جست‌وجوی استاد و پژوهشگر

• Computer Science
• Electrical Engineering
• Signal Processing
• +۳ مورد دیگر

Guo Li is affiliated with the Beijing Institute of Technology, School of Management and Economics. Their research spans computer vision, optimization algorithms, signal processing, and machine learning. Collaborations include work on image super-resolution, sensor networks, and energy systems. Publications are distributed across journals like Comput. Electron. Agric. , IEEE Trans. Circuits Syst. , and Entropy . Research interests focus on computational methods for image processing, algorithm design, and interdisciplinary applications in agriculture and energy. Recent work emphasizes lightweight neural network architectures, sparrow search algorithms, and thermodynamic modeling in materials science. Notable contributions include advancements in citrus fruit detection, fatigue life assessment of superalloys, and load forecasting techniques. Active in international conferences such as CVPR, ICC, and NSDI, with a strong publication record since 1998.

Tobias Brandtمشاهده پروفایل

استاد

• Digital Innovation
• Public Sector Management
• Information Systems
• +۵ مورد دیگر

Prof. Dr. Tobias Brandt serves as a Full Professor and Chair of Digital Innovation and the Public Sector at the University of Münster's School of Business and Economics. His academic journey includes roles as Assistant Professor at Rotterdam School of Management (2016-2021) and Research Assistant at the University of Freiburg (2011-2015). He co-founded Geospin GmbH in 2016 and holds memberships in VHB, INFORMS, and AIS. Research Interests: Brandt focuses on digital innovation in public sectors, sustainable urban systems, e-government, and platform ecosystems. His work bridges information systems and operational research to address challenges in mobility, energy, and public service delivery. Recent projects include developing tools for sustainable urban planning, digital platforms for elderly care, and leveraging AI for crisis management. Notable Projects: Current initiatives include the PIONEER II Master's program on public innovation, SMARD-Gov (LLMs for government decision-making), and comuneo (digital sustainability management platform). Completed projects include INNO4S (integrating sustainability in business education) and studies on pandemic-driven digitalization in public administration. Awards: RSM Teaching Award (2020), Daniel H. Wagner Prize (2020), IBM Faculty Award (2016). Grants: €5M+ secured from EU Erasmus+, DFG, and German Federal Ministry of Research. Labs/Teams: Leads the Chair of Digital Innovation & Public Sector, collaborating with ERCIS (European Research Center for Information Systems). Active in GovTech and digital sustainability initiatives.

Wantao Yuمشاهده پروفایل

استاد

• Digital Supply Chain Management
• Supply Chain Sustainability
• Lean, Agile, Resilient and Green (LARG) Supply Chain
• +۵ مورد دیگر

Wantao Yu is a Professor of Supply Chain Management at the Roehampton Business School, part of the University of Roehampton's Faculty of Business and Law. Previously, he held academic positions at the University of Kent, University of East Anglia, and Buckinghamshire New University. His expertise spans digital supply chain management, sustainability, and modern slavery prevention. He actively supervises PhD students in areas like agri-tech and LARG (Lean, Agile, Resilient, Green) supply chains. Research Interests: His work focuses on digital innovation in supply chains, sustainable practices, and ethical sourcing. Notable projects include STFC-funded initiatives in agri-food systems (UK, China, Kenya, Uganda) leveraging IoT and machine learning for sustainability and productivity. He emphasizes public-private partnerships with smallholder farmers and agribusinesses. Notable Achievements: Included in Stanford's World Top 2% Scientists (2020-2024) and recognized with multiple awards, including the Emerald/EFMD Doctoral Research Award (2010) and conference paper accolades (e.g., 2017, 2015). His pandemic-related research was featured in the WHO database. Teaching: Leads courses on Supply Chain Strategy & Processes and Digital Logistics. External roles include serving as an academic examiner at universities like Essex and Hertfordshire. Collaborations: Active in global research networks, with recent projects in Kenya, Uganda, and China. Key themes include data-driven supply chains, agri-tech, and resilience strategies for SMEs.

Agostino Capponiمشاهده پروفایل

استاد

• Systemic Risk
• Financial Technology
• Blockchain and Crypto Economics
• +۴ مورد دیگر

Agostino Capponi is a Professor of Industrial Engineering and Operations Research at Columbia University, affiliated with Columbia Engineering and the Data Science Institute (DSI). He holds academic fellowships at the Luohan Academy (Alibaba Group) and the Fintech@Cornell Center. His research focuses on systemic risk, financial technology, blockchain economics, and machine learning applications in finance. He has authored a best-selling book on machine learning in financial markets and received prestigious awards including the NSF CAREER Award and the JP Morgan AI Faculty Research Award. Education: Master's and PhD in Computer Science and Applied & Computational Mathematics from Caltech (2006-2009). Professional roles include Editor of Management Science , co-editor of Mathematics and Financial Economics , and leadership positions in the Bachelier Finance Society and INFORMS Finance Section. His research has been funded by NSF, DARPA, J.P. Morgan, Ethereum Foundation, and others. Research interests span blockchain governance, decentralized finance protocols, and systemic risk mitigation in financial networks. Notable contributions include work on liquidity risk, crypto-economic systems, and causal inference in financial modeling. Media coverage includes American Banker, Vox, and Chicago Booth Review. He holds a patent in military network tracking and served as a visiting scholar at the Federal Reserve Bank of New York.

Jihong Wangمشاهده پروفایل

استاد

• Power System Modelling and Control
• Energy Storage and Grid Integration
• Energy Efficient Actuators
• +۳ مورد دیگر

Professor Jihong Wang is a faculty member at the University of Warwick's School of Engineering, where she has held the position since January 2011. She previously served as a Professor of Control and Electrical Power at the University of Birmingham and held academic roles at the University of Liverpool from 1998 to 2007. As the Head of the Power and Control Systems Research Laboratory, her research focuses on power system modeling and control, energy storage integration, and energy-efficient actuators. Her work has led to over 100 journal publications and several industry collaborations, including a smart voltage controller and a clean pneumatic UPS. She led the EPSRC-funded IMAGES project, developing an open-source software tool for energy storage systems. Professor Wang actively contributes to energy storage initiatives, including co-leading the Supergen Energy Storage Hub and the Joint UK-India Clean Energy Centre (JUICE). Her funded projects span compressed air energy storage (CAES), grid-tied photovoltaic inverters, and net-zero engineering innovation. She advises on energy policy and has pioneered innovations in thermal storage, grid decarbonization, and renewable energy integration. Her research bridges academic rigor and practical applications, addressing critical challenges in sustainable energy systems. Her professional engagement includes roles like Deputy Director of the Supergen Energy Storage Network+ and collaborations with global institutions. Her work emphasizes interdisciplinary approaches to energy challenges, combining control systems, thermal engineering, and policy analysis. Professor Wang’s contributions have been recognized through best paper awards and leadership in major energy storage consortia.

Tarek Alskaifمشاهده پروفایل

دانشیار

• Energy Informatics
• Smart Grids
• Artificial Intelligence
• +۹ مورد دیگر

Dr. Tarek Alskaif is an Associate Professor of Energy Informatics at Wageningen University & Research, specializing in the intersection of information technology and energy systems. He leads research on smart energy systems, focusing on electricity markets, distributed energy resources, and AI-driven solutions. His work integrates modeling, optimization, and big data analytics to advance the sustainable energy transition. Education: PhD in Energy Informatics (2012–2016, Cum Laude) from Universitat Politècnica de Catalunya, Spain. Postdoc at Utrecht University’s Copernicus Institute (2016–2020). Current roles include coordinating the BSc Data Science Minor and teaching Python and Big Data courses. Research interests emphasize leveraging digitalization for energy systems, including smart grids, electric mobility, and battery storage. Notable projects include HighLO Energy Markets (EU-funded, using particle physics and AI for market transparency) and MESSM (coordinated via TKI Urban Energy). He also leads the AI ELSA Lab (NWO-funded). Editorial roles include Associate Editor for IEEE Transactions on Smart Grid and IEEE Power Engineering Letters . Member of IEEE, the Netherlands Institute for Research on ICT (4TU.NIRICT), and the Technical Program Committee for IEEE SmartGridComm and PSCC 2026. Has supervised over 50 students (MSc/BSc) and 7 PhDs. Projects address challenges like grid congestion, EV charging optimization, and decentralized energy trading. His work bridges academic research with industry collaborations, including partnerships with CERN and ACER.

• Child Development
• Self-Regulation
• Diversity Science
• +۶ مورد دیگر

Ying Zhang serves as an Assistant Professor in the Department of Psychology within Clarkson University's Lewis School of Health & Life Sciences, where her research examines developmental trajectories of cognitive, social, and emotional functioning from early childhood through emerging adulthood. Her work emphasizes contextual influences including cultural dynamics, socioeconomic conditions, and family relationships on self-regulation development. Her educational background includes: Ph.D. in Psychology from Syracuse University (2021) M.Ed. in Education from Jilin University (2012) B.Eng. in Engineering from University of Jinan (2008) Grounded in Diversity Science , Dr. Zhang investigates ecological influences on child self-regulation, particularly examining how intimate partner violence exposure, parental mental health, and socioeconomic disparities create pathways for risk and resilience. Her methodological approach integrates advanced statistical modeling with longitudinal designs, latent profile analyses, and machine learning techniques to analyze large secondary datasets, generating insights applicable to real-world interventions for vulnerable populations. Analysis of her 15 most recent publications (2023-2025) reveals three dominant research streams: (1) intricate mechanisms linking intimate partner violence to child self-regulation through parenting stress pathways, (2) socioeconomic and cultural influences on developmental outcomes using machine learning methodologies, and (3) diversity promotion in higher education contexts. Her work increasingly incorporates technology applications, including AI-based violence detection systems. Dr. Zhang actively involves undergraduate researchers in her projects, as evidenced by numerous student co-authorships, and teaches courses including Introduction to Psychology, Cultural Psychology, Diversity Science, and Prenatal/Child Development. Her office is located in Clarkson's Science Center (Box 5825) with open hours Mondays and Fridays 1-3:30pm.

Deng Xiaotieمشاهده پروفایل

استاد

• Algorithmic Game Theory
• Internet Economics
• Parallel Computing
• +۱ مورد دیگر

Xiaotie Deng is a distinguished academic and Chair Professor at Peking University (since 2018), with prior roles at Shanghai Jiao Tong University (2013–2017), the University of Liverpool (2010–2013), and City University of Hong Kong (1997–2013). His research focuses on algorithmic game theory, internet economics, and parallel computing. He holds prestigious fellowships including ACM Fellow (2008) and IEEE Fellow (2019). Deng has led significant grants, including a RMB 5M project on algorithmic game theory at Peking University (2018–2020) and NNSFC-funded research on market competitiveness and fairness (2018–2020). Education: PhD in Computer Science from Stanford University (1989), MSc from Chinese Academy of Sciences (1984), BSc from Tsinghua University (1982). Research interests span computational game theory, equilibrium analysis, and blockchain applications. Notable contributions include foundational work on Nash equilibrium complexity and mechanism design for resource allocation. He has advised numerous PhD students and serves on editorial boards of top journals like SIAM Journal on Computing and IEEE Transactions on Cloud Computing. Key awards: ACM and IEEE Fellowships, JSPS Invitation Fellowships (2005, 1996), and NSERC International Fellowship (1991). Active in conference organizing, including PC chairs for WINE 2020 and SAGT 2018. Consultancy includes work with Cryptape, Ant Financial, and Microsoft Research Asia, reflecting his industry engagement in algorithmic solutions and blockchain technologies.

Lirong Xiaمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Multi-Agent Systems
• +۹ مورد دیگر

Lirong Xia is a Professor of Computer Science at Rutgers University - New Brunswick and Deputy Director of DIMACS (Center for Discrete Mathematics and Theoretical Computer Science). He holds a Ph.D. in Computer Science from Duke University, an M.A. in Economics from Duke, and a B.E. in Computer Science and Technology from Tsinghua University. His research focuses on the intersection of artificial intelligence, machine learning, and social choice theory, addressing challenges in voting systems, fair division, privacy, and multi-agent systems. Key research areas include algorithmic fairness, computational social choice, and mechanism design. Recent work explores equitable voting rules, privacy-preserving mechanisms, and strategic behavior analysis. Notable publications include advancements in computational social choice and privacy in voting systems. Xia has been recognized with prestigious awards such as the NSF CAREER Award and IEEE’s “AI’s 10 to Watch.” Education: Ph.D. Computer Science, Duke University (2011) M.A. Economics, Duke University (2010) B.E. Computer Science and Technology, Tsinghua University (2004) Awards: NSF CAREER Award Simons-Berkeley Research Fellowship 2018 Rensselaer James M. Tien’66 Early Career Award IEEE Intelligent Systems “AI’s 10 to Watch” Advising: Supervised over 30 students, including PhDs and master’s candidates in AI, algorithms, and social choice theory.

Manxi Wuمشاهده پروفایل

استادیار

• Societal Networks
• Game Theory
• Network Optimization
• +۴ مورد دیگر

Manxi Wu is an Assistant Professor in Cornell University's School of Operations Research and Information Engineering, specializing in societal networks and game-theoretic approaches to system design. Her research develops computational models for strategic learning and incentive mechanisms in socio-technical systems, with applications to transportation networks and digital platforms. Education: B.S. Applied Mathematics, Peking University (2015) M.S. Transportation, Massachusetts Institute of Technology (2017) Ph.D. Social and Engineering Systems, Massachusetts Institute of Technology (2021) Her research integrates game theory, optimization, and machine learning to address challenges in autonomous services, traffic management, and decentralized decision-making. Current investigations focus on adaptive incentive structures, spatial resource allocation, and equilibrium analysis in complex networked environments. Publication analysis reveals consistent emphasis on game-theoretic frameworks applied to urban mobility systems, with recent work exploring multi-agent reinforcement learning, congestion pricing equity, and electric fleet management. Methodological innovations include novel convergence proofs for decentralized algorithms and computational approaches to fairness constraints. Awards and Honors: Hammer Fellowship UTC Milton Pikarsky Memorial Award Siebel Scholarship EECS Rising Star recognition No information is currently available regarding student advising, research grants, or laboratory affiliations.

• Natural and Artificial Lighting
• Solar Energy (Passive and Active)
• Building Technology
• +۳ مورد دیگر

Jean-Louis Scartezzini is an Honorary Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Solar Energy and Building Physics Laboratory (LESO-PB). His research focuses on natural/artificial lighting, solar energy systems, and building technology, with a strong emphasis on energy efficiency and sustainability. Director of LESO-PB since 1994 Founded and led several institutes, including the Institute for Infrastructure, Resources, and Environment (2002–2009) Doctorat in Physics from EPFL (1986) Extensive international collaborations, including visiting roles at NUS (2009) and LBNL/UCLA (1988) Research interests include: - Daylighting and lighting control systems - Passive/active solar technologies - Urban microclimate and energy systems - Stochastic simulation and predictive control Recent work addresses climate change impacts on energy systems, urban sustainability, and machine learning applications in energy optimization. Key publications span lighting health impacts, renewable integration, and microclimate modeling Awards include the European Solar Prize (2001/2002) and Walsh-Weston Bronze Medal (1998) Mentored over 20 PhD students, many leading in academia and industry (e.g., Marilyne Andersen at EPFL, Flavio Foradini at E4Tech).

Alex Kaleمشاهده پروفایل

استادیار

• Human Computer Interaction
• Data Visualization
• Data Science
• +۴ مورد دیگر

Alex Kale is an Assistant Professor of Computer Science at the University of Chicago and a core member of the Data Science Institute. His research focuses on data visualization and human-computer interaction, emphasizing tools that explicitly represent users' cognitive processes during data analysis. He leads the Data Cognition Lab, exploring software for uncertainty visualization, causal inference, and decision-making support. Kale holds a PhD in Information Science from the University of Washington (2022), an MSc from UW (2020), and a BSc in Psychology with minors in Music and Philosophy (2015). Affiliations: University of Chicago, Data Science Institute, Data Cognition Lab Education: PhD, UW (2022); MSc, UW (2020); BSc, UW (2015) Research interests include human-computer interaction, statistical reasoning interfaces, and systems for managing large-scale data. He has developed tools like MetaExplorer for meta-analysis and EVM for exploratory visual modeling. Key awards include the Best Paper Honorable Mention at CHI 2023 and VIS 2021, and the Best Paper Award at VIS 2020. His work bridges visualization design, decision theory, and cognitive science, with applications in participatory budgeting, causal inference, and reproducible research. Courses taught include Visualization for Data Science and Statistical Rethinking.

Ed Hopkinsمشاهده پروفایل

استاد

• Game Theory
• Microeconomic Theory
• Behavioral Economics
• +۶ مورد دیگر

Ed Hopkins is a Professor of Economics at King's College London and the Interim Head of the Economics Department within the King’s Business School. He holds a PhD from the European University Institute in Florence, Italy, and has held positions at the University of Edinburgh and as a visiting scholar at institutions including the California Institute of Technology and the University of British Columbia. His research focuses on game theory, behavioral economics, and social economics, with particular emphasis on topics such as tournament models, inequality, learning dynamics, and experimental economics. Key areas of interest include status concerns, marriage matching, and the implications of non-standard preferences in strategic interactions. Ed has contributed extensively to experimental economics, testing theoretical predictions in laboratory settings. He is actively involved in PhD supervision, accepting students for doctoral research. His work spans theoretical and empirical analyses, with notable contributions to understanding cyclical behavior in strategic situations, the role of information in decision-making, and the interplay between economic inequality and risk-taking.

Helen Luمشاهده پروفایل

دانشیار

• Applications of AI in Accounting and Finance
• Valuation
• Return Predictability
• +۳ مورد دیگر

Helen Lu is an Associate Professor of Accounting and AI at Vlerick Business School and a Senior Lecturer at the University of Auckland (FinTech Lead for the Master's in Business Analytics). She holds a PhD in Finance from Massey University, an MBA from London Business School, a Master's in Economics (Macroeconomics) from Peking University, and a Bachelor's in Computer Science Engineering from Northern Jiaotong University. Her research focuses on integrating AI into accounting and finance, including valuation, return predictability, ESG disclosure, executive succession, and FinTech disruptions. Before academia, Lu worked in investment banking at Credit Suisse and Deutsche Bank, specializing in capital raising and cross-border M&A in Asia-Pacific. Her work bridges academic research and industry practice, particularly in leveraging AI to solve complex financial and accounting challenges. She has published in top journals like the Journal of Accounting Research , Journal of Banking and Finance , and Journal of International Money and Finance . Her recent publications emphasize AI-driven valuation methods, ESG disclosure analysis, and the interplay between executive transitions and financial reporting. Her articles often highlight the application of machine learning to traditional finance problems, such as tail risk assessment and anomaly strategy correlations. Lu’s expertise spans multiple domains, with a focus on transforming data-driven technologies into actionable insights for financial decision-making. She actively contributes to academic discourse on sustainability metrics, particularly green asset valuation and corporate governance during crises.

Guangqu Zhengمشاهده پروفایل

استادیار

• Probability Theory
• Stochastic Analysis
• Stochastic Partial Differential Equations (SPDEs)
• +۶ مورد دیگر

Guangqu Zheng is an Assistant Professor in the Department of Mathematics and Statistics at Boston University. He holds a BA from Wuhan University, a Master's from Université Paris-Saclay, and a Ph.D. from the University of Luxembourg. Prior to Boston University, he was a Lecturer at the University of Liverpool and conducted postdoctoral research at the University of Melbourne and the University of Kansas. Education: Ph.D. in Mathematics, University of Luxembourg (2018) Master in Probability, Université Paris-Orsay (2014) BA in Economics and Management, Wuhan University (2011) Research Interests: His work focuses on probability theory, stochastic analysis, and SPDEs. Key areas include Malliavin calculus, Stein’s method, limit theorems, and applications to stochastic partial differential equations. Recent projects involve hyperbolic Anderson models, Lévy noise-driven systems, and spatial ergodicity. Publications: His recent articles explore central limit theorems for SPDEs, hyperbolic models, and applications of Stein’s method. These contributions highlight advancements in stochastic processes and their interdisciplinary applications. Teaching & Advising: At BU, he teaches advanced courses in stochastic analysis and advises students in probability and statistics. Expectations for students include proficiency in real analysis and probability theory.