professor Haynes has received the President's Award for Outstanding Research (2018) and Dean of Science Distinguished Teaching Award (2017). He serves as Co-editor-in-chief of the CAIMS Mathematics in Science and Industry Journal and was President-Elect of the Canadian Applied and Industrial Mathematics Society (2023-2025). He maintains active doctoral supervision with current research groups focusing on domain decomposition methods, closest point algorithms, and optimization techniques. Industry partnerships include projects with ExxonMobil and Global Maritime addressing drilling optimization and mooring design challenges.
