Prof. Dr. Gülşen Eryiğit is a Professor at Istanbul Technical University within the Faculty of Computer and Informatics , Department of Artificial Intelligence and Data Engineering . She founded and directs the ITU Natural Language Processing Group , Turkey's leading team in Turkish-language NLP, and serves as Senior Action Editor for ACL RR , Director of ITU TÖMER (Turkish Language Teaching Center), and Co-Chair of the EU UniDive Cost Action WG3. Education: PhD in Computer Engineering from ITU (2007), MSc and BSc from ITU and Marmara University Research: Focuses on Natural Language Processing for Turkish, including dependency parsing , coreference resolution , multiword expressions , and language education technology Her recent work involves multilingual transfer learning , LLM applications for Turkish text simplification, and gamification for morphology education. She has received prestigious awards like the Siemens Excellence Award and TÜBİTAK's Above Threshold Award . Her research has produced 65+ publications and 29+ projects funded by EU, TÜBİTAK, and industry partners. Scientific Awards: Siemens Excellence Award (2007) Above Threshold Award (TÜBİTAK, 2015) Certificate of Appreciation (EU 7th Framework, 2012) Thank You Plaque (ITU, 2017) The ITU NLP Group under her leadership has developed Turkey's first licensed NLP software exported internationally. She collaborates with European institutions through COST actions and participates in ACL, CoNLL, and LREC conferences. Her lab focuses on language technology for Turkish , including sign language processing and social media normalization.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۶۱-۷۵ از ۲۵٬۰۳۲ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
- Financial Economics
- Asset Pricing
- Tax Policy
- +۳ مورد دیگر
Professor Huibing Zhang is a Professor of Management at the Naveen Jindal School of Management, University of Texas at Dallas. He holds a Ph.D. in Economics from Duke University (1994) and a B.S. from Shanghai Jiao Tong University, China (1984). Prior to his current position, he served as Associate Professor at the University of North Carolina at Chapel Hill (2000–2005) and Assistant Professor at Carnegie Mellon University (1994–2000). Education: Ph.D. in Economics, Duke University, 1994 B.S., Shanghai Jiao Tong University, China, 1984 His research focuses on financial economics, tax policy, and asset pricing. Key areas include the impact of capital gains taxes on asset prices, behavioral finance, and optimal portfolio strategies. He explores topics such as model uncertainty in financial markets, external habits affecting stock returns, and optimal consumption decisions under borrowing constraints. His work integrates theoretical frameworks with practical applications in taxation and investment planning. Awards and Honors: Fellow, TIAA-CREF Institute TIAA-CREF Paul A. Samuelson Award (2004) for outstanding work on optimal asset location and allocation Barclays Global Investors/Michael Brennan Runner-Up Award (2002) for research on optimal consumption and investment with capital gains taxes Undergraduate Economics Teaching Award, Carnegie Mellon University (1998) BP America Research Chair, Carnegie Mellon University (1995–1996) Grants and Contracts: Taxes, Estate Planning and Financial Theory: New Insights and Perspectives (Q-Group, 2002; TIAA-CREF, 2002) Diversification and Capital Gains Taxes with Multiple Risky Assets (TIAA-CREF, 2001) Optimal Asset Location and Allocation with Taxable and Tax-Deferred Investing (TIAA-CREF, 2000) Optimal Portfolio Choice and Consumption with Capital Gains Taxes (TIAA-CREF, 1999) Carnegie Mellon Faculty Development Fund (1998–1999)
Andrea Modena is a Lecturer at Ca' Foscari University of Venice and a postdoc researcher at the University of Mannheim , Department of Economics. He is affiliated with the Bonn-Mannheim Center for Collaborative Research (CRC TR 224, Group C03) and the Leibniz Institute for Financial Research SAFE . His research bridges macroeconomic theory and financial economics, focusing on macro-finance dynamics and financial intermediation efficiency. Modena’s scholarly work explores the interplay between financial sectors and macroeconomic stability. His publications analyze business cycle fluctuations, risk pooling mechanisms, and leverage dynamics in financial intermediaries. While no formal awards are listed, his active participation in prestigious research groups (e.g., with Pietro Dindo and Loriana Pelizzon) underscores his contributions to economic theory. He holds a PhD in Economics from Ca' Foscari University of Venice (2020) and maintains dual academic roles, balancing research at Mannheim with teaching and affiliations at Ca' Foscari and Bonn. His expertise spans modeling macro-financial linkages, policy implications for financial sectors, and quantitative economic dynamics.
Refet S. Gürkaynak is a Professor of Economics at Bilkent University and a Research Fellow at the Center for Economic Policy Research (CEPR), where he directs the Monetary Economics and Fluctuations Program. He holds a BA in Economics from Bilkent University and a PhD in Economics from Princeton University. His research focuses on monetary economics, financial markets, and international economics, particularly on extracting monetary policy insights from asset prices. His work has appeared in top journals like the Journal of Monetary Economics , Review of Economics and Statistics , and American Economic Review . Research Interests Monetary Policy Transmission Financial Market Reactions Inflation Dynamics ECB Policy Communication Post-Crisis Economic Modeling Scientific Awards & Grants Central Bank of Turkey Award European Central Bank Award Turkish Academy of Sciences Award ERC Grant Consulting & Affiliations Consultant to multiple central banks Director, Monetary Economics and Fluctuations Program at CEPR Former Economist, Federal Reserve Board's Monetary Affairs Division
- Asset Pricing
- Econometrics
- Household Finance
- +۱ مورد دیگر
Nikolai Roussanov is the Moise Y. Safra Associate Professor of Finance at the Wharton School, University of Pennsylvania, and a Faculty Research Fellow at the National Bureau of Economic Research. His research spans asset pricing, econometrics, household finance, and macroeconomics, with a focus on market dynamics and behavioral economic factors. His research interests include: Asset pricing anomalies and risk factor modeling Household financial decision-making under uncertainty Macroeconomic impacts on commodity and currency markets Behavioral finance and mental accounting mechanisms Recent publications analyze inflation risks across asset classes, corporate bond valuation, behavioral retirement strategies, and the role of leisure economics in declining work hours. His work frequently integrates empirical finance and econometric methodologies. Scientific contributions include: Faculty Research Fellow, National Bureau of Economic Research His scholarship bridges technical financial modeling with real-world economic phenomena, covering topics like oil price shocks, mortgage liquidity, and systemic market failures.
Zhi Daمشاهده پروفایل
استاد
Zhi Da is the Howard J. and Geraldine F. Korth Chair in Finance and Professor of Finance at the University of Notre Dame , Mendoza College of Business, Department of Finance. He completed his Ph.D. in Finance at Northwestern University’s Kellogg School of Management (2006), preceded by an M.Sc. in Financial Engineering from the National University of Singapore (2001) and a B.B.A. with First-Class Honors (1999) from the same institution. Holding editorial roles at Journal of Finance , Management Science , Review of Financial Studies and several other top journals, he is a leading voice in empirical finance research. Education Ph.D. in Finance, 2006 – Kellogg School of Management, Northwestern University M.Sc. in Financial Engineering, 2001 – National University of Singapore B.B.A. (1st Class Honors), 1999 – National University of Singapore Research Interests Zhi Da’s scholarship sits at the intersection of asset pricing , behavioral finance , and market microstructure . He investigates how investor attention, institutional trading, liquidity frictions, and information flows jointly determine the cross-section of expected returns. His work delves into retail margin trading, the role of pension-fund flows in exchange-rate dynamics, the informational content of SEC filings, and the efficiency of short-selling mechanisms. By combining large-scale data analytics, textual analysis, and structural modeling, he uncovers novel predictors of returns ranging from presidential approval ratings to real-time attention measures. Recent projects explore fractional trading ’s impact on price efficiency, hedging demand as a driver of intraday momentum, and the hidden effort problem in delegated portfolio management. These themes collectively advance our understanding of limits to arbitrage and the formation of extrapolative beliefs. Publication Landscape Spanning 2025 back to 2009, his 15 most recent articles in Journal of Finance , Review of Financial Studies , Management Science , Journal of Financial Economics , and Journal of Financial and Quantitative Analysis converge on three broad motifs: (1) micro-level trading frictions—liquidity costs, margin requirements, and short-selling constraints; (2) macro-finance linkages—exchange rates, fiscal policy, and global capital flows; and (3) information economics—attention allocation, media analytics, and regulatory disclosures. The collective evidence demonstrates that seemingly small trading or informational frictions aggregate into large, persistent cross-sectional return predictability. Honors and Awards 2017 William F. Sharpe Award for Best Paper, Journal of Financial and Quantitative Analysis Lead-article distinctions in Journal of Finance , Review of Financial Studies , and Management Science Featured coverage in SmartMoney and CNBC Teaching & Mentorship At Notre Dame’s Mendoza College, Professor Da teaches Investments (undergraduate and MBA) and Fixed Income Securities , integrating cutting-edge research insights into the curriculum. While specific advisees are not listed, his extensive co-author network (22+ recurring collaborators) attests to a vibrant mentoring environment. Laboratory & Data Resources He publicly distributes the NAT (Net Arbitrage Trading) dataset, a stock-quarter panel of arbitrage positions used in Chen, Da & Huang (2019). This resource has become a standard tool for researchers studying arbitrage capital movements.
- Retailing
- Digital Marketing
- Advertising
- +۴ مورد دیگر
Janna Parker is a professor in the Department of Marketing at James Madison University, specializing in digital marketing, retailing, and nonprofit marketing. With a career transition from political campaigns, she focuses on social media's role in personal and professional branding. Her research examines work-personal social media boundaries, employer governance policies, and volunteerism in nonprofit contexts. Education: Bachelor's in History (California State University Sacramento), Master's (Cameron University), Doctorate (Louisiana Tech) Teaching Interests: Digital marketing education, social media strategy, nonprofit marketing Her scholarly work spans social media governance, volunteer engagement, and retail dynamics, with recent emphasis on digital marketing pedagogy and cancel culture implications. Parker has contributed to academic journals through empirical studies and conceptual commentaries. Key article trends include: Digital marketing education evolution (2024) Social media governance in corporate and nonprofit contexts (2024) Online teaching satisfaction in higher education (2022) Volunteer brand community dynamics (2020) Consumer behavior frameworks (2019) Her media appearances include expert commentary on holiday retail strategies and social media research, reflecting practical applications of her academic work.
Daniel E. Ho holds multiple prestigious positions at Stanford University: William Benjamin Scott and Luna M. Scott Professor of Law Professor of Political Science Professor of Computer Science (by courtesy) Senior Fellow, Stanford Institute for Economic Policy Research Senior Fellow, Stanford Institute for Human-Centered Artificial Intelligence Faculty Fellow, Center for Advanced Study in the Behavioral Sciences He serves on the National Artificial Intelligence Advisory Commission (NAIAC), as Senior Advisor on Responsible AI at the U.S. Department of Labor, and as a Public Member of the Administrative Conference of the United States (ACUS). Ho earned his J.D. from Yale Law School and Ph.D. from Harvard University, completing a clerkship with Judge Stephen F. Williams on the U.S. Court of Appeals for the District of Columbia Circuit. His research bridges artificial intelligence, law, and public policy with emphasis on: Regulatory governance frameworks for AI systems Fairness and bias mitigation in algorithmic decision-making Environmental enforcement using satellite imagery and computer vision Methods for estimating racial disparities without direct demographic data Legal AI reliability and statutory research systems Analysis of his 2025 publications reveals a consistent focus on practical AI governance tools addressing real-world regulatory challenges. Key themes include developing benchmarks for legal applications, mitigating hallucination in legal AI tools, and creating systems for statutory research. His work demonstrates strong integration of technical AI methods with policy implementation, particularly in environmental enforcement and fairness assessment. As Director of the Regulation, Evaluation, and Governance Lab (RegLab), Ho leads interdisciplinary research partnerships with government agencies. While specific grant details aren't provided, RegLab's operational model indicates substantial research funding for policy-relevant AI projects. No student advisees are mentioned in available materials. Ho's leadership extends to national advisory roles where he shapes federal AI policy through evidence-based recommendations, particularly regarding environmental protection and civil rights enforcement mechanisms.
Ram Cnaan is a Professor of Social Work and Associate Dean for Research at the University of Pennsylvania, affiliated with The Weitzman School of Design. He chairs the Doctoral Program in Social Welfare and directs the Program for Religion and Social Policy Research. His work focuses on faith-based social services, congregational welfare provision, and nonprofit management. Cnaan has authored influential books like The Invisible Caring Hand and serves on seven academic journal editorial boards. His research explores volunteerism dynamics, including pandemic impacts on donor retention, cross-national civic participation, and episodic volunteering at religious events. He investigates social entrepreneurship in public sectors and evaluates faith-based organizations' roles in reentry programs for ex-prisoners. Cnaan's recent studies address CSR innovations, donor-advised funds strategies, and prosocial behavior in diverse cultural contexts. Notable contributions include pioneering national studies on congregational social service provision and analyzing Israeli-Palestinian Muslim collaboration in aid work. His work bridges academic research with practical policy solutions for urban quality-of-life challenges.
Liming Fengمشاهده پروفایل
دانشیار
Liming Feng is an Associate Professor at the Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, and has served as Director of the Master of Science in Financial Engineering (MSFE) program since 2022. His academic career at the university spans from Assistant Professor (2006-2012) to his current role. He earned his Ph.D. in Industrial Engineering and Management Sciences from Northwestern University (2006), an M.S. in Mathematics from Northwestern University (2000), and a B.S. in Mathematics from Beijing Normal University (1997). Ph.D., Industrial Engineering and Management Sciences, Northwestern University, 2006 M.S., Mathematics, Northwestern University, 2000 B.S., Mathematics, Beijing Normal University, 1997 Feng’s research focuses on Financial Engineering, Stochastic Modeling, and Computational Methods. He has contributed extensively to quantitative finance, particularly in options pricing, portfolio optimization, and market impact models. His work leverages advanced numerical methods, Fourier transforms, and stochastic calculus to solve complex financial problems. The trends in his publications highlight expertise in Levy processes, jump diffusion models, and numerical algorithms for financial derivatives. He has developed innovative techniques for Bermudan options pricing, discretely monitored barrier options, and portfolio deleveraging strategies. His articles often intersect Operations Research with Financial Engineering, emphasizing computational efficiency and mathematical rigor. ISE Faculty Fellow (2025) INFORMS Financial Services Section Best Student Research Paper (2013) First runner-up of the 2012 Morgan Stanley Prize for Excellence in Financial Markets Feng has served on editorial boards for Operations Research Letters and Mathematical Finance . He has been recognized repeatedly for teaching excellence, including the Sharp Outstanding Teaching Award (2011, 2022) and multiple entries in the List of Teachers Ranked as Excellent by Their Students (2007-2024). He currently leads the MSFE program and contributes to curriculum development through courses like IE 522 (Statistical Methods in Finance) and IE 527 (MSFE Professional Development).
Charles D. Sprenger is a Professor of Economics at the California Institute of Technology (Caltech), where he has served since 2020 and held the position of Executive Officer from 2022 to 2025. He is affiliated with Caltech's Division of the Humanities and Social Sciences (HSS) and holds key roles at the Ronald and Maxine Linde Institute of Economic and Management Sciences and the Center for Theoretical and Experimental Social Sciences (CTESS). His external appointments include Board of Editors for the American Economic Review and Associate Editor roles for the Journal of the European Economic Association and Quantitative Economics . His educational background includes a B.A. from Stanford University (2002), an M.Sc. from University College London (2005), and a Ph.D. from the University of California, San Diego (2011). These credentials established his foundation in economic theory and experimental methodology. Sprenger is a leading behavioral and experimental economist specializing in intertemporal decision making and choices under uncertainty. His research designs innovative experiments across diverse contexts—from food deserts in the United States to polio vaccination drives in Pakistan—to test the validity of standard economic models. His work consistently reveals significant deviations from rational choice theory, particularly regarding time inconsistency, risk preferences, and reference-dependent behaviors. He has pioneered methods for measuring time preferences and testing cumulative prospect theory, with implications for public policy and behavioral interventions. Analysis of his 15 most recent publications (2015-2024) shows a cohesive research program centered on behavioral anomalies in decision making. His work bridges laboratory precision with real-world field applications, demonstrating how psychological factors like procrastination and loss aversion manifest in high-stakes environments. Key trends include the development of tailored incentive structures, validation of rank-dependent utility models, and exploration of dynamic inconsistency across domains including health, finance, and public policy. His notable recognition includes: Sloan Foundation Fellowship (2016-2018) Sprenger actively contributes to the academic community through editorial leadership and collaborative research. His work has been featured in Caltech news for projects like "Reducing Procrastination with Tailored Incentives" (2023) and the graduate summer program "Experimental Economics in Theory and Practice" (2023). Though specific advisees aren't listed, his teaching of advanced courses like Experimental Economics (SS 212 abc) indicates mentorship of graduate researchers. He secures significant research funding through fellowships and institutional support, enabling large-scale field experiments. As a core member of CTESS, Sprenger leads a multidisciplinary team conducting cutting-edge experimental economics research. His lab integrates theoretical modeling with empirical validation, focusing on how behavioral insights can improve policy design in areas like tax compliance, vaccination programs, and financial decision making. Current work emphasizes scalable interventions for procrastination and preference-based incentive customization.
Julian Limbergمشاهده پروفایل
مدرس ارشد
- Public Policy
- Political Economy
- Tax Policy
- +۳ مورد دیگر
Dr. Julian Limberg is a Senior Lecturer in Public Policy at the Department of Political Economy, King’s College London. He previously held a post-doctoral position at Ludwig Maximilian University of Munich and earned his PhD in Political and Social Sciences from the European University Institute. His research focuses on public policy and political economy, particularly inequality dynamics, tax policy, and environmental governance. Education: PhD in Political and Social Sciences (European University Institute), Post-doctoral Research (Ludwig Maximilian University). Affiliations: Public Policy and Regulation Research Group, Quantitative Political Economy Research Group, Global South Research Group. His work examines the causes and consequences of progressive taxation, climate policy effectiveness, and public perceptions of fiscal fairness. Recent studies include the impact of dedicated climate ministries on emissions reduction and the link between financial sector growth and tax policies. Limberg is also engaged in projects analyzing how technological changes influence tax preferences and the societal consequences of major tax cuts for the wealthy. Key articles highlight his contributions to understanding taxation trends, climate policy implementation, and the interplay between economic shifts and fiscal strategies. He collaborates across disciplines, bridging political science and economics to address contemporary governance challenges.
- Data Ethics
- AI Ethics
- Technology Governance
- +۴ مورد دیگر
Professor Brent Mittelstadt is a leading academic in data ethics and AI governance at the University of Oxford's Oxford Internet Institute (OII), serving as Professor of Data Ethics and Policy and Director of Research. He coordinates the Governance of Emerging Technologies (GET) programme, focusing on ethics, law, and technology interplay. His work bridges academic research with policy impact, contributing frameworks like 'counterfactual explanations' and fairness metrics ('Conditional Demographic Disparity') used globally. He leads high-profile projects such as Trustworthiness Auditing for AI and A Right to Reasonable Inferences in Advertising and Financial Services. Research interests span AI ethics, medical ethics, technology governance, and non-discrimination law. He has pioneered ethical frameworks addressing algorithmic bias, GDPR compliance, and AI accountability. His work has influenced policy bodies like the UK Information Commissioner’s Office and the European Commission, and is implemented by tech giants such as Google and Microsoft. Awarded O2RB Excellence in Impact Awards (2018, 2021) and PLSC Best Paper (2019) Funded by Wellcome Trust, Sloan Foundation, and others Advisory roles for NHSx, GSK Consumer Healthcare, and regulatory bodies Recent work focuses on AI regulation (EU AI Act), generative AI ethics, and healthcare AI governance. He co-leads the OxonFair toolkit for algorithmic fairness and investigates societal impacts of deepfake proliferation and large language models.
Chen Lianمشاهده پروفایل
استادیار
- Macroeconomics
- Behavioral Economics
- Finance
- +۳ مورد دیگر
Chen Lian is an Assistant Professor in the Department of Economics at UC Berkeley. Holding a PhD from MIT, their research bridges macroeconomics, behavioral economics, and finance, with a focus on bounded rationality, monetary theory, and macro-finance interactions. Education: PhD in Economics, MIT Chen’s work explores how incomplete information and behavioral biases shape macroeconomic outcomes. Key themes include inflation effects on households, fiscal-monetary policy interactions, and financial stress dynamics. They employ heterogeneous-agent models and analyze how micro-level shocks propagate through the economy. Their publications and working papers address topics like credit cycles, demand shock propagation, and the psychological underpinnings of economic decisions. Papers such as Low Interest Rates and Risk Taking (2019) and Confidence and the Propagation of Demand Shocks (2022) highlight their interdisciplinary approach.
Jakob Foersterمشاهده پروفایل
دانشیار
Jakob Foerster is an Associate Professor at the University of Oxford's Department of Engineering Science and a Supernumerary Fellow at St Anne's College. He leads the FLAIR lab, focusing on multi-agent reinforcement learning (MARL), human-AI coordination, and AI foundational research. Previously, he was a Research Scientist at Facebook AI Research (FAIR) and holds a DPhil from Oxford. His work has been cited over 5,000 times and includes seminal contributions like QMIX and the Hanabi Challenge. Research interests span compute-efficient scaling of AI, MARL applications in finance and bio, and ethical AI. He actively collaborates across academia and industry, co-organizing workshops like NeurIPS' Emergent Communication. His lab emphasizes open-ended RL, environment design, and scalable algorithms. Notable awards include the CIFAR AI Chair (2019) and NeurIPS Best Paper Runner-Up (2018). Current efforts include FLAIR's research on zero-shot coordination and the JaxMARL framework. He advises students in Oxford's Engineering DPhil and AIMS CDT programs.
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