Ali Mani is an Associate Professor of Mechanical Engineering at Stanford University and a faculty affiliate at the Institute for Computational and Mathematical Engineering. He earned his PhD in Mechanical Engineering from Stanford in 2009, following an M.S. (2004) and B.S. (2002) from Stanford and Sharif University of Technology, respectively. His research focuses on fluid mechanics, turbulence, and numerical simulations, with applications in multiphase flows, electrokinetic systems, and applied mathematics. His group develops high-fidelity simulation tools and reduced-order models to understand transport processes in turbulent and chaotic systems. Research interests include turbulence modeling, two-phase flow dynamics, and electrochemical transport. Recent work explores eddy viscosity operators, nonlocal transport phenomena, and computational methods for multiphase systems. The group's studies often bridge experimental validation and numerical analysis to improve predictive engineering models. Key contributions span electrokinetic transport in porous media, superhydrophobic surface slip effects, and phase field modeling. His lab’s work is supported by grants focusing on fluid dynamics, renewable energy systems, and advanced simulation frameworks.
Jishen Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego (Jacobs School of Engineering). His research focuses on computer architecture, non-volatile memory systems, and deep learning acceleration. Dr. Zhao has published extensively in top venues including ISCA, MICRO, ASPLOS, and IEEE Transactions. He collaborates with researchers at UCSD and beyond to advance systems for emerging applications in AI and autonomous vehicles. Dr. Zhao's primary research areas include persistent memory systems, hardware/software co-design for deep learning, and safety-critical computing. He develops techniques for crash consistency, memory disaggregation, and efficient neural network deployment. His work on autonomous vehicles addresses scenario generation and perception-aware system design. Recent projects explore LLM applications for software engineering and hardware verification. Analysis of Dr. Zhao's 2024-2025 publications reveals a strong shift toward AI-integrated systems research. He applies large language models to tasks like RTL verification and software issue localization while continuing to innovate in memory systems for serverless computing. There is growing emphasis on safety-critical systems for autonomous vehicles and energy-efficient neural network training using novel hardware architectures. Information about Dr. Zhao's scientific awards, advising activities, grants, and laboratory facilities was not available in the provided documentation.
Susan Smith-Peter is a Professor of History at the College of Staten Island, City University of New York, specializing in Russian history beyond Moscow and St. Petersburg. Her research focuses on regional identity, civil society development, and imperial governance in 19th-century Russia, with particular attention to Siberia and provincial dynamics. She holds a Ph.D. from the University of Illinois at Urbana-Champaign and a B.A. from Ohio University. Her work analyzes how Tsarist administrative frameworks fostered subnational identities through statistical bureaus, agricultural societies, and provincial newspapers. Notable contributions include *Imagining Russian Regions* (2018), which argues that autocracy’s civil society initiatives inadvertently fueled revolutionary movements. Her research has been supported by grants from the Fulbright Program, American Historical Association, and IREX. Professor Smith-Peter’s publications span journals like *Slavic Review* and *Kritika*, exploring topics from sugar beet industries to colonial Alaska. She has translated key texts into Russian and edited historical documents such as *The Great Republic Tested by the Touch of Truth*. She serves on campus committees and previously chaired Columbia University’s Seminar on Slavic History and Culture. Key Awards: Fulbright Fellowship, American Historical Association Grant, IREX Grant Grants: Fulbright-Hays Fellowship, University of Illinois Grant, CUNY Grant Her interdisciplinary approach bridges economic, cultural, and political history, emphasizing regional agency within imperial contexts. Ongoing projects explore Siberian historiography and the legacy of 19th-century provincial activism.
Yiyu Yao is a Professor in the Department of Computer Science at the University of Regina, Faculty of Science. He holds a B.Eng. from Xi'an Jiaotong University and earned both his M.Sc. and Ph.D. from the University of Regina. His office is located in College West 308.6, and he can be reached at Yiyu.Yao@uregina.ca or by phone at (306) 585-5226. Dr. Yao's research spans multiple interconnected domains in intelligent systems. His primary focus is on three-way decisions, which serves as a unifying framework for his work in granular computing, rough sets, and decision-theoretic models. He has developed significant theoretical contributions to decision-theoretic rough sets (DTRS) and probabilistic rough sets, creating bridges between uncertainty management and practical decision-making applications. His work extends to web intelligence, information retrieval systems, and multiview data analysis, where he applies his theoretical frameworks to real-world problems in data science and artificial intelligence. Analysis of Dr. Yao's recent publications reveals a strong continuing focus on three-way decision theory, with increasing applications across diverse domains. His work demonstrates evolution from foundational theoretical contributions to sophisticated applications in multi-criteria decision making, conflict analysis, and explainable AI. The research shows integration of granular computing principles with modern machine learning techniques, particularly in handling uncertainty and developing interpretable models. Recent publications indicate growing interest in the intersection of three-way decisions with fuzzy sets, shadowed sets, and cognitive approaches to data analysis. Dr. Yao has mentored numerous graduate students and has hosted many visiting scholars, primarily from Chinese institutions including Nanjing University Posts and Telecommunication, Harbin Normal University, Shaanxi Normal University, and others. He serves as Area Editor on Rough Sets for the International Journal of Approximate Reasoning and as Associate Editor for Information Sciences. He is also Associate Editor-in-Chief for the Journal of Emerging Technologies in Web Intelligence and serves on multiple editorial boards including LNCS Transactions on Rough Sets and Web Intelligence and Agent Systems. He has organized significant conferences including the International Joint Conference on Rough Sets (IJCRS 2017) and served on the Steering Committee for the International Symposium on Fuzzy and Rough Sets.
Jan Eeckhout is an ICREA Research Professor at Pompeu Fabra University (UPF) in Barcelona, specializing in macroeconomic theory, labor markets, and urban economics. His work focuses on market power dynamics, wage inequality, and technological impacts on labor and urban systems. He holds a PhD from the London School of Economics (LSE). Eeckhout has received a prestigious ERC Advanced Grant (€2.45M) for research on 'Macro Market Power and Distribution.' He authored the influential book The Profit Paradox (2021), exploring how dominant firms reshape labor markets and economies, translated into multiple languages. His research frequently appears in top journals like the Quarterly Journal of Economics and Review of Economic Studies. Research Interests: Macro-Labor Theory, Labor Markets, Urban Economics, Market Power, and Economic Inequality. Recent work examines technological origins of labor market stagnation, IT-driven urban polarization, and wealth effects on worker productivity. Advising and Grants: Supervises PhD students (e.g., Milena Djourelova, David Puig) and collaborates with institutions globally (CEMFI, EUI, Sciences Po). His team includes co-authors like Jan De Loecker and Philipp Kircher. Active in policy discussions via think tanks and media outlets like VoxEU and the NYT. Labs/Teams: Leads a diverse research group at UPF, with projects on market power, urban economics, and labor dynamics.
K. Rajibul Islam is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC) and the Department of Physics and Astronomy. He holds a joint appointment with the Perimeter Institute for Theoretical Physics and co-founded Open Quantum Design and Lightflow Optics Inc. His research focuses on quantum information processing, quantum simulation, and trapped ion systems, with applications in quantum computing and entanglement studies. Education: Ph.D. in Physics (2012, University of Maryland), M.Sc. in Physics (2007, Tata Institute of Fundamental Research), B.Sc. in Physics (2005, Jadavpur University). Postdoctoral research at Harvard University (2012–2015) and MIT (2015–2016). Research Interests : Quantum simulation of spin models, quantum computing with trapped ions, entanglement measurement, frustrated spin systems, and quantum materials. His lab, QITI (Quantum Information with Trapped Ions), develops scalable quantum simulators and open-access quantum computers like 'QuantumIon.' Awards : Fellow of the American Physical Society (2024), VAIBHAV Fellowship (2024), Excellence in Teaching Award (2024), Early Researcher Award (2019), and Distinguished PhD Dissertation Award (2012–13). Teaching : Courses include PHYS 701 (Graduate Quantum Physics), PHYS 234 (Quantum Physics I), PHYS 393 (Physical Optics), and PHYS 256 (Geometrical and Physical Optics). He emphasizes outreach via initiatives like Bigyan.org.in , a Bengali-language science platform. Lab and Collaborations : Active in developing trapped-ion quantum hardware, including ion trap designs, optical addressing systems, and holographic control methods. Collaborates on quantum algorithms, machine learning for quantum systems, and experimental quantum thermodynamics.
Dr. Hanbo Shim is an Assistant Professor in the Department of Management at The University of Texas at Arlington, College of Business. He holds a PhD in Industrial Relations and Human Resources from Rutgers University and a BA in Mathematics and Economics from the University of Illinois at Urbana-Champaign. His research and teaching focus on Human Resource Management, Organizational Behavior, and HR Analytics. PhD, Industrial Relations and Human Resources, Rutgers University (2022) MS, Industrial Relations and Human Resources, Rutgers University (2019) MA, Human Resource Management, Rutgers University (2016) BA, Mathematics and Economics, University of Illinois (2012) Dr. Shim's research explores the temporal dynamics of employee performance, compensation systems, emotional intelligence, and social networks in organizations. He uses longitudinal analysis, multilevel modeling, meta-analysis, and computer simulation to examine how individual and interpersonal factors influence organizational outcomes. His work bridges HR analytics with behavioral science. His recent publications span topics such as green HRM, pay policy dynamics, emotional intelligence, and HR analytics education. These works reflect a strong interdisciplinary approach integrating psychology, sustainability, data science, and strategic management. His research has been presented at leading conferences including the Academy of Management and European Reward Management Conference. Award highlights include: Ralph Alexander Best Dissertation Award (2024) Innovative Teaching Award, Academy of Management HR Division (2022) Best Student Convention Paper Award (2020) Best Doctoral Conference Paper Award, Samsung Economic Research Institute (2020) Dr. Shim actively advises students through capstone and honors projects and serves on PhD and graduate studies committees. He has collaborated with SL Corporation on HR analytics and developed open-source educational materials. His service includes editorial board membership for Compensation & Benefits Review and ad hoc reviewing for top journals. He is also engaged in professional development workshops and public speaking, including for the Society for Human Resource Management at UTA. His lab and research activities emphasize simulation-based methods and real-world HR analytics applications.
Valerie Viet Triem Tong is a Research Professor at the Paris Institute of Electrical and Electronic Engineering, School of Electrical and Electronic Engineering. She has established herself as a leading researcher in cybersecurity with a particular focus on information flow control systems, Android security, and malware analysis. Her work spans both theoretical foundations and practical security tools development. Her research interests center on Information Flow Control , where she has developed frameworks for monitoring and enforcing security policies at both operating system and application levels. She has made significant contributions to Android Security , creating tools for detecting malicious behavior in mobile applications and addressing privacy concerns in smartphone environments. Her work in Malware Analysis includes developing advanced techniques for tracking and visualizing malware behavior, with emphasis on evasive Windows malware and Android malware in the wild. She also investigates Peer-to-Peer Network Security , focusing on Sybil attack resistance and distributed identity management. Analysis of her publication record reveals a consistent trajectory from foundational work in information flow theory to increasingly applied security research. Her recent work shows a strong emphasis on practical security tools (DaViz, GUI-Mimic, BAGUETTE), security evaluation methodologies (Digital twin, CERBERE), and addressing contemporary challenges in malware analysis (debiasing datasets, handling obfuscated applications). A notable trend is her integration of visualization techniques with security analysis to make complex security data accessible to both experts and machine learning systems. As an advisor, she has mentored numerous researchers who have become first authors on significant publications, including Radoniaina Andriatsimandefitra, Tomás Concepcion Miranda, and Cedric Herzog. Her research has been supported by multiple grants focused on cybersecurity infrastructure, though specific grant details are not provided in the available information. Dr. Tong is actively involved with the CIDre security research group in Rennes, contributing to collaborative projects that bridge theoretical security models with practical implementation challenges. Her work on information flow monitoring has evolved from basic research to applied systems that address real-world security concerns across multiple platforms.
Susana Mourato is Professor of Environmental Economics at the Department of Geography and Environment at the London School of Economics and Political Science (LSE). She joined LSE in 2008 after ten years at Imperial College London. In 2021, she became the Vice President and Pro-Vice Chancellor (Research) at LSE. She also holds positions as Visiting Reader at Imperial College London and Honorary Senior Fellow at CSERGE (University of East Anglia). Professor Mourato is an expert in environmental economics and the application of economic valuation techniques to measure environmental change and social value. Professor Mourato's research focuses on valuing natural wealth and creating markets for ecosystem services, perceptions and preferences for low-carbon energy technologies, environmental valuation methods and applications, and the relationship between life satisfaction and the environment. Her work spans the fields of environmental economics, wellbeing economics, and behavioral environmental economics. She has conducted extensive research on ecosystem services, wildlife conservation, air and water pollution, chemicals, climate change, low carbon technologies, and cultural heritage, testing and applying economic valuation techniques to these diverse areas. Her recent publications show a strong trend toward integrating behavioral economics with traditional environmental valuation techniques. She has published extensively on the links between subjective wellbeing and environmental quality, as well as the application of economic valuation methods to inform environmental policy. Her work often involves interdisciplinary collaborations across economics, ecology, and social sciences, with significant policy impact through government advisory roles and international organizations. Member of Culture & Heritage Capital Advisory Board (UK Department for Digital, Culture, Media & Sport) Associate of the Grantham Research Institute on Climate Change and the Environment Former Academic Director of LSE Summer School Former Head of Department (2017-2020) Professor Mourato has worked on more than 45 research projects and consultancies for research councils, government, industry, charities, and international organizations. She currently leads projects for the OECD evaluating the impact of chemicals on IQ, for LSE Middle East Centre estimating preferences for climate change policies in the Gulf Region, and for water conservation in Kuwait. Her research has informed policy development in multiple countries and international contexts.
Jon M. Peha is a Full Professor in the Department of Engineering and Public Policy and the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He serves as Founder and Director of the Center for Executive Education in Technology Policy (CEE-TP) and maintains affiliations with the CyLab Security and Privacy Institute and the Information Networking Institute. His career uniquely bridges government service (as FCC Chief Technologist, White House OSTP Assistant Director, and congressional advisor), industry leadership (as CTO for three tech startups), and academic research. Education: Ph.D. in Electrical Engineering, Stanford University (1991) M.S. in Electrical Engineering, Stanford University (1986) B.S. in Electrical Engineering and Computer Science, Brown University (1984) Peha's research spans the technical and policy dimensions of information networks, with particular focus on spectrum management, broadband Internet architecture, wireless communications, cybersecurity, and communications for emergency response. His work integrates engineering principles with economic and regulatory analysis to address real-world challenges in telecommunications infrastructure. Current projects examine connected vehicle communications, spectrum sharing models, and consumer-centric broadband labeling systems that emerged from his large-scale user studies. His research publications demonstrate consistent leadership in both technical innovation and policy analysis, with recent work addressing satellite interference mitigation, V2X communications, and pandemic-era internet performance. The breadth of his scholarship reflects his unique position at the intersection of engineering practice and policy formulation. Scientific Awards: IEEE Fellow AAAS Fellow FCC Excellence in Engineering Award IEEE Communications Society TCCN Publication Award Brown Engineering Medal AAAS Featured Science and Technology Policy Fellow (40@40) Peha actively engages with policymakers through congressional testimony, FCC consultation, and White House advisory roles. His government service has directly informed his academic work on spectrum policy, network neutrality, and public safety communications. He has supervised numerous graduate students across EPP, ECE, and INI programs, with research spanning vehicular networks, spectrum sharing, and emergency communications systems. As Director of CEE-TP, he leads executive education initiatives that bridge technical expertise and policy decision-making. His work with CyLab focuses on cybersecurity and privacy challenges in broadband systems and connected vehicles. Current projects include developing cost-effective spectrum sharing models for intelligent transportation systems and analyzing the economic implications of multi-network access architectures in 5G networks.
Tracy Xiao Liu is a Professor at the Department of Economics, School of Economics and Management, Tsinghua University. Her research focuses on behavioral market design and the intersection of economics and computer science (Econ-CS), utilizing experimental methods to explore decision-making mechanisms, incentive structures, and behavioral spillovers. Her publications span journals such as Management Science , Games and Economic Behavior , and Journal of Economic Behavior & Organization . Key themes include behavioral economics, game theory, public goods, and experimental studies on market design, incentive contracts, and social preferences. Recent work examines AI-driven economic rationality (GPT models), energy policy impacts, and virtual red packet dynamics in online groups. Tracy collaborates with scholars across institutions, including her husband Baoping Liu (Peking University, harmonic analysis). Her experimental research bridges microeconomic theory with real-world applications in education, pensions, and crowdsourcing platforms.
Professor Barney Tan serves as Professor of Information Systems and Senior Deputy Dean (Impact and Partnerships) at UNSW Business School. Previously, he held the position of Head of School (Information Systems and Technology Management) and was formerly Professor of Strategic Information Systems at The University of Sydney. Professor Tan completed his PhD in Information Systems at the National University of Singapore in 2012, following a Bachelor of Computing (Honors) in Information Systems from the same institution in 2004. His research focuses on strategic information systems, AI management and implementation, digital platforms and ecosystems, fintech, and information systems for sustainable development with particular emphasis on IT trends in the Asia-Pacific region including China and ASEAN countries. As an engaged researcher, Professor Tan is deeply passionate about translational research that contributes toward sustainable development and frequently provides advisory support to organizations he has studied, including national governments through his work with the United Nations International Think Tank for Landlocked Developing Countries. His research has been published in top-tier journals including MIS Quarterly, Information Systems Research, Journal of Association of Information Systems, Information Systems Journal, and The Journal of Strategic Information Systems. Senior Editor, Information Systems Journal (2022-Present) Senior Editor, Information Technology and People (2019-Present) Associate Editor, Internet Research (2020-Present) Associate Editor, Information and Management (2016-Present) Editorial Board Member, Information Systems Research (2022-Present) Editorial Board Member, IEEE Transactions on Engineering Management (2017-Present) Professor Tan has received numerous prestigious teaching and research awards throughout his distinguished career: 22 awards in 11 years at The University of Sydney SUPRA Teacher of the Year award for 2019 and 2020 SUPRA Supervisor of the Year award for 2019, 2020 and 2021 The University of Sydney Business School Dean's Award for Teaching in 2019 Multiple Dean's Citations for Teaching across various courses and semesters Professor Tan has successfully secured multiple competitive research grants: Hong Kong University Grants Committee General Research Fund (2020-2022): 'The Impact of Social Media on Digital Guanxi Formation in the Chinese Workplace', Co-Investigator, HKD$475,617 (A$88,286) The University of Sydney Business School Industry Partnership Grant (2017): 'International Think Tank for Landlocked Developing Countries Research Development Project', Chief Investigator, A$27,238 Zhejiang Gongshang University Strategic Research Grant (2016-2019): 'Emerging Digital Commerce Platforms: Development Patterns and Usage Behavior', Principal Investigator, CNY$300,000 (A$60,535) Multiple University of Sydney Bridging Support Grants (2015-2016) focused on digital commerce and Australian-China trade Professor Tan is frequently featured in mainstream media outlets including ABC News, Business Insider, Sydney Morning Herald, The Australian, News.com.au, The Australian Financial Review, CIO, and Bloomberg Businessweek, where he provides expert commentary on technology-related topics such as cryptocurrency, digital platforms, and China's tech landscape.
Cathy Wu is an Associate Professor at MIT, with affiliations in the Laboratory for Information and Decision Systems (LIDS), Department of Civil and Environmental Engineering (CEE), and Institute for Data, Systems, and Society (IDSS). Her research group focuses on integrating machine learning with model-based optimization to solve complex problems in transportation systems and cyber-physical systems. Academic Leadership: Class of 1954 Career Development Associate Professor (MIT) Research Grants: NSF CAREER Award, Amazon Robotics, Mathworks, MIT Mobility Initiative, US DOT, Microsoft Research, Cintra, Symbotic Research Interests : Wu's work bridges AI and engineering challenges in transportation. Key areas include: Hybrid ML/Model-based Optimization (large neighborhood search, branch-and-cut) Sustainable Mobility (Project Greenwave, eco-driving) Multi-Agent Coordination (warehouse automation, cooperative driving) Cyber-Professional Systems (generalization in RL, transfer learning) Recent work demonstrates significant advances in eco-driving (11-22% emissions reduction), large-scale multi-agent path finding (1000+ agents), and foundational RL methods for traffic control. Her group has produced 15+ major publications since 2015, with notable media coverage in Science, Wired, and NewScientist. Selected Scientific Awards NSF CAREER Award (2023) Ole Madsen Mentoring Award (2025) IEEE ITSS WiE/YP Fellowship (2024) Harold L. Hazen Teaching Award (2022) Her lab has advised 12+ graduate students and postdocs, including: Vindula Jayawardana (PhD '24, now at Anthropic) Sirui Li (PhD '25, now at Microsoft Research) Yining Ma (Postdoc, active researcher) Zhongxia Yan (PhD '24, now at Anthropic)
Professor Dinusha Mendis is a leading academic in Intellectual Property and Innovation Law at Bournemouth University, where she serves as Director of the Centre for Intellectual Property Policy and Management (CIPPM). Her expertise bridges copyright law with emerging technologies like 3D printing, AI, blockchain, and the Metaverse, informed by extensive research and consultation with entities such as the European Parliament, UKIPO, and corporations like HP and Chanel. She holds a PhD from Edinburgh University and has authored seminal works on the intersection of technology and IP. BSc in Law from Aberdeen University LLM and PhD from Edinburgh University Called to the Bar of England and Wales Her research focuses on copyright challenges in immersive environments , AI-generated content regulation , and blockchain/NFTs . She led major studies for the European Commission and UKIPO , including the first peer-reviewed work on 3D printing and IP. Her 2019 co-edited book with Stanford and QUT scholars established foundational frameworks for additive manufacturing legal analysis. Recent publications highlight AI copyright disputes (2024 The Conversation ), NFT legal ambiguities (2022), and pandemic-era 3D printing (2020). Trends show increasing emphasis on decentralized IP systems and machine learning's impact on creative industries . Scientific Awards & Grants JSPS Visiting Professorship (2023) Daiwa Anglo-Japanese Foundation Grant (2024) EU Commission Research Funding (2020) AHRC Grant for 3D Jewellery Study (2017) As a PhD supervisor, she mentors researchers on AI copyright (Benjamin White), crypto-art (Bahar Dagli), and music creation law (Elizabeth Bailey). She contributes to global IP policy through the World Economic Forum's Metaverse Governance Team and EU IPR Enforcement Projects .
Eric Green is an Adjunct Assistant Professor in the Department of Civil Engineering at the University of Kentucky , affiliated with the Kentucky Transportation Center . He holds a Ph.D., M.S., and B.S. in Civil Engineering from the same institution. Ph.D., Department of Civil Engineering, University of Kentucky M.S., Department of Civil Engineering, University of Kentucky B.S., Department of Civil Engineering, University of Kentucky His research focuses on highway safety , spatial analysis (GIS) , crash modeling , and software development for traffic safety . Recent work includes text mining for secondary crash detection and GPS-based horizontal curve analysis. Publications highlight trends in crash analysis , Highway Safety Manual methodologies , and data integration for asset management . Key subfields include GIS applications, safety modeling, and automated regression techniques.
