John Leahy is the Allen Sinai Professor of Macroeconomics and Public Policy at the University of Michigan, holding dual appointments in the Department of Economics (College of Literature, Science, and the Arts) and the Gerald R. Ford School of Public Policy. As Chair of the Economics Department, he focuses on macroeconomic theory, monetary policy, and behavioral economics, particularly rational inattention models. His research emphasizes how cognitive limitations and information processing affect economic decisions, contrasting classical economic assumptions. Leahy has held positions at Harvard, NYU, and Boston University, and served as Coeditor of the American Economic Review and Editor of the American Economic Journal: Macroeconomics. He consults with Federal Reserve Banks, advocating for data-driven, question-first research methodologies. His work bridges theoretical rigor and practical applications, influencing policy analysis and academic discourse. Education: PhD in Macroeconomics from Princeton University; MSFS from Georgetown University; BA in Math and History. His research spans macroeconomic policy, structural change, and behavioral models of decision-making, with recent focus on wishful thinking and imperfect information processing. He collaborates widely, emphasizing interdisciplinary approaches and creative problem-solving. Key contributions include modeling rational inattention, analyzing age structure impacts on monetary policy, and exploring North-South economic disparities. His editorial leadership and academic mentorship reflect his commitment to advancing innovative economic inquiry.
Juan Baeza is a Senior Lecturer in Health Policy at King's Business School, King's College London. He holds a PhD from the University of Kent, an MSc from the London School of Economics, and a BA from Goldsmiths, University of London. His research focuses on health policy analysis, particularly examining the impact of health reforms on medical professions and health systems globally, with a focus on the UK's NHS, as well as Chile, Mexico, Russia, Sweden, Poland, and Australia. Affiliations: King's Business School, Department of Public Services Management and Organisation. Education: PhD in Health Policy (University of Kent, 2002), MSc in Economics (LSE, 1993), BA in Social Sciences (Goldsmiths, 1990). Research Interests: Baeza's work explores professional relations within healthcare, healthcare reform, evidence-based practice, and organizational change. He emphasizes how health policies are translated into actionable practices by healthcare professionals and how medical professions influence policy development and implementation. Recent Articles Trends: His publications highlight themes such as integrated care collaboration, the role of evidence in healthcare decision-making, and the governance of pluralist healthcare systems. Recent work includes analyses of pandemic discourse (e.g., Brazil's response to COVID-19) and the reconfiguration of health services in England. Grants & Projects: Co-investigator in projects like the AI-assisted fetal ultrasound trial (NIHR-funded) and studies on stroke care implementation across Europe. Teaching & Leadership: Teaches health policy modules, directs the intercalated BSc in Healthcare Management, and leads executive education programs. Labs/Teams: Active in the Integrated Care Systems (ICS) Research-Practice Network, organizing workshops on healthcare collaboration and prevention strategies.
Dr Thomas Paul Colley holds dual roles as Senior Lecturer in Defence and International Affairs at the Royal Military Academy Sandhurst and Senior Visiting Research Fellow in the Department of War Studies at King’s College London. His work bridges academic research and strategic policy application across multiple domains. Research Expertise Propaganda and strategic communication in conflict Strategic narratives in international relations Military strategy communication dynamics Insurgency and counterinsurgency frameworks Climate change strategic communication Social media analysis for defense applications Disinformation impact assessment Scientific Contributions 2022 : News Wars (book, with Martin Moore) 2021 : Book chapter on diplomatic engagement 2020 : Multiple high-impact articles on disinformation and insurgency Awards & Recognition Recipient of King’s College London’s Rising Star Teaching Excellence Award Featured expert in major UK media (BBC, The Times, The Independent) Consulting for UK government agencies (Home Office, Cabinet Office, DSTL) Teaching & Supervision Co-convenor of MA War Studies flagship modules PhD supervision on UK combatant memory of Afghanistan Global defense engagement training for international officers
Michael Kordell is a Lecturer at Texas A&M University, specializing in high-energy physics and particle physics. His research focuses on jet quenching, quark-gluon plasma dynamics, and Bayesian analysis of jet-medium interactions. He collaborates extensively with the JETSCAPE framework to simulate jet evolution in heavy-ion collisions. Key contributions include studies on photon-triggered jets, hybrid hadronization models, and multistage energy-loss mechanisms. His work spans 2013–2025, with over 30 publications. Major topics include jet substructure analysis, heavy flavor propagation in nuclear media, and parameter estimation techniques for QGP transport coefficients. His studies utilize both theoretical models and experimental data from small and large collision systems. Notable collaborations involve the JETSCAPE project, focusing on computational frameworks for jet shower simulation and in-medium effects. His research bridges particle physics with nuclear physics, particularly in understanding medium-induced effects on jet dynamics.
Daniel Halpern Jelin is an Associate Professor at Pontificia Universidad Católica de Chile. He directs the Master in Strategic Communication, the Diploma in Online Social Networks and Communications, and the Diploma in Tools for Internal Communication Management. Additionally, he leads the think tank Tren Digital and teaches courses on communication strategies in organizational contexts. He holds a Ph.D. in Communications from Rutgers University (USA), a Master's in Political Science (International Relations) from Pontificia Universidad Católica de Chile, and a Bachelor's degree in Social Information and Journalism from the same institution. His research explores the intersection of technology, communication, and society, with emphases on: Strategic communication frameworks in digital environments Social media dynamics and their societal impacts E-government adoption and public sector innovation Quantitative analysis of online behavior and organizational tech integration His recent publications (2012-2016) demonstrate cross-disciplinary work spanning communication theory, political science, educational technology, and human-computer interaction. Common themes include social media's effects on relationships, digital governance models, visualization pedagogy, and emerging technology acceptance. Notable scientific recognitions include: Fulbright Fellowship (2008-2011) Rutgers University Continuing Fellowship (2009-2011) Top Research Paper Award, Penn State (2009) Multiple travel and research grants from academic institutions He has secured research funding as Principal Investigator for projects including: Risks/opportunities of ICT in education (UC Public Policy) Social media's societal impact (FONDEDOC) Cyberbullying in Chile (VRI Initiation Grant) Senators' Twitter usage (Fulbright Summer Grant) He directs Tren Digital , a research think tank examining digital trends in organizational and social contexts.
Prof. Vesa Välimäki is an Audio Signal Processing Professor at Aalto University's School of Electrical Engineering, leading the Audio Signal Processing Research Group within the Aalto Acoustics Lab. He also serves as Vice Dean for Research and Head of the Doctoral Programme at the university. His research focuses on digital signal processing, machine learning, and their applications in audio, acoustics, and music technology, particularly in artificial reverberation, audio filter design, and virtual analog modeling. He has pioneered techniques like velvet noise for reverberation synthesis and contributed to open-source tools like FLAMO. His academic accolades include IEEE, AES, and AAIA Fellowships, along with multiple best paper awards at venues like DAFx and ICASSP. He has advised numerous students, including recipients of prestigious awards like the Huawei Master's Thesis Award. Prof. Välimäki has held editorial roles at the Journal of the Audio Engineering Society and organized major conferences such as SMC-17. His work extends to applied projects like acoustic optimization for early childhood education facilities and immersive audio in virtual reality (e.g., the 'Space Walk' project). Key Projects: NordicSMC (Nordic University Hub for Sound and Music Computing), Aalto Acoustics Lab, FLAMO library Grants: NordForsk funding (2018–2023), Foundation for Aalto University Science and Technology His research spans both theoretical advancements (e.g., diffusion models for audio restoration) and practical implementations (e.g., real-time equalizers, headphone compensation systems). He collaborates internationally, contributing to acoustic measurement techniques and noise reduction strategies for diverse environments.
Professor Rodrigo Freitas holds the TDK Professorship in Materials Science and Engineering at MIT. His research focuses on computational materials design, bridging atomistic simulations with mesoscale microstructural analysis. He leads the Freitas Research Group, specializing in machine learning-driven modeling of materials kinetics and solidification processes. Education: B.S. and M.S. in Physics, University of Campinas, Brazil M.S. and Ph.D. in Materials Science & Engineering, UC Berkeley Research Interests: Professor Freitas investigates microstructural evolution in metals and alloys using advanced computational methods. Key areas include solidification mechanisms, interstitial atom behavior in superalloys, and machine learning applications for materials discovery. His work emphasizes bridging atomistic and mesoscale phenomena to guide industrial applications like semiconductor manufacturing and battery design. Publications Trend: Recent work emphasizes machine learning potentials for alloy modeling, short-range order analysis in high-entropy alloys, and kinetic modeling of complex chemical systems. Themes include alloy phase stability, defect dynamics, and data-driven materials discovery. Labs/Teams: Leads the Freitas Research Group at MIT, which develops novel computational tools for materials engineering.
Professor Julia Race is a leading academic in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde’s Faculty of Engineering, where she also serves as Vice Dean (Academic). Her research focuses on the role of pipeline infrastructure in achieving net-zero emissions, particularly through carbon dioxide transport for Carbon Capture and Storage (CCS) and hydrogen energy systems. PhD, University of Cambridge – Carbon diffusion across dissimilar steel welds (1992) BEng, University of Sheffield (1989) Her research interests center on the adaptation of energy infrastructure for decarbonization, combining engineering, risk assessment, and socio-economic analysis. She investigates material specifications for CO₂ and H₂ pipelines, quantitative risk assessments, hydraulic design, and the wider economic impacts of energy transitions. Her work is closely tied to UN Sustainable Development Goals, particularly those related to climate action and sustainable industry. The recent publications reflect a strong trend toward interdisciplinary research at the intersection of engineering, economics, and policy. Her work increasingly emphasizes the socio-economic dimensions of decarbonization, including employment impacts, labour supply constraints, and regional economic benefits of CCS and hydrogen infrastructure. There is a clear focus on UK industrial clusters and the role of Scottish CO₂ transport systems in national and international markets. Julia Race has contributed to several policy briefings and collaborative reports with key stakeholders including the Scottish Government, OEUK, and Storegga. She is actively engaged in research projects funded by EPSRC, NERC, and the British Council, focusing on early-career development, maritime decarbonisation, and engineering education equity. Co-investigator, Strathclyde Engineering Scholars – Equal Outcomes for the Most Disadvantaged (2025) Principal Investigator, EPSRC/NERC CDT in Offshore Renewable Energy (IDCORE 2) (2019–2028) Co-investigator, Empowering Early Career Researchers to Advance Maritime Decarbonisation in Indonesia (2024–2026) Co-investigator, Green Hydrogen Integration at Sullom Voe (2023–2024) She plays a key role in policy outreach and professional engagement, regularly participating in workshops and meetings with government and industry stakeholders. Her leadership extends to diversity and inclusion in engineering education, where she contributes to initiatives aimed at supporting disadvantaged students.
Julie Dorsey is the Frederick W. Beinecke Professor of Computer Science at Yale University, where she teaches computer graphics. She joined Yale in 2002 after holding tenured positions at MIT in both the Department of Electrical Engineering and Computer Science and the School of Architecture. She earned undergraduate degrees in architecture and graduate degrees in computer science from Cornell University. Research Areas: Photorealistic image synthesis Material and texture modeling Interactive visualization of complex scenes Sketch-based design interfaces Acoustical and lighting design algorithms Recent Article Trends focus on AI-driven graphics techniques, 3D hair modeling, depth sensing, and cultural heritage preservation. These works reflect her interdisciplinary approach bridging computer science, art, and physics. Scientific Awards: MIT Edgerton Faculty Achievement Award NSF Career Award Alfred P. Sloan Research Fellowship Radcliffe Institute Fellowship (2010-11) Whitney Humanities Center Fellowship (2010-12) Editorial Contributions: She serves as Editor-in-Chief of ACM Transactions on Graphics and has held editorial roles at Computers and Graphics, Foundations and Trends in Computer Graphics and Vision, and SIGGRAPH 2006 Papers Chair. Labs & Collaborations: Leads Yale's Computer Graphics Group, contributes to interdisciplinary projects at the intersection of computing and the arts, and collaborates with researchers in biomedical and industrial AI applications.
Professor David Taubman is a distinguished academic serving as Professor and Deputy Head of School (Research) at the School of Electrical Engineering and Telecommunications (EE&T) at the University of New South Wales (UNSW) in Sydney, Australia. He is also co-director of Kakadu Software Pty. Ltd. and its affiliates Kakadu R&D and Kakadu GPU. With a career spanning over three decades, Professor Taubman has made significant contributions to the field of image and video compression, most notably as the author of the EBCOT coding algorithm adopted in the JPEG2000 international standard. Professor Taubman earned his B.Sc. in Mathematics and Computer Science (1986) and B.E. (Medal) in Electrical Engineering (1988) from the University of Sydney, followed by an M.Sc. (1992) and Ph.D. (1994) in Electrical Engineering from the University of California at Berkeley. His professional journey includes engineering work at the Electricity Commission of N.S.W. (1988-1990), research positions at Hewlett-Packard Laboratories in Palo Alto (1994-1998), and an academic career at UNSW where he progressed from Senior Lecturer (1998-2003) to Associate Professor (2004-2009) and finally to Professor (2009-present). He has held various leadership roles including Head of the EE&T Telecommunications Research Group (2003-2014), Head of the EE&T Signal Processing Research Group (2014-present), Director of Research for the School of EE&T (2011-2016), and Deputy Head of School (Research) since 2017. Professor Taubman's research interests center on image and video compression, with particular expertise in JPEG2000 standards and implementations. His work spans signal processing, wavelet transforms, scalable video coding, motion modeling, and multimedia systems. He has pioneered numerous compression algorithms and frameworks, including the EBCOT coding algorithm that became central to the JPEG2000 standard. His recent research focuses on efficient motion modeling with cuboidal partitioning, learned lifting-based transform structures, and high-throughput implementations of JPEG2000 for video applications. His work bridges theoretical foundations with practical implementations, as evidenced by the commercially successful Kakadu Software tools that have garnered around 500 commercial licensees. Analysis of Professor Taubman's recent publications reveals a consistent focus on advancing compression technologies with particular emphasis on scalability, efficiency, and adaptability. His work spans traditional image compression (JPEG2000 extensions), video coding (cuboid-based partitioning for UHD/360-degree video), and emerging applications (nanopore sequencing data compression). A notable trend is the integration of machine learning techniques with traditional compression frameworks, as seen in his work on learned lifting-based transform structures. His research maintains strong connections to real-world applications across diverse domains including medical imaging, astronomical data processing, and genomic sequencing. IEEE Fellow Engineers Australia Fellow (by invitation) Professor Taubman has served as Associate Editor for the IEEE Transactions on Image Processing for two four-year appointments (2003-2005 and 2010-2013). He has been actively involved in numerous research grants focused on image and video compression technologies, particularly those related to the JPEG2000 standard and its extensions. His work has received significant industry support, reflected in his consultancy with various U.S., Japanese, and Australian corporations. He has also contributed to international standards development as a member of Standards Australia Technical Committee MS-065 (mirroring ISO TC42 on Digital Photography) and as a constitutional member of Standards Australia Technical Committee IT-029 (Coded Representation of Picture, Audio and Multimedia/Hypermedia Information). Professor Taubman co-directs Kakadu Software Pty. Ltd. and its research affiliates Kakadu R&D and Kakadu GPU, which have developed the commercially successful Kakadu Software tools for JPEG2000. His research group at UNSW focuses on advanced image and video compression techniques, with particular expertise in wavelet-based methods, scalable coding, and motion modeling. The group maintains strong industry connections and has contributed significantly to the development and standardization of image compression technologies worldwide.
Prof. Dr. Sven Heidenreich is a full Professor of Business Administration, specializing in Technology and Innovation Management at the University of Saarland. He leads an active research group and holds a prominent position in the German-speaking academic community, with consistent recognition in national and international rankings. University: University of Saarland Department: Business Administration Research Focus: Technology and Innovation Management Email: sven.heidenreich@uni-saarland.de His research centers on innovation processes, particularly consumer integration, co-creation, resistance to innovation, and sustainable business models. He employs a quantitative-empirical approach to study individual and organizational aspects of innovation, with applications in digital services, video games, and green innovation. The recent publications reflect a strong trend in understanding consumer behavior in innovation contexts, including greenwashing, leapfrogging, co-creation, and the role of personality in entrepreneurial success. His work frequently appears in high-impact journals such as Journal of Product Innovation Management , R&D Management , and Technological Forecasting and Social Change . Top 0.5% researcher worldwide in Innovation Management (ScholarGPS 2024) JPIM Outstanding Reviewer Award 2023 Multiple appearances in WirtschaftsWoche Economist Rankings (2018–2024) Finalist, Best Paper Award, IRCSM 2024 Prof. Heidenreich supervises doctoral researchers and has led significant research projects, including the DFG-funded TRIP project on integrating different consumer types into new product development. His team includes postdocs, junior professors, and scientific staff, indicating active mentorship and collaborative research. He also collaborates with researchers across Europe and beyond. He leads the DFG project TRIP and has secured funding from major German research bodies. His lab focuses on empirical studies involving consumer panels, student experiments, and idea competitions to validate innovation theories in realistic settings.
Zhijian Huang is an Associate Professor in the Department of Finance and Accounting at Saunders College of Business, Rochester Institute of Technology, with expertise in corporate finance, behavioral finance, and risk management. Education: B.Eng., Shanghai Jiaotong University (China) M.S., Michigan State University M.Eng., Cornell University Ph.D., Pennsylvania State University His research focuses on financial markets, cognitive dissonance in investor behavior, cryptocurrency volatility, and climate policy impacts on stock prices. Recent publications explore asymmetric responses to earnings news, social media sentiment effects, and credit risk modeling. Huang teaches courses in equity analysis, options/futures, and risk management, with a strong emphasis on derivative instruments and portfolio optimization strategies.
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Kash Barker serves as the John A. Myers Professor and David L. Boren Professor at the University of Oklahoma in the Department of Industrial & Systems Engineering within the College of Engineering. As Graduate Liaison, he leads research on network resilience, supply chains, and systems engineering for societal good, with applications spanning infrastructure, supply chains, and community systems. His lab has produced 11 Ph.D. graduates (10 in academia) and 31 M.S. graduates. Research Domains: Resilient networks and interdependent systems Risk and decision analytics Supply chain survivability Pandemic economic impact modeling Climate migration optimization Cyber-Physical-Social Systems Article Trends emphasize disinformation defense , network restoration optimization , and multi-layer resilience modeling across infrastructure, supply chains, and community systems. His work combines game theory , machine learning , and decision analysis frameworks. Scientific Awards & Roles: Fellow, Institute of Industrial and Systems Engineers Senior Member, IEEE Fellow, Fulbright Finland Foundation (2023) Associate Editor roles in IISE Transactions and Naval Research Logistics Editorial Board Member for Risk Analysis and Scientific Reports Faculty Advisor, OU INFORMS student chapter Educational Background: Ph.D., Systems Engineering, University of Virginia M.S., Industrial Engineering, University of Oklahoma B.S., Industrial Engineering, University of Oklahoma
Nicolas Riviere is a Professor at INSA Lyon in the Department of Mechanical Engineering, working within the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509). He is part of the "Fluides complexes et transferts" (Complex Fluids and Transfers) group and the Environment team. His teaching activities primarily focus on fluid mechanics at the Mechanical Engineering Department of INSA Lyon, covering: General balances (mass, momentum, energy) Aerodynamics Compressible flows Numerical simulation of flows Free surface hydraulics Prof. Riviere's research centers on free surface hydrodynamics, with applications to natural and industrial risks. His work takes an experimental approach, utilizing the laboratory's channel facilities, particularly the channel intersection installation. His research spans river floods with compound beds, urban flooding, sanitation networks, torrential flows, and flow-obstacle interactions. He has developed a strong interdisciplinary focus, co-leading the "Baignades en Rivières Urbaines" studio with Oldrich Navratil from University Lyon 2 and the EVS Laboratory. His publication record demonstrates consistent contributions to the fields of fluid mechanics and environmental hydraulics, with recent work focusing on open-channel flows, urban flooding phenomena, vegetation-flow interactions, and experimental techniques for studying complex hydraulic phenomena. His research often bridges theoretical fluid mechanics with practical environmental applications. Prof. Riviere has received recognition for his work in environmental fluid mechanics, with numerous publications in high-impact journals in hydraulic engineering and fluid mechanics. He has supervised multiple PhD students and research projects related to environmental fluid mechanics and has collaborated with various institutions on interdisciplinary research projects addressing water-related challenges. The laboratory where he works, LMFA, provides extensive experimental facilities including wind tunnels, hydrodynamic channels, and advanced measurement techniques such as PIV (Particle Image Velocimetry), LDV (Laser Doppler Velocimetry), and other state-of-the-art instrumentation for fluid flow analysis.
