Dr. Zhen Qi is an Assistant Professor of Finance at the Department of Management and Organizational Studies, Western University. He holds a Ph.D. in Finance from the University of Manitoba (2024), an M.S. in Finance from University of International Business and Economics (2017), and a B.A. in Finance from Beihang University (2015). His research focuses on empirical asset pricing , climate finance , machine learning applications in finance , and international finance . Key themes include analyzing climate risk disclosures' impact on financial markets, macroeconomic uncertainty effects on global equity markets, and machine learning techniques for predicting bond returns. Teaching specialties include Investments and Corporate Finance . His work has been published in journals like British Journal of Management , Journal of International Financial Markets , and Finance Research Letters . No scientific awards or grants are explicitly mentioned in the provided materials. He currently advises no listed students and has no stated lab affiliations.
Dr. Li Ma is a Professor in the Department of Animal & Avian Sciences at the University of Maryland, College Park. His research focuses on statistical genetics, population genetics, and genomic selection in livestock, particularly dairy cattle. He develops computational tools to enhance genetic studies using next-generation sequencing data, with applications in improving livestock productivity and disease resistance. His work includes analyzing recombination patterns and PRDM9 alleles in dairy cattle breeding, genomic selection strategies using large-scale datasets, and integrating multi-omic data for precision livestock breeding. He also explores big data analytics in agricultural genomics. Notable research areas include sequence-based genomic discovery, genetic architecture of complex traits, and applying machine learning to genetic studies. His recent articles (2024–2025) show interdisciplinary work in financial econometrics, addressing topics like risk management, stochastic volatility modeling, and option pricing strategies. This dual focus suggests expertise spanning both biological and quantitative finance domains. Dr. Ma collaborates on projects involving genomic databases, statistical method development, and computational biology tools. His work bridges genetic research and advanced financial modeling, though specific student advisement details are not listed here.
Mihail Velikov is an Assistant Professor of Finance at Penn State University's Smeal College of Business. His research focuses on empirical asset pricing, stock market anomalies, and the application of AI/machine learning in finance. He holds a PhD in Finance from the University of Rochester. Education: PhD in Finance, University of Rochester, 2015 MSBA in Applied Economics, University of Rochester, 2013 Bachelor's in Mathematics and Finance (double major), Ramapo College of New Jersey, 2010 (Summa Cum Laude) Research Interests: His work explores transaction costs, investment strategies, and the use of AI to enhance asset/wealth management. Key themes include anomaly evaluation protocols, cost-mitigation techniques, and the integration of machine learning into financial models. Awards: William F. Sharpe Award (2023) Graham and Dodd Scroll Award (2019) INQUIRE Europe Research Grant (2025) Geneva Institute for Wealth Management Research Grant (2022) Advising & Grants: Advised doctoral students including Han Xiao (CUHK-Shenzhen) and Lu Yang (Analysis Group). Secured grants such as the INQUIRE Europe grant and multiple Smeal Small Research Grants. Co-led the Federal Reserve Bank of Richmond's DFAST supervisory modeling team for bank stress testing. Labs/Teams: Active in AI-driven finance research, collaborating on projects like the Assaying Anomalies protocol and the AI-Powered (Finance) Scholarship initiative.
Lin Tong is a tenured Associate Professor in Finance and Business Economics at Fordham University's Gabelli School of Business, where she joined in 2014. She holds a PhD in Finance from the University of Iowa, an MS in Mathematics from Iowa State University, and a BA in Mathematics from Nanjing University. Her research examines institutional investors, high-frequency trading, mutual funds, and behavioral finance. She has published in top journals including Management Science and Review of Financial Studies , with work featured in The Economist and Barron's . Her publications consistently explore market microstructure dynamics, investor psychology, and performance evaluation. Recent work (2021-2024) focuses on information asymmetry in M&A, mutual fund competition, and international asset pricing anomalies. Dr. Tong serves as a reviewer for numerous finance journals and presents regularly at major conferences including the American Finance Association and European Finance Association meetings.
Andrew Brim is a Professional Practice Assistant Professor in the Department of Data Analytics and Information Systems at the Huntsman School of Business, Utah State University. He holds a PhD (2020), MS (2019), and BS (2006) in Computer Science from USU. Prior to academia, he worked at Bank of America as a software developer for Global Markets Trading Technology, focusing on credit and rates derivative trading systems. His research interests include artificial intelligence for stock market predictions, reinforcement learning applications, and algorithmic trading strategies. He mentors the Algorithmic Trading club and teaches courses such as Advanced Financial Accounting and Financial Accounting Principles. Notable awards include the 2025 USU Eldon J. Gardner Teacher of the Year and 2025 Huntsman School Teacher of the Year. His recent publications emphasize deep reinforcement learning techniques in financial markets and CNN-based trading models.
Kevin B Fornshill serves as a Lecturer in the Department of Criminology, Law and Society at George Mason University, specializing in extremism research and hate crime investigation. His instructional portfolio includes CRIM 325: Hate Crimes and CRIM 490: White Extremist Ideology and Criminal Behavior, earning him the Department's Instructor Appreciation Award (2016-2017) and the ADL SHIELD Award (2010) for decade-long contributions to hate crime investigations in the National Capital Region. His academic foundation comprises an M.A. in Criminal Justice from Boston University, a B.A. in Public Affairs from George Mason University, and specialized federal training through the Criminal Investigative Training Program (CITP-601) and Police Integrated Training Program (PITP-703) at the Federal Law Enforcement Training Center. Fornshill's research centers on white supremacist ideology and terrorism trends, maintaining the Law Enforcement Online Special Interest Group on White Extremism with extensive resources including extremist literature, tattoo documentation, and multimedia files. His secondary scholarly output in neuroeconomics—evident in 15 recent publications—examines trust dynamics, market behavior, and decision neuroscience through experimental frameworks, though this economic research appears distinct from his institutional criminology profile. Key recognitions include: George Mason University Instructor Appreciation Award (2016-2017) ADL SHIELD Award for hate crime investigation (2010) He actively bridges academia and law enforcement through expert testimony (Supreme Court of Canada, New Brunswick Court of Appeals), DHS/FLETC instruction, and presentations at venues including the TiNYg 2024 Strategic Security Conference and FBI Terrorism Trends Training. His operational work with the Law Enforcement Online SIG facilitates nationwide intelligence sharing on extremist threats. Fornshill's Enterprise Hall office coordinates critical resources for federal, state, and local agencies combating domestic extremism through the White Extremism SIG platform.
Jason P. Berkowitz serves as Associate Professor and Associate Academic Dean in the Department of Economics and Finance at The Peter J. Tobin College of Business, St. John's University, where he has been a faculty member since fall 2012. He holds a Ph.D. in Finance from the University of North Carolina at Charlotte, complemented by an MS and BBA in Finance from The George Washington University. His educational background includes: Ph.D., Finance, University of North Carolina at Charlotte MS, Finance, The George Washington University BBA, Finance and Sports Management, The George Washington University Dr. Berkowitz specializes in investments and behavioral finance, with distinctive research applying sports betting markets (particularly college basketball and football) as proxies for financial market analysis where real-world data is scarce. His work examines market anomalies like point shaving, favorite-longshot bias, and volatility trading using sports contexts to model financial phenomena. Analysis of his 2011-2018 publications reveals consistent focus on sports betting markets as laboratories for financial behavior. Key trends include exploiting college sports data to study market inefficiencies, news reaction asymmetries, and asset class applications—demonstrating how sports contexts illuminate broader financial principles. Prior to academia, Dr. Berkowitz gained industry experience as Director of Finance for the Wilmington Blue Rocks and stadium concessions manager at major venues including Lincoln Financial Field and RFK Stadium. His administrative role as Associate Academic Dean indicates significant institutional responsibilities beyond teaching core finance courses like Derivatives and Investments.
Benjamin HOLCBLAT is an Assistant Professor in Data Analytics and Finance at the University of Luxembourg's Faculty of Law, Economics and Finance (FDEF), Department of Finance. He holds a Senior Research Scientist role alongside his academic position. His contact details include benjamin.holcblat@uni.lu and office F 003 at 6 Rue Richard Coudenhove-Kalergi, Luxembourg. Education: Ph.D. in Financial Economics, Carnegie Mellon University M.Sc. in Finance, Carnegie Mellon University M.Res. in Economics, University of Paris (Panthéon Sorbonne-Paris School of Economics) "Economist-Statistician" diploma, ENSAE Paris (Institut Polytechnique de Paris) Research Interests: Dr. HOLCBLAT specializes in Data Science applied to finance, econometric methodologies, and asset pricing models. His work bridges quantitative techniques with financial market analysis, evidenced by an h-index of 80 ('excellent'). His research often addresses modern challenges in financial economics through advanced data analytics. Publications: Active contributor on ORBilu, though specific article details are not provided here. His work likely spans empirical finance, computational methods, and market microstructure. Grants & Advising: No current grants or advisee records are explicitly stated in available texts. Labs/Teams: Not specified in provided materials, though his role suggests involvement in interdisciplinary finance research groups.
Thomas Henker is a Professor at Bond Business School, Bond University (Gold Coast, Australia). He holds a PhD in Finance from the University of Massachusetts (awarded 1999) with a dissertation on Bid and Ask Spreads in Futures Markets . His research focuses on market microstructure and investor behavior. Henker's research examines: Investor decision-making patterns (retail investors, risk-taking behavior) Market dynamics (volatility, short selling effects, dark pool fragmentation) Financial instruments (hedge funds, volatility modeling) Market anomalies (idiosyncratic volatility puzzle) His 29 publications (2004-2018) demonstrate consistent focus on empirical finance using methodologies like experimental design and market data analysis. Recent works investigate hedge fund clustering (2018), short-selling regulation impacts (2017), and dark pool market structure (2014).
Steve Crawford is an Associate Professor of Accounting at the C. T. Bauer College of Business , University of Houston, where he has taught since 2014. He specializes in Financial Statement Analysis for MSACCY and MBA programs, and has received five teaching awards for his contributions. PhD and MBA from University of Chicago's Booth School of Business (2007) BA and MAcc from Brigham Young University (2002) His research focuses on financial analysts, market dynamics, corporate disclosure practices, and compensation structures. Publications appear in top-tier journals including Review of Accounting Studies and Management Science , with recurring themes in: Energy Finance (oil price impacts on earnings) Market Efficiency (analyst coverage effects on stock returns) Disclosure Dynamics (management forecasts and information sharing) Investment Behavior (buy-side analyst motivations and fund manager strategies) Scientific recognition includes five teaching awards at Bauer College. His professional trajectory spans: Assistant Professor at Rice University's Jones Graduate School Current associate professor role at University of Houston Contact: scrawford@bauer.uh.edu | Office: MH 390G | Phone: 713-743-5329
Ariadna Dumitrescu is an Associate Professor at the Department of Economics, Finance and Accounting within Esade Business School, Ramon Llull University. Her research focuses on corporate governance, financial markets, and investor behavior. She leads the Group of Research in Economics and Finance (GREF), contributing to interdisciplinary studies on sustainable finance and market transparency. Her work addresses topics such as ESG investing, debt restructuring, and insider trading, with implications for regulatory frameworks and market efficiency. Research Projects: Principal investigator of projects like IDFM: Information Disclosure in Financial Markets (2022–2025) and Innovación tecnológica y transparencia de los mercados financieros (2019–2021). Co-leads the GREF: Group for Research in Economics and Finance , a multidisciplinary team exploring financial economics and policy. Research Interests: Her studies investigate how corporate governance structures influence market outcomes, particularly stock returns and investor decision-making. She analyzes liquidity dynamics, debt restructuring mechanisms, and the role of private information in financial markets. Recent work explores ESG ETF performance and carbon market potentials. Grants & Collaboration: Funded by agencies like the Agencia Estatal de Investigación and MINECO. Collaborates internationally, with projects addressing market transparency, technological innovation in finance, and governance-impact studies. Labs/Teams: Active in the Esade Corporate Governance Center and GREF, fostering applied research and policy recommendations in finance and economics.
Dr. Heather Sorcha is an Associate Professor at Michigan Technological University's College of Business. She holds a PhD in Finance from Washington State University (2011), an MA in Applied Economics (2010), and a BA in Actuarial Science from Roosevelt University (1999). Her research focuses on FinTech innovations, market efficiency, and investor behavior. Dr. Sorcha's research examines financial technology disruption, insider trading patterns, and sentiment-driven market anomalies. She utilizes econometric modeling to investigate behavioral finance phenomena in capital markets. Her publications demonstrate consistent focus on financial education methodologies and market microstructure analysis. Recent works explore experimental finance, FinTech ecosystems, and pedagogical innovations in investment education. Teaching Awards: Academy of Teaching Excellence (Michigan Tech, 2018) Dean's Teaching Showcase (Michigan Tech, 2017) Dean's Teaching Award (Central Michigan University, 2013) Graduate Student Teaching Excellence (WSU, 2010) She chairs the College Strategic Planning Committee and serves on editorial boards for finance journals.
Dr. John O'Hara is an Honorary Senior Lecturer at the University of Essex's School of Mathematics, Statistics and Actuarial Science. He holds additional affiliations as a Research Fellow at Stellenbosch University and an Honorary Associate Professor at the University of Cape Town. His expertise spans financial mathematics, machine learning in finance, stochastic processes, and quantitative finance. Education: BSc in Pure Mathematics, University of Ulster (1976) PGCE in Education, Queen’s University Belfast (1977) MSc in Probability Theory (Hilbert Spaces), Queen’s University Belfast (1981) PhD in Differential Equations, University of the Witwatersrand (1991) His research focuses on financial mathematics and machine learning applications in finance, including volatility modeling, option pricing, and algorithmic trading strategies. O'Hara is a Fellow of the Institute of Mathematics and its Applications and a member of the London Mathematical Society. He previously directed the Centre for Computational Finance and Economic Agents (CCFEA) at Essex and has held academic leadership roles in Southern African institutions. Awards and Memberships: Fellow of the Institute of Mathematics and its Applications London Mathematical Society Membership Professional Activities: O'Hara has contributed to interdisciplinary research at the intersection of finance and computational methods. His work emphasizes symmetry analysis in financial PDE models and innovative applications of wavelet transforms to option pricing. He has supervised multiple research projects in computational finance and maintains active collaborations across institutions. Labs and Centers: Director, CCFEA (2019–2021) Research Fellow, School for Data Science and Computational Thinking, Stellenbosch University
David Maslar is an Assistant Professor of Finance and Academic Director of the Full-Time MBA program at the University of Tennessee's Haslam College of Business. He holds a Ph.D. in Finance from the University of Missouri (2013), with additional master's degrees in Applied Mathematics and Economics from the same institution, and a B.S. in Economic Analysis from Binghamton University (2006). His research focuses on investments, market microstructure, and fixed income, with notable publications in the Journal of Corporate Finance and Journal of Financial Markets. Maslar has received multiple teaching awards, including the Sharon Miller-Pryse Outstanding Finance Faculty Award (2017, 2019) and the John A. Riggs Excellence in MBA Teaching Award (2014). His work has explored topics such as bond mutual funds, political connections, and agency costs of debt. Education: Ph.D. in Finance, University of Missouri, 2013 M.S. in Applied Mathematics, University of Missouri, 2009 M.A. in Economics, University of Missouri, 2009 B.S. in Economic Analysis, Binghamton University, 2006 Research Interests: Empirical asset pricing, fixed income analysis, market microstructure dynamics, and the impact of political connections on corporate debt costs. His work bridges theoretical frameworks with empirical analysis, often addressing liquidity, institutional investor behavior, and market efficiency in financial markets. Awards & Honors: MBA First Year Outstanding Commitment to Students Faculty Award (2020) Semi-Finalist, FMA Best Paper Award (2017–2020) John A. Riggs, Jr. Excellence in MBA Teaching Award (2014) Sharon Miller-Pryse Outstanding Finance Faculty Award (2017, 2019) Teaching & Service: Teaches Financial Management, Fixed Income, and Financial Markets courses at both undergraduate and MBA levels. Served as Ph.D. Program Committee member (2016–2020), seminar coordinator, and dissertation committee member at the University of Tennessee. Active in academic service, including roles as discussant for major finance conferences. Labs/Teams: Collaborates with researchers on topics such as market microstructure, corporate finance, and institutional investor strategies through interdisciplinary projects and conference presentations.
Vincent Bogousslavsky is an Associate Professor in the Seidner Department of Finance at Boston College's Carroll School of Management. His research focuses on asset pricing, market microstructure, liquidity, and informed trading. He holds a Ph.D. from the Swiss Finance Institute at EPFL and previously served as a Visiting Assistant Professor at the University of Chicago's Booth School of Business (2021–2022). Education: Bachelor of Science, University of Lausanne Master of Science, University of Lausanne Doctor of Philosophy (Ph.D.), Swiss Finance Institute, EPFL Research Interests: His work examines topics such as liquidity dynamics, market efficiency, and the implications of trading behavior on asset pricing. Recent projects include analyzing informed trading intensity, retail option trading patterns, and the impact of market glitches on execution costs. Publications: His research has been featured in top journals like the Journal of Finance and Journal of Financial Economics . Key themes include intraday return patterns, order imbalance volatility, and the cross-sectional analysis of market anomalies. Awards: He received the NASDAQ OMX - CQA Prize (Runner-up) at the EFA Doctoral Tutorial in 2014. Advising/Grants: While no explicit list of advisees or grants is provided, his extensive publication record suggests active engagement in academic research and mentorship. His personal website ( https://bogousslavsky.github.io/ ) offers further insights into his work.
