جست‌وجوی استاد و پژوهشگر

• Investments
• Behavioral Finance
• Market Microstructure

T. Clifton Green serves as the John W. McIntyre Professor of Finance at Goizueta Business School, Emory University, where he has been a faculty member since 1999. He teaches Corporate Finance in the BBA program, Behavioral Finance in the PhD program, and has previously instructed Security Analysis and Portfolio Management for MBA students. His educational background includes: PhD in Finance from New York University MA in Economics from the University of Virginia BS in Economics from Texas A&M University Green's research focuses on Investments, Behavioral Finance, and Market Microstructure, examining how investors process information and how trading mechanisms impact market efficiency. His work has been featured in The Wall Street Journal, The New York Times, Financial Times, and CNBC television, demonstrating real-world relevance of his academic contributions. Recent publications (2022-2025) reveal expanding research frontiers in retail trading behavior, AI applications in finance, and alternative data utilization. His studies leverage unique market events and large datasets to investigate anomalies in investor decision-making and market dynamics, maintaining continuity with his foundational work on bond markets and macroeconomic news impacts. Professor Green maintains active research collaborations across finance and interdisciplinary domains, with multiple 2025 working papers under review at top journals including the Review of Financial Studies and Journal of Financial and Quantitative Analysis.

Yi Zhuمشاهده پروفایل

استاد

• Industrial Organization
• Quantitative Marketing
• Advertising
• +۷ مورد دیگر

Yi Zhu is a Professor of Marketing and holder of the Margaret J. Holden and Dorothy A. Werlich Endowed Professor at the Carlson School of Management, University of Minnesota . His work bridges Industrial Organization , Quantitative Marketing , and Chinese Economy with a focus on digital advertising, platform economics, and consumer search behavior. Education PhD in Business Administration, University of Southern California (2013) MA in Economics, University of British Columbia (2004) MA in Management, Shanghai Academy of Social Sciences (2002) BE in Industry Engineering, Shanghai University of Electric Power (1998) His research applies Industrial Organization to Marketing , examining online auctions , advertising mechanisms , media slant , and Chinese economic dynamics . Recently, he has explored two-sided platforms and surge pricing effects on consumer complaints. Publications span Marketing Science , Management Science , and Journal of Marketing Research , with work highlighted in Harvard Business Review and Forbes . His advertising research includes auction design, TV-to-online search interactions, and budget-constrained advertiser behavior. Scientific Awards Winner of John D.C. Little Award (2015) Winner of Don Morrison Long Term Impact Award (2023) 3M Nontenured Faculty Grant (2013-2016) Marketing Science Institute (MSI) Scholar (2022, 2023) Holds the Carlson School Outstanding Teaching Award (2022) and serves as Associate Editor for Marketing Science . Teaching includes Marketing Analytics for MBAs and Marketing Strategy for undergraduates, with consistently high instructor ratings. Referees for top journals like Management Science and Information Systems Research .

Niccolò Galliمشاهده پروفایل

عضو هیئت علمی

• Competition law
• Antitrust Law
• Intellectual property (IP)
• +۷ مورد دیگر

Niccolò Galli is a Research Associate at the Robert Schuman Centre for Advanced Studies, European University Institute, and Contract Professor of Intellectual Property and Competition Law at the University of Florence. His work bridges law, innovation policy, and digital regulation, with a focus on EU competition law and intellectual property rights in digital markets. European University Institute, Research Associate, Robert Schuman Centre for Advanced Studies University of Florence, Contract Professor, IP and Competition Law His research interests lie at the intersection of innovation, antitrust, and intellectual property law, particularly in the context of digital transformations and ICT sector regulation. He employs empirical legal methods to analyze competition dynamics in multi-sided platforms, algorithmic collusion, and patent aggregation. The most recent publications reflect a strong trend in digital competition law, focusing on market definition for digital platforms, algorithmic collusion, and judicial enforcement of EU competition law. These works combine doctrinal analysis with interdisciplinary insights from economics and data science. His scientific recognition includes: 2024 Jacques Lassier Prize (International League of Competition Law) 2024 Licensing Executive Society - Italian Chapter Award for best IP research 2016 Elena Messina Dissertation Prize Galli has advised and collaborated on research projects related to digital markets and competition law, including the ENTraNCE for Judges series and studies on multi-sided platforms. While no formal grants are listed, his Marie Skłodowska-Curie fellowship and PhD funding indicate substantial research support. He has not supervised any students listed in the text but contributes to academic discourse through collaborative research and policy-relevant outputs. He is part of the research cluster on Digital transformations and society and the Innovation and intellectual property in the Digital Age working group at the EUI, contributing to interdisciplinary dialogue on the future of digital regulation in Europe.

Francisco Castroمشاهده پروفایل

استادیار

• Auctions
• Market Design
• Online Display Advertising
• +۳ مورد دیگر

Francisco Castro is an Assistant Professor at the UCLA Anderson School of Management since 2020. His research bridges operations management and market design , focusing on spatial and incentive dynamics in digital marketplaces. Prior to UCLA, he served as a Postdoctoral Research Scientist at Uber , where he developed models for ride-hailing platforms and supply chain resilience during crises. Ph.D., Decision, Risk and Operations (2020, Columbia Business School) M.S., Mathematical Engineering (2014, University of Chile) B.S., Engineering Sciences (2013, University of Chile) Castro’s research explores optimal pricing policies and incentive-compatible contracts in platforms like Uber. His work on surge pricing frameworks (Management Science, 2021) and spatial capacity planning (Operations Research, 2021) has implications for ride-hailing, delivery logistics, and high-dimensional market design challenges. Recent projects address autonomous vehicle integration and spatial inequality risks in platform economies. His publications span journals like Operations Research , Games and Economic Behavior , and Management Science , with working papers examining matching queues , two-sided marketplace dynamics , and AI-driven market design . Castro emphasizes translating these insights into MBA curriculum , preparing students for post-pandemic economic shifts through creative problem-solving and data-driven decision frameworks .

Meryem Schalckمشاهده پروفایل

استادیار

• Data Science
• Artificial Intelligence
• Insurance Sector
• +۳ مورد دیگر

Meryem Schalck is an Assistant Professor of Data Science at IPAG Business School in Nice, France. She earned her PhD in Economic Sciences from the University of Orléans (2022) and has over 15 years of professional experience in the insurance sector as a Data Scientist. Her research focuses on applying AI and machine learning techniques to financial fraud detection, survival analysis, and econometric models in insurance. Research and Publications: Her recent work includes developing fraud scores for automobile insurance using cross-data analysis and predicting SME failures in France with machine learning methods, published in journals like Research in International Business and Finance and Applied Economics . Teaching Expertise: She teaches courses on AI, digital technologies, and statistical analysis for business management across IPAG's PGE, BBA, and MSc programs. Her pedagogical interests include NO CODE tools and business games. Professional Background: Prior roles include Senior Manager at Addactis (pricing software expertise), consultant at Fraeris, and actuarial roles at GI Analytics (Aviva) and Tricast, specializing in predictive modeling and SAS-based statistical tools.

Kwame Porter Robinsonمشاهده پروفایل

استادیار

• Community-Based Economies
• Digital Sustainability
• Generative Justice
• +۵ مورد دیگر

Kwame Porter Robinson serves as Assistant Professor of Technology, Information Systems and Analytics at Wayne State University, where he develops community-based economic systems through co-designed AI and automation. His work bridges academic research with practical applications in digital sustainability and generative justice, informed by prior experience as a Department of Defense data scientist and NGO consultant. His educational background spans technical and creative disciplines: Ph.D. in Information, University of Michigan (2024) M.S. in Computer Science, University of Maryland (2012) B.S. in Electrical Engineering (honors), New Mexico State University (2008) B.F.A. in Graphic Design (magna cum laude), Boston University (2002) Research focuses on decolonial computing and community economies , examining how human-AI collaboration can create unalienated labor systems in artisanal contexts. His methodology emphasizes bottom-up technology co-design with communities, particularly evident in Detroit-based artisan studies and blockchain implementations for economic empowerment. Publications since 2019 reveal accelerating focus on computational reparations and generative justice, with recent work exploring fractal scaling in AI governance and worker-owned AI ecosystems. Key themes include decolonial transitions, circular value flow, and environmental sustainability in crafting economies. Scientific recognition includes: Rackham Merit Fellowship (2019-2024) with multiple research grants AWS Cloud Credits for Research (2019) Best Student Talk award for ethical AI (2023) National Intelligence Meritorious Unit Citation (2012) Teaching includes Business Information Systems and Blockchain & CyberSecurity courses, reflecting his industry-academia synthesis. While specific grant details beyond Rackham awards aren't provided, his DoD background and AWS credits indicate strong industry partnerships. Collaborative work with scholars like Ron Eglash demonstrates interdisciplinary team engagement in justice-oriented computing initiatives.

Margarida Lima Regoمشاهده پروفایل

استاد

• Private Law
• Contract Law
• Insurance Law
• +۹ مورد دیگر

Margarida Lima Rego is a Full Professor and Director at the NOVA School of Law , Universidade Nova de Lisboa, where she has taught since 2005. She is the scientific coordinator of the Doctorate in Law and previously co-founded and coordinated the Master’s in Law and Financial Markets (2015–2022). Her roles include teaching Law of Obligations , Hard Cases , and a Jean Monnet Module on EU Insurance Law, alongside leading Private Law seminars. PhD in Private Law, Universidade Nova de Lisboa (2009) MPhil in Contract Law, University of Oxford (2001) MJur in European and Comparative Law, University of Oxford (2000) Degree in Law, University of Lisbon (1999) Her research focuses on Private Law , with emphasis on Contract Law , Insurance Law , and intersections with Human Rights , Gender Equality , and Data-Driven Law . She explores legal theory, judicial decision-making under uncertainty, and technological innovation in financial markets. Her publications span topics like third-party contracts, statistical discrimination in insurance, and compensatory principles. At CEDIS, NOVA School of Law’s R&D unit, she founded the NOVA Knowledge Centre for Data-Driven Law , integrating empirical analysis into legal scholarship. She contributes to EU insurance law challenges in the SDG era and addresses modernization in financial markets through a legal lens. Her work bridges doctrinal rigor with interdisciplinary methodologies.

• Cybersecurity
• Game Theory
• Quantum Cryptography
• +۵ مورد دیگر

Stefan Rass is a Professor at the Institute of Networks and Security within the Faculty of Engineering & Natural Sciences at Johannes Kepler University Linz (JKU), where he leads the LIT Secure and Correct Systems Lab. As Principal Investigator for FFG-funded projects including reSilienz (digital supply chain resilience, 2023–2025) and ITPUK (AI signature verification, 2022–2024), he bridges theoretical game theory with practical cybersecurity solutions for critical infrastructures and robotics systems. His research spans game-theoretic security models (patrolling games, defense-in-depth strategies), quantum cryptography (QKD network architectures), and cyber deception frameworks like Honeyquest for measuring honeypot effectiveness. Recent work addresses robotics security benchmarking (RobotPerf), cryptographic instruction chaining for control flow protection, and risk assessment methodologies for interdependent infrastructures. His mathematical decision-making approach integrates bounded rationality and stochastic modeling to solve real-world security challenges. Professor Rass actively shapes the field through program committee roles (ARES 2023), peer reviews, and invited talks on security transparency. His current projects focus on cost-benefit-aware monitoring for cyber-physical systems and quantum key distribution standardization, reflecting Austria’s strategic priorities in digital resilience. The LIT Secure and Correct Systems Lab under his direction develops foundational theories while deploying tools for industrial applications, particularly in critical infrastructure protection and secure robotics workflows.

• Data science
• Machine learning
• Artificial intelligence
• +۱۰ مورد دیگر

Dr. Xiaobai (Bob) Li is a Professor in the Department of Operations and Information Systems at the Manning School of Business, University of Massachusetts Lowell. His work bridges data science, machine learning, and business analytics with specialized focus on data privacy and information economics. Ph.D. in Management Science, University of South Carolina MBA, University of New Hampshire BS in Civil Engineering, Chongqing University Research Interests span data science, machine learning, business analytics, and data privacy. His work explores Privacy-preserving analytics Healthcare data anonymization Information economics Optimization techniques Big Data applications Text analytics with particular emphasis on balancing data utility and privacy protection. Scientific Awards include: Manning Research Excellence Award (2023) Best Associate Editor Award (2021) Best Paper Awards at NEAIS, WITS, and ICIS Teaching Excellence Awards Grants from NIH and NSF supported his work on Consumer Electronic Privacy Protection and New Technology to Preserve Patient Privacy . He has served as Associate Editor for journals like Information Systems Research and Decision Support Systems .

• Venture Capital
• New Venture Growth
• Gender Equality
• +۴ مورد دیگر

Manuel Hess, a German national, serves as an Associate Professor in the Department of Accounting, Law & Finance. His academic work focuses on Venture Capital, New Venture Growth, Gender Equality, Entrepreneurship, Corporate Governance, New Venture Boards, and Social Networks. Hess's research provides critical insights into startup funding dynamics, board governance structures, and gender-based disparities in entrepreneurial success. Hess investigates venture capital decision-making processes with emphasis on corporate strategic search, technology sourcing ambidexterity, and gender bias in investor evaluations. His work reveals how physical appearance affects women entrepreneurs' funding outcomes and how emotional dynamics undermine gender equality in boardrooms. He also develops practical frameworks like the Startup Navigator to guide entrepreneurs through scaling challenges and governance complexities. Analysis of Hess's 2020-2025 publications shows a cohesive research trajectory centered on venture capital-performance linkages, gender dynamics in entrepreneurship, and startup governance evolution. Key contributions include identifying performance spillovers from core-focused corporate venture capital, documenting attractiveness biases in funding decisions, and exposing emotional barriers to boardroom equality. His recent work increasingly integrates practical tool development with theoretical insights for entrepreneurial ecosystems.

• Competition Economics
• EU Competition Law
• Algorithmic Collusion
• +۵ مورد دیگر

Dr. Timo Klein serves as an Assistant Professor in Competition Economics at Utrecht University's School of Law within the Department of International and European Law. He maintains this academic position while working as a senior economic consultant for Oxera Consulting LLP. Dr. Klein teaches Advanced EU Competition Law and Economics courses and conducts research at the intersection of economics and legal frameworks, specializing in contemporary competition policy challenges. Dr. Klein earned his BSc in Economics and Business (2013, University of Amsterdam), MSc in Political Economy of Europe (2014, London School of Economics), and MPhil in Economics (2016, Tinbergen Institute). He completed his PhD at the University of Amsterdam (2016-2020), during which he also worked at the Chief Economist Team at DG Competition, European Commission. His research focuses on economic dimensions of competition law with particular emphasis on algorithmic collusion, pricing algorithms, and digital markets regulation. He examines how emerging technologies challenge traditional competition policy frameworks through theoretical, empirical, and computational approaches. His work spans sports economics, dark patterns in consumer protection, merger control theories, and abuse of dominance cases, often analyzing European Court of Justice rulings and their economic implications. Dr. Klein's publication record demonstrates consistent engagement with cutting-edge competition policy issues, bridging theoretical economic models with practical legal applications. His research frequently appears in leading competition law journals, addressing topics from autonomous algorithmic collusion to ecosystem theories of harm in digital markets. While specific advising details aren't documented, Dr. Klein's academic position suggests involvement in student supervision. His dual role as academic and consultant indicates practical application of research to inform policy development and business practices in competition economics.

Soulaymane Kachaniمشاهده پروفایل

استاد

• Financial Engineering
• Risk Management
• Dynamic Pricing
• +۸ مورد دیگر

Soulaymane Kachani is a Professor and Senior Vice Provost at Columbia University, where he oversees teaching, learning, and innovation strategies. He is affiliated with the Columbia Data Science Institute (Financial and Business Analytics Center, Foundations of Data Science Center), Columbia Center for Financial Engineering, and Computational Optimization Research Center. Education: PhD and MSc in Operations Research from MIT, Diplôme d'Ingénieur in Applied Mathematics from École Centrale Paris. Research: Focuses on financial engineering, dynamic pricing, logistics, algorithmic trading, and transportation analysis, integrating machine learning and data science methodologies. Awards: Recipient of multiple teaching and service awards, including the Egleston Distinguished Service Award (2012) and Diversity Award (2010). Leadership: Spearheaded the establishment of the Center for Teaching and Learning (2015), driving online education initiatives and HyFlex teaching during the pandemic. His work bridges academic innovation with corporate consulting, particularly in supply chain management and quantitative finance.

Hai Zhangمشاهده پروفایل

مدرس ارشد

• Hedge Funds
• Financial Innovation
• Risk Management
• +۶ مورد دیگر

Hai Zhang is a Senior Lecturer in Finance at the Strathclyde Business School, University of Strathclyde, where he joined in March 2017 as a Strathclyde Chancellor's Fellow. His research focuses on financing innovation in incomplete financial markets, particularly in alleviating severe financing constraints due to asymmetric information. Education: PhD in The Financing Innovation in Entrepreneurship and Hedge Funds, Adam Smith Business School, University of Glasgow (2013-2016), awarded February 28, 2017. Research Interests: Dr. Zhang specializes in Hedge Funds , Financial Innovation , and Real Options with applications in Asset Pricing and SME Financing . His work bridges theoretical models with practical market mechanisms to address information asymmetry in capital allocation. Recent Research Trends: His 2024-2025 publications analyze SME financing under market frictions and convertible bond dynamics, revealing critical links between capital structure decisions and debt overhang in volatile markets. These studies advance corporate finance theory while offering actionable frameworks for financial engineering. Scientific Awards: Adam Smith Business School Prize for PhD excellence 2017 (awarded February 1, 2018) Outstanding reviewer for International Review of Economics and Finance (January 2018) Advising and Grants: Dr. Zhang supervises PhD students in hedge funds innovation and FinTech, with three students completed to date. His grant portfolio includes ESRC-funded doctoral research (2013-2016) and the current £150k project "Research on investment and financing of small and medium-sized enterprises based on enterprise asset securitization" (2021-2024) as Co-investigator. Professional Engagement: He serves as regular referee for 7 finance journals including Journal of Business Venturing and Quantitative Finance, and presented at the 2024 EFMA annual conference on algorithmic trading applications.

• Time Series Analysis
• Energy Analytics
• Statistical Clustering
• +۳ مورد دیگر

Dr. Andrés Modesto Alonso is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid, affiliated with the Energy Analytics research group and Flores de Lemus Institute. His work spans computer science, economics, and statistics through advanced time series analysis and energy forecasting methodologies. Primary affiliation: Department of Statistics, UC3M Research groups: Energy Analytics, Flores de Lemus Institute His research focuses on time series analysis , energy forecasting , and statistical clustering with applications in electricity markets, smart grids, and environmental data. Recent publications emphasize deep learning models for energy prediction, dynamic factor models, and market-based distance metrics. Scientific output trends show 15 recent articles (2018-2024) covering topics like: Electricity market price forecasting Smart grid optimization through clustering Adaptive control charts for industrial processes Precision matrix estimation in high-dimensional statistics Extreme value analysis for environmental monitoring Dr. Alonso has supervised multiple theses on time series modeling and classification techniques, while collaborating on grants related to stochastic optimization and responsible AI applications in economic forecasting.

Najmaddin Akhundovمشاهده پروفایل

استادیار

• Integer Programming
• Algorithm Development
• Simulation-based Optimization
• +۵ مورد دیگر

Najmaddin Akhundov is an Assistant Professor in the Decision Sciences and Marketing Department at the Robert B. Willumstad School of Business, Adelphi University. His expertise lies in operations research, with a focus on integer programming, stochastic optimization, and simulation-based methods applied to scheduling, logistics, energy systems, and risk management. Education: Ph.D., Industrial and Systems Engineering, University of Tennessee (2022) M.S., Systems Design Engineering, University of Waterloo (2015) B.S., Industrial Engineering, Baku Engineering University (2011) Research Interests: Dr. Akhundov’s research spans both methodological and applied domains. Methodologically, he advances integer programming , algorithmic development , simulation-based optimization , and stochastic programming . Application-wise, he tackles complex scheduling problems (staff, maintenance, power generators, production), reverse and last-mile logistics, evacuation planning, sustainable port management, and risk-informed maintenance planning. Recent publications (2019-2024) reveal a consistent trajectory toward integrating advanced optimization techniques with real-world operational challenges. Studies range from exploiting symmetry in job sequencing to configuring last-mile distribution networks, pricing risk in energy markets, and optimizing surveillance strategies against invasive species. Collectively, these works highlight a commitment to bridging theory and practice in operations research. Awards & Honors: INFORMS ENRE Best Publication Award in Natural Resources (2022) Harvey J. Greenberg Research Award – Honorable Mention, INFORMS Computing Society (2022) Graduate Fellowship Award, University of Tennessee (2018-2022) Best Graduate Presentation, Dana Knox Student Research Showcase (2018) Study Abroad Fellowship, Ministry of Education of Azerbaijan (2013-2015) Merit-Based Scholarships from Azercell Telecom and Baku Engineering University Teaching & Mentoring: At Adelphi, Dr. Akhundov teaches courses such as Management of Production/Operations and Statistical Methods, having previously taught Applied Operations Research, Optimization Techniques, and Mathematical Programming with MATLAB. While no specific advisees are listed in the provided text, his active research program and course offerings indicate ongoing engagement with both undergraduate and graduate students. Laboratories & Teams: While no dedicated laboratory is explicitly mentioned, his collaborative work with researchers from the University of Tennessee, University of Waterloo, and multiple international partners suggests participation in interdisciplinary research teams focused on optimization and logistics.