جست‌وجوی استاد و پژوهشگر

Jiri Chodمشاهده پروفایل

استاد

• Operations Management
• Industrial Organization
• Corporate Finance
• +۵ مورد دیگر

Jiří Chod , the Ferrante Family Professor and Chairperson at Boston College , is a leading scholar in operations management, industrial organization, and corporate finance. His work explores blockchain technology applications in finance, corporate governance, and supply chain management. Education: MS from University of Economics, Prague; PhD from University of Rochester Teaching: Undergraduate and graduate courses in operations management, economics, and data analytics His research focuses on blockchain technology , smart contracts , and supply chain transparency , with recent publications analyzing cryptocurrency competition, platform tokenization, and ICO dynamics. Articles appear in Journal of Financial Economics , Management Science , and Operations Research . Scientific appointments include: Associate Editor, Management Science (2019–Present) Senior Editor, Production and Operations Management (2010–2020) Associate Editor, Manufacturing & Service Operations Management (2012–2015)

José E. Figueroa-Lópezمشاهده پروفایل

استاد

• Statistics
• Mathematical Finance
• Probability Theory
• +۳ مورد دیگر

José E. Figueroa-López is a Professor of Statistics and Data Science at Washington University in St. Louis , serving as Associate Chair of the department and Director of Graduate Studies. He holds a PhD from the Georgia Institute of Technology . His research focuses on Statistics, Mathematical Finance, and Probability , including high-frequency data inference, nonparametric methods, stochastic processes, and algorithmic trading. His work is funded by multiple NSF grants, such as 'Systemic Shock Inference for High-Frequency Data' (DMS-2413557, 2024–2027). Notable awards include the Guido L. Weiss Teaching Award (2020) and Purdue University Faculty Scholar (2014) . He has led NSF-funded projects on nonparametric methods, Levy models, and portfolio optimization since 2009. His academic leadership includes overseeing graduate programs and advancing research in stochastic control and financial mathematics.

Hanqing Jinمشاهده پروفایل

دانشیار

• Mathematical Finance
• Stochastic Analysis
• Portfolio Optimization
• +۳ مورد دیگر

Dr. Hanqing Jin is an Associate Professor in the Mathematical Institute at the University of Oxford, specializing in Mathematical Finance and Applied Stochastic Analysis. His research focuses on investor decision-making under non-utility behavior, dynamic portfolio optimization, and stochastic control problems in financial markets. Prior to Oxford, he held an Assistant Professorship at the National University of Singapore. He has contributed to foundational work on mean-variance portfolio selection, behavioral finance, and the application of stochastic processes to financial modeling. His academic background includes extensive work on continuous-time portfolio optimization, risk management frameworks, and the intersection of behavioral economics with quantitative finance. Notable contributions include studies on optimal lockdown policies during pandemics, blockchain consensus algorithms analysis, and the development of novel biomarker detection techniques using Raman spectroscopy. Dr. Jin's research integrates advanced mathematical techniques with real-world financial challenges, bridging theoretical models with practical applications in areas such as robo-advising systems and cryptocurrency frameworks. His work on transaction cost analysis and dynamic mean-variance strategies has been widely cited in both academic and industry contexts.

Yan Wangمشاهده پروفایل

استاد

• Trust Management
• Recommender Systems
• Social Networks
• +۷ مورد دیگر

Yan Wang is a Full Professor in the School of Computing at Macquarie University, Australia. He obtained his PhD from Harbin Institute of Technology (HIT), China, and has been at Macquarie since 2003 following a postdoctoral fellowship at the National University of Singapore. His research focuses on trust management, recommender systems, social networks, and services computing, with a strong emphasis on applications in cyber security and data analytics. Wang has published extensively in top-tier venues like AAAI, IJCAI, and IEEE Transactions, and has led over 25 research projects, including current initiatives like Trust-Oriented Data Analytics in Online Social Networks (DP230100676) and Combating Fake News on Social Media (2020–2023). He has received prestigious awards such as the IEEE TCSVC Outstanding Service Award (2017) and the Vice-Chancellor’s Excellence in Research Supervision Award (2014). He serves on editorial boards of journals like IEEE Transactions on Services Computing and has organized major conferences including IEEE ATC2013 and IEEE CLOUD2017. His work bridges theoretical advancements in machine learning and practical challenges in social computing, edge computing, and federated learning. Affiliations: School of Computing, Data Horizons Research Centre, Frontier AI Research Centre Key Projects: Trust-Oriented Data Analytics in Online Social Networks (2023–2026) Combating Fake News on Social Media (2020–2023) Research Themes: Recommender systems, graph learning, fake news detection, and trust management in distributed systems. Wang’s recent work explores causal representation learning, cross-domain recommendations, and privacy-preserving techniques in edge computing environments.

Andrea Waltherمشاهده پروفایل

استاد

• Nonlinear Optimization
• Algorithmic Differentiation
• Mathematical Optimization
• +۳ مورد دیگر

Andrea Walther is a Professor of Mathematical Optimization at the Humboldt University of Berlin, holding a position within the Faculty of Mathematics and Natural Sciences. She leads the Mathematical Optimization research group at the Institute of Mathematics, focusing on algorithmic differentiation, nonlinear optimization, and applied mathematics. Her academic journey includes a Diploma in Business Mathematics (1996, University of Bayreuth), a PhD (1999, TU Dresden), and habilitation (2008, TU Dresden). She has held roles such as Junior Professor at TU Dresden (2007–2008) and Professor at the University of Paderborn (2009–2019) before joining Humboldt in 2019 as a MATH+ Professor. Education : 1991–1996: Studies in Business Mathematics, University of Bayreuth 1996: Diploma in Business Mathematics, University of Bayreuth 1999: PhD in Mathematics, TU Dresden 2008: Habilitation, TU Dresden Her research interests center on optimization methods, particularly algorithmic differentiation (e.g., ADOL-C software), nonsmooth optimization, and applications in engineering and machine learning. She leads initiatives like the Cluster of Excellence MATH+ and contributes to projects such as the Transregio 154. Key Projects: Co-PI of DFG Project 'Mixed-integer non-smooth optimization for gas market problems' (2020–2022) Principal Investigator in MATH+ Projects (EF3-7, AA2-7) Co-developer of ADOL-C, a widely used tool for algorithmic differentiation Notable awards include being a SIAM Fellow. Her work bridges theoretical advancements and practical applications, with contributions to energy sector optimization, inverse problems, and computational frameworks for solving complex systems.

Marc Paolellaمشاهده پروفایل

استاد

• Financial Econometrics
• Time Series Analysis
• Portfolio Optimization
• +۴ مورد دیگر

Marc Paolella is a Full Professor of Empirical Finance at the University of Zurich's Department of Finance. His academic journey includes roles as Associate Professor (2003–2006) and Assistant Professor (1999–2003) at Kiel University and visiting positions at the University of Geneva. He holds a Dr. sc. pol. (1998) and Habilitation (2002) from Kiel University, alongside degrees from SUNY Stony Brook and Colorado State University. His research focuses on financial econometrics, emphasizing portfolio optimization, risk prediction, and saddlepoint approximation theory. He has authored four textbooks, including works on probability theory, statistical inference, and GARCH models. Over 50 journal articles span leading venues like the Journal of Econometrics and Journal of Financial Econometrics. Paolella's contributions include developing methods like CHICAGO for portfolio risk calculation and the COMFORT model for non-Gaussian returns. He serves as Editor-in-Chief of the journal Econometrics and holds editorial roles at multiple journals. Awards include the Elected Fellowship at the IETI and recognition for impactful research. His teaching spans advanced courses in financial econometrics, probability theory, and mathematical finance. He has supervised numerous theses and leads the Quantitative Finance program at the Science ETH UZH. Research grants include Swiss National Science Foundation funding for portfolio optimization under non-elliptical distributions.

• Systemic Risk
• Financial Risk Management
• Credit Scoring
• +۴ مورد دیگر

Christophe Hurlin is a Professor at the University of Orleans specializing in finance, risk management, and econometrics. His research spans systemic risk measurement, credit scoring models, machine learning applications in finance, and computational reproducibility in financial research. With over 30 scholarly publications, he has established himself as a significant contributor to financial econometrics and risk management literature. His primary research interests focus on systemic risk measurement methodologies, credit scoring models incorporating machine learning techniques, and the reproducibility of financial research findings. Hurlin's work often bridges theoretical econometric frameworks with practical financial applications, particularly in banking regulation and risk modeling. He has developed innovative tools such as the Risk Map for validating risk models and has contributed significantly to understanding systemic risk through comprehensive surveys and comparative analyses of risk measures. Hurlin's publication record shows a clear evolution from traditional risk measurement techniques toward integrating machine learning approaches in finance, with recent work focusing on the fairness of credit scoring models, Bayesian approaches to default probability calibration, and the intersection of machine learning with regulatory capital requirements. His research demonstrates consistent engagement with both theoretical underpinnings and practical applications in financial risk management. Hurlin has collaborated extensively with researchers across Europe, particularly with colleagues from HEC Paris (notably Christophe Pérignon), creating a substantial body of work on systemic risk, credit scoring, and computational reproducibility. His most cited works include 'Where the Risks Lie: A Survey on Systemic Risk' and 'Nonstandard Errors,' reflecting his influence in both risk management and methodological research. His research has practical implications for banking regulation, financial stability monitoring, and the implementation of machine learning in credit assessment systems. Through his work on computational reproducibility, Hurlin has also contributed to improving research standards in financial economics, advocating for greater transparency and verification in published findings.

• Financial Economics
• Momentum Investing
• Corporate Bonds
• +۵ مورد دیگر

Valentina Galvani is a Professor and Chair of the Economics Department at the University of Alberta's Faculty of Arts. She holds a Ph.D. in Economics from Purdue University (2005), an MSc in Economics (2003), a Doctoral Degree in Mathematical Finance (2002) from the University of Brescia (Italy), and a Laurea (BS+MS) in Mathematics. Her research focuses on financial markets microstructure, energy economics, and corporate bond markets, with a strong emphasis on momentum investing and data-driven industry collaborations. Dr. Galvani has led MITACS-accelerated research projects with Alberta's banking sector since 2013, applying machine learning and model development to commercial finance challenges. Her early work included foundational contributions to general equilibrium theory in infinite-dimensional asset markets (Lp spaces). She joined the University of Alberta in 2005 and assumed the Chair position in 2022. Her research interests span financial economics, including market-state effects, corporate bond predictability, and energy market dynamics. Recent work addresses geopolitical conflicts' impact on oil markets, U.S. strategic petroleum reserves, and Saudi Arabia's competitive positioning under sanctions. She teaches graduate-level directed research and undergraduate courses in labor economics and personnel economics. Dr. Galvani's MITACS collaborations span 12 consecutive years (2013–2024), reflecting her industry engagement. While no specific awards are listed, her extensive publication record and leadership roles highlight her academic impact. She advises on energy diversification, market liquidity, and policy interventions in financial systems.

• Pension Fund Management
• Mortality Risk Modeling
• Financial Economics
• +۳ مورد دیگر

David Blake is a Professor of Finance and Director of the Pensions Institute at Bayes Business School, City St George's, University of London. He holds a PhD in Financial Economics from the London School of Economics (1986) and has held roles including Director of the Securities Industry Programme at City University and Research Fellowships at London Business School and LSE. His expertise spans pensions economics, retirement income policy, and mortality risk modeling. Education: PhD in Financial Economics, London School of Economics (1986) MSc(Econ) in Monetary Economics, London School of Economics (1978) BSc(Econ) in Economics, London School of Economics (1975) Research Interests: Blake's work focuses on longevity risk, pension fund management, retirement income systems, and the application of actuarial science to financial markets. He co-founded the LifeMetrics Indices to benchmark longevity risk and chairs the Independent Review of Retirement Income (2016). Awards: 2016 Robert I. Mehr Award (Journal of Risk and Insurance) 2011 Robert I. Mehr Award (Journal of Risk and Insurance) 2013 aiCIO's The Professors: Most Influential Academics in Institutional Investing 2012 Pensions Insight Magazine's 50 Most Influential People in Pensions Articles Trends: Blake's recent work addresses longevity risk in capital markets, pandemic mortality impacts, behavioral economics in savings, and systemic risks in financial systems. His research bridges actuarial science, public policy, and financial economics. Labs/Teams: Director of the Pensions Institute, a leading think tank for retirement policy, and collaborator with institutions like the London School of Economics and UBS Pensions Research Centre.

Keith Cuthbertsonمشاهده پروفایل

مدرس

• Fund Management
• Hedge Funds
• Fund Performance
• +۳ مورد دیگر

Keith Cuthbertson is a Special Lecturer at Bayes Business School, City, University of London. He holds a BSc in Physics and Mathematics from the University of Sussex and an MA in Economics from the University of Manchester. His professional experience includes roles at H.M. Treasury, Bank of England, National Institute of Economic and Social Research (NIESR), Imperial College London, and visiting positions at the Federal Reserve Bank (Washington), Freie University (Berlin), and University of Bordeaux. His research focuses on investment fund performance, behavioral finance, and risk management. Key areas include: (1) Measurement and persistence of mutual fund performance, (2) Statistical methods to distinguish skill from luck in fund management, (3) Factor models for portfolio optimization, and (4) Market timing strategies in equity and bond funds. His work emphasizes practical applications for investors and regulators. Recent publications (2016–2023) demonstrate a consistent focus on fund performance analytics, with evolving emphasis on factor models, portfolio size effects, nonparametric methods, and sustainability-linked finance. His research frequently combines academic rigor with practitioner-oriented insights. PhD Supervision: Elisa Pazaj (2015–present): Topics in Financial Markets Niall O'Sullivan (2006–2009): Performance of Mutual Funds Consultancy: Extensive work with Centrica, Towers Perrin, RBS, Department of Energy and Climate Change (DECC), and other financial/government institutions. Focuses on applied finance, derivatives, and risk management solutions.

• Asset Pricing
• Financial Markets
• Fund Management
• +۳ مورد دیگر

Dr. Dirk Nitzsche is an Associate Professor in Finance at Bayes Business School, part of City, University of London. He serves as Course Director for the Quants Masters Programmes and Associate Dean for International Relations. His academic career spans over 25 years, including roles at Imperial College London and Newcastle University. He holds a BA and PhD from the University of Newcastle. Dr. Nitzsche's research focuses on asset pricing, mutual fund performance, and financial markets, with a particular emphasis on European markets. He has authored/co-authored five textbooks, including Derivatives: Theory and Practice and Quantitative Financial Economics . His work examines performance persistence of mutual funds, particularly in the UK and Germany, using advanced statistical methods like bootstrapping and False Discovery Rate analysis. His recent studies highlight persistent skill-driven performance in small portfolios of top-performing UK mutual funds. He has also explored market timing, fund manager skill vs. luck, and carbon portfolio management. His research has attracted media attention and influenced policy discussions on fund transparency and competition. Dr. Nitzsche has supervised students like Pari Thirnchai and contributed to editorial roles at the European Journal of Finance . His work bridges academic rigor and practitioner relevance, addressing both theoretical and applied challenges in finance.

Ali Wanis Ali Elshaariمشاهده پروفایل

دانشیار

• Quantum Photonics
• Topological Photonics
• Quantum Integrated Photonics
• +۷ مورد دیگر

Ali W. Elshaari is an Associate Professor at the Royal Institute of Technology (KTH) in Stockholm, Sweden. He holds a B.S. in Electrical Engineering from the University of Benghazi (2007) and a Ph.D. in photonics from the Rochester Institute of Technology (2011). His postdoctoral research at TU Delft’s Kavli Institute of Nanoscience focused on quantum transport. Currently, he leads the Quantum Nano Photonics Group, pioneering work in topological and quantum integrated photonics to develop high-performance circuits for communication, sensing, and metrology. His research spans hybrid quantum photonics, strain-tunable systems, and superconducting detectors, with applications in quantum communication and quantum materials characterization. Elshaari's research interests include integrating single-photon emitters into CMOS-compatible platforms, exploring quantum phenomena like entanglement and coherence, and developing advanced photonic materials (e.g., hexagonal boron nitride and Cu₂O). He has contributed to on-chip single-photon generation/filtering, strain-tunable photonic circuits, and slow-wave superconducting detectors. His work bridges experimental and theoretical approaches, leveraging imaging techniques and phase retrieval algorithms. Elshaari is an editorial board member for Nature Portfolio - Scientific Reports , Wiley Advanced Quantum Technologies , and EPJ Quantum Technology . He teaches courses in quantum technology, electromagnetism, and optical physics. His funding includes grants from the Wallenberg Foundation, Swedish Research Council, Vinnova, and the European Research Council. His lab actively recruits students for bachelor’s and master’s projects in quantum photonics and nanophotonics.

• Computational Finance
• Financial Optimization
• Portfolio Selection
• +۴ مورد دیگر

Dr. Enrico Schumann is a Research Fellow at the Faculty of Economics, University of Basel, affiliated with the Wilhelm Winternitz Center for Economics (WWZ), specializing in Computational Economics and Finance. Institution: University of Basel School: Faculty of Economics Department: Computational Economics and Finance Position: Research Fellow Email: enrico.schumann@unibas.ch His research focuses on computational methods in finance, particularly optimization techniques, portfolio selection, and risk-reward analysis. He employs heuristic and numerical methods to solve complex financial modeling problems. His recent publications highlight a consistent focus on algorithmic and computational approaches to financial decision-making, including portfolio optimization and risk assessment using advanced numerical techniques. Dr. Schumann has co-authored influential works such as the book Numerical Methods and Optimization in Finance and contributed to edited volumes on dynamic economic modeling. His work bridges finance, operations research, and computational economics. There are no listed scientific awards or honors in the provided text. No information is available about student supervision or grant funding. He is part of a research environment that emphasizes quantitative and computational approaches to economic and financial problems, collaborating with scholars like Manfred Gilli and Dietmar Maringer.

• Statistics
• Machine Learning
• Financial Econometrics
• +۵ مورد دیگر

Jennifer Chan is a Professor in the Statistics Department at the University of Sydney's Faculty of Science. She earned her PhD from the University of New South Wales in 1997 and previously lectured at the University of Hong Kong before joining her current institution in 2006. Her research integrates statistical and machine learning models with applications in finance and insurance, including volatility modeling, Bayesian methods, and neural network applications. Her interdisciplinary research focuses on: Generalized linear mixed models and multivariate volatility measures Machine learning techniques for financial risk assessment Bayesian robustness and portfolio optimization Time-series analysis of cryptocurrencies and equity markets Recent publications demonstrate strong focus on Bayesian models in finance (42% of last 15 papers), machine learning applications (33%), and actuarial science (25%), with emerging emphasis on neural networks for financial forecasting. Awards & Honors: Second prize, Natural Science Award of China's Ministry of Education (2008) National Drug Strategy Research Scholarship (1994-1996) She supervises doctoral candidates working on machine learning applications in finance and insurance. Her international collaborations include institutions in Israel, Japan, Malaysia, and the United States.

Ralf Kellnerمشاهده پروفایل

استاد

• Economics
• Data Science
• Statistics
• +۲ مورد دیگر

Professor Ralf Kellner holds the Chair of Financial Data Analytics at the University of Passau, Faculty of Economics. His work integrates economics, data science, and statistics, focusing on empirical and application-oriented research to explore how statistical learning and AI can uncover insights in data-driven decision-making processes that generate economic value. He also teaches courses such as Deep Learning and Text Analysis in Finance, Financial Data Analytics and Machine Learning, and Scientific Computing with Python. His research examines the intersection of financial markets, statistical learning, and artificial intelligence, with specific interests in modeling adverse financial developments, systemic risks, and analyzing text data via domain-specific language models. Publications highlight collaborations with researchers like D. Rösch and N. Gatzert. Recent publications include work on hybrid service agents, quantile neural networks, default resolution time analysis, Bayesian sovereign bond risk models, and international diversification studies. His methodological approaches span extreme value theory, quantile regression, and multivariate statistical techniques applied to financial and insurance contexts. Contact: ralf.kellner@uni-passau.de