Gaurav Arya is a Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University, with additional appointments in the Department of Chemistry and Biomedical Engineering. His research laboratory employs physics-based computational tools to investigate biological and soft-material systems at the molecular scale. Ph.D. from University of Notre Dame (2003) B.Tech. from Indian Institute of Technology Delhi (1998) Research focuses on: Molecular modeling and simulations Statistical mechanics DNA nanotechnology Viral DNA packaging Chromatin biophysics Polymer-nanoparticle composites Recent research trends emphasize AI-driven materials discovery and programmable DNA nanostructures. Key grants include: NSF DMREF: Architecting DNA nanodevices (2023-2027) DOE Mesoscale Self-Assembly (2020-2027) UC San Diego Ligand-Nanocrystal Interlayer Studies (2024-2027) Scientific contributions: Featured in 2025 Nature Communications on DNA superstructures 2022 Science Advances on DNA nanodevice reconfiguration 2021 PNAS on viral DNA packaging motors
Manuel Morales is an Associate Professor in the Department of Mathematics and Statistics at the University of Montreal since 2005. He holds a Ph.D. in Mathematics (2003) from Concordia University, an M.Sc. in Statistics (2000) from Concordia, and a B.Sc. in Mathematics (1996) from the National Autonomous University of Mexico. His research focuses on Financial and Actuarial Mathematics, particularly in Ruin Theory, Lévy processes, and High-Frequency Finance. He leads applied projects integrating Machine Learning in Banking and ESG Investment, and has pioneered AI governance frameworks at the National Bank of Canada as their Chief AI Scientist. Education: Ph.D. Mathematics, Concordia University, 2003 M.Sc. Statistics, Concordia University, 2000 B.Sc. Mathematics, National Autonomous University of Mexico, 1996 Research Interests: His work spans theoretical and applied directions, including non-Gaussian option pricing, regime-switching models, Limit Order Book dynamics simulation, and AI applications in finance. He emphasizes responsible investment and ESG factors through alternative data analysis. Advising & Partnerships: Supervises Master’s/Ph.D. students in Insurance and Financial Mathematics. Leads the FinML Network (since 2018) and collaborates with industry partners like the National Bank of Canada on AI-driven financial projects. His grants and contracts enable applied research in high-frequency market surveillance and model governance. Labs & Teams: Directs the FinML Network and oversees the National Bank’s AI initiatives, focusing on AI governance and algorithmic trading strategies.
CHENG Shih-Fen is an Associate Professor of Computer Science at Singapore Management University (SMU) and a Principal Research Scientist at Amazon. He holds a PhD in Industrial and Operations Engineering from the University of Michigan and a BSE in Mechanical Engineering from National Taiwan University. His research focuses on modeling and optimization of complex systems in urban computing, decision-making, and transportation, with notable contributions to taxi fleet management, ride-hailing systems, and sustainable logistics. Research interests include Artificial Intelligence , Decision Optimization , Machine Learning , and Urban Sustainability . Notable achievements include prestigious awards from CIKM, AAMAS, and INFORMS. He has advised students such as Qian Shao and Pang Jin Tan, who received SMU Presidential Doctoral Fellowships. Key contributions include the Driver Guidance System (DGS) for taxis and patented taxi demand prediction models. Publications span top venues like IJCAI, AAAI, and Transportation Science. He is a Senior Editor of Electronic Commerce Research and Applications and actively contributes to professional communities like INFORMS and AAAI.
Professor Zhenjun Ma is a Professor and Deputy Director of the Sustainable Buildings Research Centre (SBRC) at the University of Wollongong. He holds a PhD from The Hong Kong Polytechnic University and has expertise in renewable energy systems, thermal energy storage, and building energy efficiency. His research focuses on advancing sustainable HVAC solutions, building control optimization, and demand flexibility in energy systems. He has received prestigious awards including the World Society of Sustainable Energy Technologies Innovation Award and Excellence in HVAC&R Research from AIRAH. Education: BEng and MSc from Xian Jiaotong University; PhD from Hong Kong Polytechnic University. Current academic roles include editorial board memberships in journals like Renewable Energy and Energy Conversion and Management , and leadership in initiatives like the NSW Decarbonisation Innovation Hub. Research Interests: Renewable energy integration in buildings, thermal storage technologies, data-driven building analytics, and grid-to-building energy systems. Active in over 40 funded projects, including grants from Australia's Department of Industry and the NSW Government. Awards: Invitational Fellowship from Japan Society for the Promotion of Science (2025), Fellow of AIRAH (2021), and multiple best paper awards. Supervises over 30 PhD/Master’s students on topics like energy flexibility optimization and net-zero building systems. Labs/Teams: Leads SBRC’s energy efficiency and sustainability research clusters. Collaborates with industry partners like BlueScope Steel on solar energy solutions.
Dr. Mohammad Naraghi is a Professor in the Department of Mechanical Engineering at Manhattan University, specializing in thermal analysis of rocket engines, sustainable building systems, and radiative heat transfer. His research focuses on rocket thermal evaluation (RTE), solar energy optimization, and crystal growth processes. He holds a PhD from the University of Akron, MS from the University of Wales, and BS from the University of Tehran. Research areas include: Thermal modeling of regeneratively cooled rocket engines Radiative heat transfer in enclosures and aerospace systems Solar energy systems optimization (panel orientation, photovoltaic plants) Energy dynamics of green buildings and data centers CFD analysis of fluid flow and heat transfer in propulsion systems His 30+ years of publications span advanced thermal modeling techniques, including RTE software development and stochastic methods. Key contributions include NASA-recognized rocket engine thermal models and a patented seasonally selective building façade. Grants include NASA-funded rocket thermal research and ARPA/AFOSR crystal growth projects. Awards include ASME Fellow, AIAA Associate Fellow, and multiple NASA/ASEE fellowships. Teaching includes courses on solar energy systems, fluid mechanics, and green building energy dynamics. Advises graduate students in mechanical engineering and contributes to industry partnerships through applied thermal research.
Lamine M. Mili is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His expertise spans power systems, signal processing, and robust estimation theory. He holds an IEEE Fellowship (2016) for contributions to robust state estimation in power systems. Mili's research focuses on advancing methodologies for power system reliability, control, and integration of renewable energy sources. His work includes studies on dynamic state estimation, nonlinear dynamics, bifurcation theory, and quantum computing applications. He has contributed extensively to resilience engineering and computational social science in power systems. Mili’s recent articles address challenges in smart grids, quantum circuit error prediction, and multifractal signal analysis in EEG. His research often combines advanced statistical techniques with real-world grid data, emphasizing robustness and adaptability in dynamic environments. Education: Ph.D., University of Liège, 1987 M.S., University of Tunis, 1983 B.S., Swiss Federal Institute of Technology, Lausanne, 1976 Research Interests: Power system stability and control State estimation and robust filtering Quantum computing for power systems Resilience and cyber-physical-social systems Nonlinear dynamics and bifurcation analysis His recent publications reflect a focus on hybrid power systems, probabilistic methods, and data-driven approaches for grid optimization. The 2025 articles highlight advancements in photovoltaic state estimation, quantum error prediction, and robust modulation techniques. Mili’s work often bridges theoretical models with practical grid applications, emphasizing uncertainty quantification and real-time monitoring.
Professor Adrian Pagan holds the position of Professor of Economics at the University of Sydney's School of Economics. His research focuses on macro-econometric modeling, policy analysis, and business cycle theories. He has held visiting appointments at prestigious institutions including Oxford University and Princeton University. Key achievements include: Fellowships with the Academy of Social Sciences, Econometric Society, and Journal of Econometrics Medallist Fellow of the Modelling and Simulation Society of Australia and New Zealand Distinguished Fellow of the Economic Society of Australia Centenary Medal recipient (2001) His work emphasizes structural macroeconomic modeling, particularly in analyzing recurrent economic events and policy impacts. Recent research explores business cycle synchronization, financial frictions, and shock decomposition in macroeconomic systems. Publications span over four decades, with notable contributions to journals like Journal of Econometrics , Macroeconomic Dynamics , and European Economic Review . He has authored the influential 2016 book The Econometric Analysis of Recurrent Events in Macroeconomics and Finance .
Milton Boyd is a Professor in the Department of Agribusiness and Agricultural Economics at the University of Manitoba, Faculty of Agricultural and Food Sciences. He also serves as an Adjunct Professor in Risk Management and Actuarial Science at the Asper School of Business. His research and teaching focus on quantitative finance, risk management, derivatives, and international business. PhD, Purdue University, United States MA, Washington State University, United States BA, Seattle Pacific University, United States His research interests center on quantitative finance and agricultural risk management , with a strong emphasis on derivatives, portfolio strategies, and market behavior. He applies statistical and financial modeling to real-world agricultural and commodity markets, often integrating international and policy perspectives. His work bridges academic rigor with practical application in agribusiness and government sectors. His recent publications reflect a consistent focus on financial risk modeling, commodity pricing, and market efficiency. Themes include hedging strategies, volatility analysis, and the role of futures markets in price discovery and income stability. His work spans both developed and emerging markets, with increasing attention to Asia and global trade dynamics. Two University of Manitoba Awards for Research and Outreach Fellow of Seattle Pacific University Best Conference Presentation Award Outstanding Journal Paper Award Dr. Boyd has advised numerous graduate students and contributed to academic service through editorial roles, conference committees, and keynote presentations. He has secured research funding through university and external grants, though specific grants are not listed. His outreach includes media commentary, industry training, and policy advising, particularly in commodity market development. He has been actively involved in professional development and public service, including teaching short courses at the Winnipeg Commodity Exchange (ICE), Canadian International Grains Institute, and Canadian Securities Course. He has served as a Policy Advisor for the Frontier Center for Public Policy and as a columnist for Grainews , contributing to public understanding of financial and commodity markets.
Mircea R. Stan is a Professor of Electrical and Computer Engineering at the University of Virginia, serving as Director of Computer Engineering and Virginia Microelectronics Consortium (VMEC) Professor. He leads the High-Performance Low-Power (HPLP) lab and is an associate director of the Center for Automata Processing (CAP). His research focuses on AI hardware, Processing in Memory, Low Power Design, Cyber-Physical Systems, and Spintronics. Education: Ph.D. (1996) and M.S. (1994) from UMass Amherst; Diploma (1984) from Politehnica University, Bucharest. Research interests include energy-efficient computing architectures, IoT systems, and emerging technologies like magnetic skyrmions and memristors. He has pioneered work on asynchronous stochastic computing, thermal-aware microarchitecture, and microfluidic cooling for 3D-ICs. Key awards include the 2024 A. Richard Newton Technical Impact Award, 2018 ISCA Influential Paper Award, and IEEE Fellow (2014). He has held editorial roles at IEEE TVLSI, IEEE TNano, and IEEE Design & Test. Notable contributions include the HPLP lab’s advancements in low-power logic computing, the VCRFID framework for Industry 4.0, and thermal-aware design tools like Hot-LEGO and Cool-3D.
Dr. Charles Wang is a Reader in the Department of Physics at the University of Aberdeen, within the School of Natural and Computing Sciences. He has held this position since 2005 and is also an Honorary Cruickshank Lecturer in Astronomy at the same institution. His academic journey began with a BSc in Physics from National Taiwan University, followed by a Certificate of Advanced Study in Mathematics from Cambridge, and culminated in a PhD in Mathematical Physics from Lancaster University. Education: BSc (National Taiwan University), CASM (Cambridge), PhD (Lancaster) Current Position: Reader, Department of Physics, University of Aberdeen Additional Role: Honorary Cruickshank Lecturer in Astronomy Dr. Wang's research lies at the intersection of theoretical physics and experimental gravity, focusing on general relativity, quantum gravity, modified gravity, astrophysics, and cosmology. He is a pioneer in quantum gravity phenomenology, particularly through atom interferometry techniques. His work extends into applied mathematics, including differential geometry, Clifford algebra, and the Cosserat theory of rods. He actively collaborates with industry and research institutions on quantum sensing, gravity gradiometry, and precision measurement applications. His recent publications reveal a strong trajectory in quantum aspects of gravity, including Unruh radiation, gravitational decoherence, quantum sensing of spacetime fluctuations, and loop quantum gravity formulations. These works are published in high-impact journals such as Physical Review D, Classical and Quantum Gravity, and the European Physical Journal C. Scientific honors include being a Fellow of the STFC Centre for Fundamental Physics. He has secured significant research funding from sources like MoD/Dstl, EPSRC, UKSA, and BP for projects related to quantum gravity experiments and gravity sensing technologies. STFC Centre for Fundamental Physics Fellow Dr. Wang has supervised PhD students and contributed to major international collaborations such as STE-QUEST (ESA mission candidate), GG-TOP (with Birmingham), and CERN-related supernova research. He has also served in professional roles including Grampian Regional Organiser for the Institute of Physics in Scotland and as a Series Editor for Springer Briefs in Physics. He is affiliated with research groups including the Plasma Science Research Group (PSRG) and contributes to interdisciplinary initiatives such as the Advanced Centre for Energy and Sustainability (ACES).
Dr. Philip Brabazon is a Senior Lecturer at the University of Portsmouth, affiliated with the School of Organisations, Systems and People and the Centre for Operational Research & Logistics. His work focuses on operational research, logistics, and mass customization in industries such as automotive and manufacturing. He has published extensively on topics including order fulfillment systems, supply chain management, and production economics. Dr. Brabazon is currently accepting PhD students and has supervised 7 theses. His research explores themes like automotive order-to-delivery processes, virtual build-to-order systems, and the application of simulation in operational systems. He has contributed to understanding mass customization strategies, risk analysis in offshore operations, and safety case frameworks. His work bridges theoretical models with practical industry applications, particularly in optimizing supply chains and production systems. Notable publications include analyses of automotive logistics, long-tail retail dynamics, and Markovian approximations in fulfillment systems. His research has been cited over 100 times in key journals like the European Journal of Operational Research and Production and Operations Management.
Lars BEEX is a Senior Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine, Department of Engineering. He holds the right to supervise PhD students and has directed five to completion. His research focuses on computational mechanics of solids, including Bayesian inference, multiscale methods, and quasicontinuum approaches, with applications to materials like textiles, foams, and medical devices. His academic journey includes a PhD from Eindhoven University of Technology (2008-2012), supervised by Marc Geers and Ron Peerlings, as well as MSc and BSc degrees from the same institution. **Research Interests:** - Computational mechanics of solids - Bayesian inference and uncertainty quantification - Multiscale modeling (quasicontinuum method) - Mechanical modeling of fibrous and discrete materials - Phase-field damage models - Contact mechanics and elastoplasticity **Awards:** - Biezeno Solid Mechanics Award 2013 (Best PhD thesis in solid mechanics, Netherlands) - Cum laude distinction for both MSc and BSc degrees **Industrial Collaborations:** - SISTO Armaturen - IEE - Kiswire International **Teaching:** - Numerical methods for continuous optimization - Courses for Computer Science, Mathematical Modelling, and Engineering students **Lab/Affiliations:** - Legato Team (part of the University of Luxembourg's engineering research cluster)
Kristopher Klein is an Associate Professor at the Lunar and Planetary Laboratory (LPL), University of Arizona, within the Department of Planetary Sciences, College of Science. He earned his Ph.D. from the University of Iowa in 2013 and has been a faculty member at LPL since 2017. His research focuses on theoretical and computational plasma physics in the context of solar and heliospheric systems. Education: Ph.D., 2013, University of Iowa Years with LPL: 2017–present Dr. Klein's research centers on fundamental plasma phenomena in the heliosphere, particularly turbulent heating, energization mechanisms, and departure from thermodynamic equilibrium in collisionless plasmas like the solar wind. He employs analytic theory, numerical simulations (e.g., AstroGK, HVM, gkeyll), and spacecraft data from missions such as Parker Solar Probe and HelioSwarm. He is a co-developer of the Arbitrary Linear Plasma Solver (ALPS), an open-source tool for dispersion analysis. His recent publications (2019–2025) reveal a strong focus on plasma turbulence, wave-particle interactions, kinetic instabilities, and solar wind heating mechanisms. The work frequently combines Parker Solar Probe observations with theoretical modeling to understand energy transfer at kinetic scales. Themes include ion and electron heating, stochastic heating, cyclotron damping, and multi-scale turbulence characterization. Scientific Awards: 2024 AAS Harvey Prize 2022 Landau-Spitzer Award for Outstanding Contributions to Plasma Physics Dr. Klein advises graduate students including Niranjana Shankarappa and Waverly Gorman, with former student Teddy Broeren (Ph.D., 2023). He leads major NASA-funded research projects related to the HelioSwarm and Parker Solar Probe missions. His involvement includes being Deputy Principal Investigator for HelioSwarm and Co-Investigator and Project Scientist for the SWEAP instrument on Parker Solar Probe. These roles involve significant grant leadership and collaboration with interdisciplinary teams. He is actively involved in instrumentation and data analysis, particularly through quasi-thermal noise spectroscopy and wave-particle correlation techniques. His work bridges theory, simulation, and observational data to advance understanding of space plasma physics.
Andrea Carpinteri is a Full Professor of Structural Mechanics in the Department of Engineering and Architecture at the University of Parma, Italy. He has been a leading figure in the fields of fracture mechanics, fatigue of materials, and structural integrity for over three decades. He previously served as an Associate Professor at the University of Parma (1994–2000) and the University of Padua (1988–1994). He earned his degree in Civil Engineering from the University of Bologna in 1980 with top honors (110/110 cum laude). His academic journey reflects a strong foundation in structural engineering, which evolved into a research career focused on material failure mechanisms. His research interests include fracture mechanics , multiaxial fatigue , size effects in structures , fatigue crack propagation , and constitutive modeling of traditional and advanced materials . He has developed influential fatigue criteria, such as the Carpinteri-Spagnoli (C-S) criterion, and applied fractal theories to model fatigue behavior. His work bridges theoretical modeling, numerical simulation, and experimental validation. The 15 most recent publications highlight a consistent focus on multiaxial fatigue , fretting fatigue , crack path modeling , and energy-based life assessment . His research spans metallic alloys (e.g., Inconel 718, Al 7075), composites, and natural fiber-reinforced materials, often using critical plane and damage mechanics approaches. Recent works emphasize random loading, spectral analysis, and innovative modeling of crack morphology. ESIS Fellow (2012) IGF Honorary Member (2017) Publons Reviewer Award (Top 1% in Engineering, 2018) Multiple 'Most Active Reviewer Awards' (2013–2018) Winner of the BANDO OPEN-UP Prize (2018) International Prize on Renewable Energy Projects (2011) He has supervised numerous PhD students and collaborated with researchers globally. He has been the Principal Investigator or Local Coordinator of multiple national and EU-funded research projects, including H2020 and MIUR grants. His editorial leadership includes serving as Guest Editor for 26 special issues and as a board member of 10 international journals. He chairs TC3 (Fatigue) of ESIS and has organized over a dozen international conferences on fatigue and fracture. He leads research in structural integrity, particularly through his involvement in the Laboratory of Materials and Structures Testing at the University of Parma. His team focuses on both theoretical advancements and practical applications in civil, mechanical, and aerospace engineering.
Dr. Liya Zhao is a Senior Lecturer in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW Sydney), where she leads the Dynamic Smart Structures and Energy Harvesting Laboratory. She previously held academic positions at the University of Technology Sydney (UTS), first as a Lecturer (2017) and later promoted to Senior Lecturer (2021), before joining UNSW in 2022. Her research is highly interdisciplinary, focusing on smart structures, nonlinear dynamics, and sustainable energy technologies. Education: Ph.D. in Structures & Mechanics, Nanyang Technological University, Singapore (2015) B.Eng. in Civil Engineering, Tongji University, China (2009) Research Interests: Dr. Zhao's work centers on energy harvesting from ambient sources (wind, vibration, human motion, waves), smart materials (piezoelectric, triboelectric), metamaterials, and nonlinear dynamics. She designs adaptive structures for broadband energy harvesting and vibration suppression, with applications in self-powered wireless sensor networks, structural health monitoring, and wearable devices. Her research integrates theoretical modeling, numerical simulation, and experimental validation. Publication Trends: Over the past decade, her research has evolved from fundamental electromechanical modeling toward multifunctional metastructures and real-world deployment. Her recent work emphasizes hybrid energy harvesting, nonlinear tuning for broadband response, and integration with self-powered sensing systems, reflecting a strong trend toward practical, sustainable technologies. Scientific Awards: ARC Discovery Early Career Researcher Award (DECRA), 2021–2024 World's Top 2% Scientists (Stanford University), 2020–2023 Nanyang Engineering Doctoral Scholarship (NEDS), NTU Singapore Grants & Supervision: Dr. Zhao has secured multiple competitive grants, including ARC Discovery Projects and internal university funding, as both sole and chief investigator. She actively supervises research students and welcomes motivated candidates in mechanics, dynamics, and energy systems. Her lab, Dynamic Smart Structures and Energy Harvesting Lab , fosters innovation through experimental and computational research. She also contributes to teaching, including Mechanics of Solids II and Introduction to Aircraft Engineering. Lab & Team: She leads a dynamic research group focused on next-generation smart structures, supported by state-of-the-art facilities at UNSW. Her team develops novel materials and systems for sustainable energy and sensing, aiming to bridge the gap between fundamental science and real-world applications.
