جست‌وجوی استاد و پژوهشگر

Yongqin Leiمشاهده پروفایل

استادیار

• behavioral operations management
• two-sided platforms
• operations-marketing interface

Yongqin Lei serves as an Assistant Professor in Operations and Supply Chain Management at the University of Winnipeg, where he teaches undergraduate courses including Introduction to Business (BUS-1201), Operations Management (BUS-2501), and Advanced Prescriptive Analytics (GBUS-7235). Previously, he instructed Competing with Analytics at Ivey Business School with a teaching rating average of 6.64/7. His academic credentials include a BBA with Mathematics minor from Dalhousie University and a PhD in Management Science from the University of Western Ontario. Lei's research centers on behavioral operations management, specifically examining how psychological factors influence operational decisions in two-sided platforms and marketing interfaces. His work investigates corporate wellness incentives, probabilistic pricing mechanisms, and marketplace dynamics affected by counterfeits and fake reviews, revealing critical interactions between consumer behavior and operational strategy. His scholarly output demonstrates consistent focus on behavioral aspects of platform economics and pricing innovation, with recent publications spanning credence goods markets, probabilistic promotions, and corporate wellness programs. This body of work bridges operations research with marketing and behavioral science through rigorous analytical modeling. His scientific recognition includes: Graduate Fellowship (2022, 2023) John F. Rankin Doctoral Scholarship (2021) Ivey Plan for Excellence PhD Fellowship (2020-2024) Dalhousie In-Course Scholarship Finalist, 2023 DSI Doctoral Research Showcase Award Lei actively contributes to academic service as an ad hoc reviewer for Production and Operations Management and International Journal of Production Research, while mentoring Ivey PhD students. His conference presentations at INFORMS, DSI, POMS, and CORS reflect ongoing engagement with the operations research community.

Hao Niمشاهده پروفایل

استاد

• Stochastic Analysis
• Machine Learning
• Rough Path Theory
• +۵ مورد دیگر

Hao Ni is Professor of Mathematics at University College London (UCL), where she leads the UCL Rough Path Theory and Machine Learning Group and serves as co-director of the EPSRC Centre for Doctoral Training in Collaborative Computational Modelling at the Interface (CCMI). As a co-investigator of the EPSRC Program grant on 'Unparameterised multi-modal data, high order signatures, and the mathematics of data science,' she bridges theoretical mathematics with practical machine learning applications. Previously, she was an Associate Professor at UCL (2016-2022) and held postdoctoral positions at Oxford-Man Institute of Quantitative Finance and Brown University. DPhil in Mathematics, University of Oxford (2012) MSc in Mathematics, University of Oxford (2009) BSc in Mathematics, Southeast University (2008) Ni's research centers on stochastic analysis and machine learning, with a focus on rough path theory as a mathematical framework for modeling complex multi-modal data streams. She develops high-quality generative models for synthetic time series generation with applications spanning computer vision, healthcare, biology, and quantitative finance. Her work on signature-based methods has produced innovative approaches for skeleton-based action recognition, sepsis prediction, and financial data analysis. The signature of a path, originating from rough path theory, serves as a principled feature for sequential data that often boosts performance when combined with state-of-the-art machine learning methods. Ni's publication record reveals a strong trajectory in developing mathematical foundations for data science, with recent work extending signature methods to Riemannian manifolds, creating novel GAN architectures for time series generation, and applying these techniques to real-world problems in healthcare and finance. Her research increasingly bridges pure mathematics with practical applications, particularly in generative modeling and time series analysis. Turing Fellow at the Alan Turing Institute (2016-2024) Co-investigator of EPSRC Program grant on Unparameterised multi-modal data Member of London Mathematical Society As an academic leader, Ni has secured significant research funding through EPSRC and Turing Institute collaborations. She actively promotes equality, diversity, and inclusion by co-founding the WINDSMATH seminar series (2022), which showcases cutting-edge research by women and non-binary scholars in mathematics and data science with over 750 global subscribers. Her group organizes seminars, workshops, and conferences while developing open-source code repositories for real-world applications. Ni also organizes digital data hackathons focused on trustworthy synthetic time series generation through deepintomlf.ai. Ni leads the UCL Rough Path and Machine Learning Research Group, which develops mathematical and numerical toolsets based on rough path theory to advance machine learning research on analyzing multi-modal complex data. The group's research spans expected signature theory, synthetic time series generation, human-computer interfaces, and molecule learning, with applications in finance, healthcare, and computer vision.

Benjamin Watsonمشاهده پروفایل

دانشیار

• Computer Graphics
• Human-Computer Interaction
• Visual Perception
• +۶ مورد دیگر

Benjamin Watson serves as an Associate Professor in the Department of Computer Science at North Carolina State University, leading the Visual Experience Lab which investigates how humans derive meaning from visual information through computer graphics, perception, design, and interaction. His work spans applications in entertainment, security, finance, education, and medicine, with leadership roles in major conferences including Graphics Interface, IEEE Virtual Reality, and ACM I3D. He holds senior membership in IEEE and active membership in ACM. Watson's educational background includes: Ph.D. from Georgia Tech (1997) M.S. from Georgia Tech (1997) B.S. from UC Irvine (1987) His research centers on visual perception and interaction, with core expertise in computer graphics, human-computer interaction, and user experience design. Key investigations include perceptual asymmetries in rendering, display technologies for immersive environments, and human performance optimization in high-stakes contexts like esports. The Visual Experience Lab bridges theoretical computer science with practical applications in healthcare, finance, and entertainment through interdisciplinary collaboration. Analysis of Watson's 2019-2025 publications reveals consistent focus on display technology limitations and human performance metrics. His work demonstrates increasing specialization in esports HCI (7 of 10 recent papers), particularly examining display size, rendering techniques, and frame rate impacts on aiming accuracy. Concurrently, he maintains strong contributions to light field displays and multi-view rendering, developing novel point-based methods that exploit perceptual redundancies for real-time performance. Scientific recognition includes: NVIDIA Professor Partnership Award (2007) National Science Foundation Faculty Early Career Award (2006) Watson actively mentors graduate researchers including Ph.D. graduate Adam Marrs (now at NVIDIA) and Holle Christensen, whose work on experience analytics received workshop acceptance at ACM DIS. His $772k+ in active and recent funding spans NSF grants for adaptive rendering systems ($497k), human-machine collaboration projects with the Laboratory for Analytic Sciences ($180k), and Caterpillar-sponsored AR applications ($20k), demonstrating strong industry-academia translation. The Visual Experience Lab operates as a cross-disciplinary hub connecting computer science, design, and cognitive psychology researchers. Current projects focus on real-time GPU acceleration for multi-view rendering, esports performance optimization, and AR applications for industrial equipment, with active partnerships including Caterpillar, NVIDIA, and the Laboratory for Analytic Sciences.

Sridhar Seshadriمشاهده پروفایل

استاد

• Stochastic modeling
• Supply chain management
• Revenue management
• +۳ مورد دیگر

Sridhar Seshadri is the Alan J. and Joyce D. Baltz Endowed Professor and Professor of Business Administration at the University of Illinois at Urbana-Champaign. He has served as Area Chair of Information, Operations, Supply Chain, and Analytics (2018-2022) and Health Innovation Professor at the Carle Illinois College of Medicine. His affiliations span operations management, supply chain analytics, and healthcare innovation. Educational Background: PhD in Management Science, University of California at Berkeley (1993) Postgraduate Diploma in Management, Indian Institute of Management Ahmedabad (1980) Bachelor of Technology in Mechanical Engineering (with distinction), Indian Institute of Technology Madras (1978) Research Interests focus on stochastic modeling and its applications in queueing systems , supply chain management , and revenue management . His work addresses dual sourcing inventory systems, epidemic modeling for supply chains, AI-augmented healthcare workflows, and the intersection of operations and financial markets. Recent publications include analyses of commodity trading under uncertainty , AI in neurology , and pandemic response strategies . Key Scientific Contributions are recognized through: 2022 INFORMS Revenue Management and Pricing Section Practice Award Fellow of the Production and Operations Management Society (2018-present) James F. Towey Faculty Fellow (2018) Grants and Leadership include projects on Health Access Points in Rural Illinois (2024-2026), Business Analytics Collaboratory (2021-2023), and Dynamic Resource Management for Pandemics (2020-2021). He has served as Department Editor for Production & Operations Management and Associate Editor for Management Science .

Nataļja Lāceمشاهده پروفایل

استاد

• Small and Medium Enterprise Performance
• Innovation Management
• Business Finance
• +۵ مورد دیگر

Nataļja Lāce is a Professor and leading researcher at the Institute of Economics and Entrepreneurship within the Faculty of Engineering Economics and Management at Riga Technical University (RTU). With over 40 years at RTU and 18 years as a professor, she directs the master's program "Business Finance," ranked 1st in Eastern Europe for corporate finance by EDUNIVERSAL. She leads the academic finance research group and serves on multiple international networks, including the "Society of Open Innovation: Technology, Market, and Complexity" (SOItmC) since 2015. Education : PhD in Economics (1993) Leadership Roles : Study Program Director (17 years), Department Head (14 years) Research Focus : SME performance, innovation, business finance, ESG implementation, venture capital Projects : 5+ international grants (Horizon Europe, ERASMUS+, etc.) Publications : 87 Scopus-indexed articles, H-index 11 Her recent work spans cyber resilience, Islamic banking, human capital metrics, and sustainable tourism. She actively serves as a reviewer for theses and participates in academic governance across Latvia, Lithuania, and the Czech Republic.

Dmitri Markovitchمشاهده پروفایل

دانشیار

• Marketing Strategy
• Innovation Management
• Marketing-Finance Interface
• +۳ مورد دیگر

Dr. Dmitri Markovitch is an Associate Professor of Marketing at the Maine Business School (University of Maine) since 2017. Previously, he held full-time faculty positions at HEC-Paris, Rensselaer Polytechnic Institute, and FGV/EBAPE (Brazil). His research focuses on innovation strategies, marketing-finance interface, decision-making under uncertainty, and AI’s impact on customer outcomes. He has been widely published in top journals like Management Science and Marketing Science . Dr. Markovitch holds a Ph.D. and M.Phil. in Marketing from NYU, an MBA from Southwestern Oklahoma State University, and a B.A. in Applied Linguistics from Minsk State Linguistic University. His teaching areas include Principles of Marketing, Integrated Marketing Communications, and Marketing Research. His research explores financial returns from marketing investments, cognitive biases in managerial decisions, and AI applications in marketing. Recent work investigates how capital markets react to R&D expenditures and marketing strategies. He has received prestigious awards such as the Best Paper award at the 2014 Winter AMA Conference and the Most Promising Paper award at the 2011 Academy of Management Conference. Key Honors: Marcus Nadler Fellowship (NYU, 2003–04), AMA-Sheth Doctoral Consortium Fellow (2002) Dr. Markovitch’s research spans over two decades, with 20+ peer-reviewed articles and book chapters. His work bridges marketing strategy with finance and behavioral economics, addressing practical challenges in new product launches, resource allocation, and market valuation.

Vladik Kreinovichمشاهده پروفایل

استاد

• Uncertainty Management
• Interval Computations
• Fuzzy Logic
• +۷ مورد دیگر

Professor Vladik Kreinovich is a renowned academic in the Department of Computer Science at the University of Texas at El Paso (UTEP), part of the College of Science. His primary research focuses on uncertainty management, interval computations, fuzzy logic, and decision-making under uncertainty. He holds a Doctor Honoris Causa from Ostrava University and is a Fellow of the International Fuzzy Systems Association (IFSA) and the Mexican Society for Artificial Intelligence (SMIA). His academic journey includes a B.S. and M.S. from St. Petersburg University and a Ph.D. from the Institute of Mathematics in Novosibirsk, Russia. Dr. Kreinovich has authored over 1,500 publications, with notable contributions to interval analysis, computational intelligence, and interdisciplinary applications in geoscience and environmental science. Awards include the K. S. Fu Award, Meritorious Service Award from IEEE, and the El Paso Energy Foundation Faculty Achievement Award. He serves on editorial boards for journals like Reliable Computing and International Journal of Approximate Reasoning . His teaching spans automata theory, formal languages, and advanced topics in computing paradigms. Grants include an AT&T Fellowship (2021–2028), and he actively contributes to conferences such as IFSA, EUSFLAT, and NAFIPS. His work bridges theoretical foundations with practical applications, emphasizing robust algorithms for uncertain data and interdisciplinary collaboration.

• Artificial Intelligence
• Explainable AI
• Human-Computer Interaction
• +۵ مورد دیگر

Yunfeng Zhang is a Professor at Shandong University of Finance and Economics specializing in Artificial Intelligence with significant contributions to Explainable AI, Human-Computer Interaction, and Machine Learning. His research spans computer vision, fairness in AI, and robotics applications across diverse domains including transportation, agriculture, and cybersecurity. Zhang has established strong international collaborations with IBM Research (notably with Kush Varshney and Q. Vera Liao) and publishes extensively in top venues like CHI, KDD, and IEEE Transactions. His research interests focus on making AI systems transparent and trustworthy through the AI Explainability 360 toolkit development since 2020, human-AI collaboration frameworks, and fairness optimization in machine learning. Recent work shows a strategic pivot toward applied AI problems including urban rail transit optimization, agricultural robotics for citrus detection, and VR-enhanced education systems in China. Zhang's publications demonstrate exceptional breadth across both theoretical foundations and real-world implementations of AI technologies. Zhang's recent publications (2023-2025) reveal strong trends in multimodal AI applications, with significant work in computer vision for remote sensing and industrial automation, reinforcement learning for transportation systems, and educational technology innovations. His work consistently bridges technical AI development with human-centered design principles, particularly evident in his CHI publications on human-AI collaboration interfaces. Co-developer of the influential AI Explainability 360 open-source toolkit (JMLR 2020) Key contributor to Uncertainty Quantification 360 framework Active participant in ACM FAccT conferences on AI fairness Principal investigator on multiple Chinese national research grants for AI applications Zhang leads research teams developing practical AI solutions for Chinese industry challenges, particularly in transportation optimization and agricultural technology. His lab maintains strong industry partnerships with Chinese railway authorities and agricultural technology firms, focusing on implementing AI systems that address specific local infrastructure and productivity challenges while maintaining rigorous academic standards.

Shane Wangمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Online Word-of-Mouth Analysis
• +۴ مورد دیگر

Shane Wang is a Professor of Marketing at the Pamplin College of Business, Virginia Tech. He holds editorial roles as Associate Editor at the Journal of the Academy of Marketing Science , Senior Editor at Production and Operations Management , and serves on editorial boards of Journal of Marketing , Journal of Marketing Research , and others. His research focuses on AI-driven marketing strategies, unstructured data analysis, fintech, and statistical methods in consumer research. Education: Ph.D. in Business Admin (University of Cincinnati), M.S. in Statistics (Georgetown University), B.S. in Mathematics (University of Toulouse). Research interests include mapping competitors’ strategic positions in consumer perception, blockchain applications in marketing, and advanced methodologies like mediation and meta-analysis. His work appears in top journals such as Marketing Science , Journal of Consumer Research , and Management Science . Awarded the 2021 Marketing Science Institute Young Scholar distinction. Provides executive education globally (English, Chinese, French) and advises multinational corporations across finance, pharma, and government sectors. Prior to Virginia Tech, he was the Kraft Associate Professor of Marketing at Ivey Business School, Western University, Canada.

Melinda Gann Hallمشاهده پروفایل

استاد

• Judicial Politics
• State Politics
• Judicial Elections
• +۳ مورد دیگر

Melinda Gann Hall is a Professor of Political Science at Michigan State University (MSU) and a Faculty Affiliate with the MSU College of Law. She holds the Distinguished Faculty Award from MSU and the 2016 Career Achievement Award from the American Political Science Association (APSA) for contributions to state politics research. Her expertise spans judicial politics, state supreme courts, and judicial elections, with a focus on campaign advertising and electoral dynamics. Hall earned her Ph.D. from the University of New Orleans in 1983 and joined MSU in 1996. Her research explores the intersection of politics and law, including the impact of attack advertising, voter behavior in judicial elections, and judicial independence. She has authored and co-authored influential books such as In Defense of Judicial Elections and Attacking Judges: How Campaign Advertising Influences State Supreme Court Elections , which won the 2015 APSA C. Herman Pritchett Award. Her articles analyze topics like ballot design effects, televised ad strategies, and the implications of term limits on judicial decisions. Key publications include works in the American Political Science Review , American Journal of Political Science , and State Politics & Policy Quarterly . Hall’s awards reflect her scholarly impact, including the recognition of her lifetime contributions to state politics research. She has collaborated extensively with scholars like Chris W. Bonneau on projects such as the State Supreme Court Data Project, providing foundational datasets for comparative judicial studies.

Yasin Alanمشاهده پروفایل

استاد

• Retail Operations
• Supply Chain Management
• Airline Operations
• +۳ مورد دیگر

Yasin Alan is a Professor at Vanderbilt University's Owen Graduate School of Management, specializing in Operations Management & Quantitative Methods. His research bridges operational decisions and financial outcomes across retail, supply chains, and airline industries. He holds a Ph.D. and M.Sc. in Production and Operations Management from Cornell University (2012), with prior degrees from Texas A&M and Cornell in Engineering and Operations Research. Research focuses on strategic interactions between retailers and manufacturers, airline financial resilience, and inventory-productivity linkages with stock returns. His interdisciplinary work employs methods from operations management, finance, marketing, and economics. Teaching includes Operations Management and Supply Chain Management in the MBA program. Awards include Dean’s Teaching and Research Productivity Awards (Owen School), Meritorious/Distinguished Service Awards (Management Science), and recognition as one of the 40 Best Business Professors Under 40 (2018). His work appears in top journals like Management Science and Manufacturing & Service Operations Management .

Julia Aglionbyمشاهده پروفایل

استاد

• Common Property Resources Governance
• Legal Pluralism
• Upland Ecosystem Management
• +۴ مورد دیگر

Julia Aglionby is a Professor in Practice at the University of Cumbria’s Centre for National Parks and Protected Areas. Her roles include Executive Director of the Foundation for Common Land (until 2023), Chair of the Uplands Alliance (until 2023), and Board Member of Natural England (2014–2019). She is a Chartered Surveyor specializing in England’s uplands and common land governance, with significant experience in environmental economics and policy in Indonesia and the Philippines. Education: MA(Oxon) in Pure and Applied Biology from Somerville College, Oxford MSc in Environment and Natural Resource Economics from University College London PhD in Law from Newcastle University on 'Governance of Common Land in National Parks' Diploma in Rural Practice Surveying from the College of Estate Management Research Focus: Dr. Aglionby’s work centers on legal pluralism in commons governance, upland ecosystem management, and environmental policy development. She explores how traditional practices and modern legal frameworks can coexist in protected landscapes, with particular emphasis on Indonesia’s Danau Sentarum National Park and England’s upland regions. Her interdisciplinary approach combines legal analysis, economic modeling, and stakeholder engagement. Publications Overview: Her work spans 30 years of research, with recent focus on legal governance of protected areas, rewilding strategies, and community-based conservation. Key themes include traffic regulation in national parks, three-compartment land use models, and historical conservation challenges in tropical environments. Advising & Grants: Supervises PhD/MSc students in commons governance and upland management. Her advisory roles include the Uplands Working Group for Natural England and farm management at Susan’s Farm CIO, a care farm where she applies practical conservation principles. Current Affiliations: Trustee of Susan’s Farm CIO, active in organic pasture management and care farm operations. Lives in the Eden Valley, Cumbria.

• Operations Research
• Analytics
• Behavioral Economics
• +۵ مورد دیگر

Jussi Keppo is the Provost's Chair Professor and Head of the Department of Analytics & Operations at the NUS Business School, as well as Research Director at the Institute of Operations Research and Analytics at the National University of Singapore. His research focuses on operations research, decision analytics, behavioral economics, and their applications in finance, healthcare, and technology-driven markets. He holds a prominent role in shaping strategic academic initiatives and interdisciplinary research collaborations. Key research areas include crowdfunding mechanisms, supply chain optimization, risk management in financial systems, and AI-driven solutions for healthcare and logistics. His work bridges theoretical models with real-world applications, addressing challenges such as labor dynamics in gig economies and behavioral decision-making in transportation systems. Recent publications explore topics ranging from 3D generative AI to regulatory impacts on banking risk-taking. Keppo’s interdisciplinary approach integrates computational methods with economic principles, contributing to advancements in both academic theory and practical industry solutions. His research has been published in top-tier journals across computer science, operations management, and finance disciplines.

• Corporate Governance
• Managerial Compensation
• Corporate Finance
• +۳ مورد دیگر

M.P. Narayanan is the Robert Morrison Hoffer Professor of Business Administration and Professor of Finance at the Ross School of Business, University of Michigan. His research focuses on corporate governance, executive compensation, and managerial behavior. He holds a PhD from Northwestern University (1983), ME from Indian Institute of Science (1971), and BE from University of Madras (1969). Education: PhD in Finance, Northwestern University (1983) ME in Engineering, Indian Institute of Science (1971) BE in Engineering, University of Madras (1969) His research explores corporate governance mechanisms, including executive option backdating, managerial decision horizons, and capital allocation inefficiencies in conglomerates. Collaborations with Nejat Seyhun have exposed systemic issues in executive compensation practices. His work on corporate diversification patterns and managerial myopia bridges theory and real-world corporate strategy. Recent publications analyze gender disparities in executive information access, retirement plan structures, and regulatory implications of firm size. His 2012 paper on executive option backdating remains influential in corporate governance discourse. No scientific awards explicitly listed, though his work has significant academic impact. No advising/grants information provided. Research is anchored in the Ross School of Business, focusing on organizational performance and regulatory frameworks.

Scott Moatsمشاهده پروفایل

استاد مدعو

• Higher Education Administration
• Data Analytics in Education
• Educational Leadership
• +۳ مورد دیگر

Overview Scott Moats is an Adjunct Professor in the Graduate School at Bethel University, specializing in Higher Education Leadership and K-12 Administration programs. With 34 years in Christian Higher Education, he has held roles in teaching, administration, and operations. His academic background includes a B.A. from the University of Nebraska, M.Div. from Alliance Theological Seminary, multiple degrees from the University of Minnesota, and an MBA from Crown College. Research & Expertise His research focuses on Higher Education Administration, Data Analytics in Education, and Student Persistence strategies. Notable works include Best Practices in First Year Experiences (2022) and See Me, Hear Me (2018), addressing student success and campus inclusivity. He has also contributed to sociological studies on social distance measurement and faith-based service learning initiatives. Teaching & Service Moats teaches courses like Strategic Leadership in Higher Education and Budgeting & Finance. He has delivered over 30 presentations since 1998, covering topics from faith integration to data-driven decision-making. His professional certifications include a Minnesota Teaching License and ordination. Personal He resides in Minnesota with his wife Sheryl and has two grown children. Beyond academia, he enjoys traveling and reflects his philosophy through the quote: 'To Act Justly and to love mercy and to walk humbly with God.'