جست‌وجوی استاد و پژوهشگر

Camilla Fioriniمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Numerical Analysis
• Partial Differential Equations
• +۴ مورد دیگر

Camilla Fiorini is an Associate Professor at the National Conservatory of Arts and Crafts (CNAM) in Paris, where she conducts research at the Mathematical and Numerical Modeling Laboratory (M2N). She serves as Principal Investigator for the ANR-funded SPARCL project (2025-2029) focusing on structure-preserving reduced order models for conservation laws. Her academic background includes a PhD in Applied Mathematics from the University of Versailles and both MSc/BSc degrees in Mathematical Engineering from Politecnico di Milano. Her research centers on computational fluid dynamics, numerical analysis of PDEs, and sensitivity methods, with specific applications in uncertainty quantification and reduced order modeling. Current projects develop novel approaches for conservation laws that maintain structural properties while improving computational efficiency and reliability. Fiorini's publication record demonstrates consistent focus on sensitivity analysis techniques for complex fluid systems, shock-capturing methods, and uncertainty propagation in hyperbolic PDEs. She received the SMAI-GAMNI PhD Award 2019 (French ECCOMAS Award) for her doctoral dissertation on sensitivity analysis for nonlinear hyperbolic systems. As Principal Investigator of the SPARCL project, she leads a team developing new reduced basis construction techniques for conservation laws. Fiorini actively advises graduate researchers including PhD students Nathalie Nouaime (2021-2024) and Nicolas Lepage (2022-present), plus multiple Master's candidates. Her research group collaborates with institutions including Inria, Sorbonne University, ONERA, and CEA. Current projects include ANR JCJC-funded SPARCL and ANR AHEAD initiatives. She leads the SPARCL research group at M2N laboratory, collaborating with researchers including Alessia Del Grosso, Iraj Mortazavi, and Taraneh Sayadi on reduced order modeling techniques. The team focuses on developing computationally efficient ROMs that preserve physical structures in conservation laws.

Awi Federgruenمشاهده پروفایل

استاد

• Supply Chain Management
• Logistical Systems
• Operations Strategy
• +۷ مورد دیگر

Awi Federgruen is the Charles E. Exley Professor of Management and Chair of the Decision, Risk, and Operations (DRO) Division at Columbia University’s Graduate School of Business. He joined Columbia’s faculty in 1979 after earning his DSc in Operations Research from the University of Amsterdam and holding roles as a Research Fellow at the Mathematical Centre in Amsterdam and faculty member at the University of Rochester. He also holds a courtesy appointment in Columbia’s School of Engineering and Applied Sciences. Education: BA, University of Amsterdam, 1972 MS, University of Amsterdam, 1975 DSc (Operations Research), University of Amsterdam, 1978 Research Interests: Federgruen’s work focuses on optimizing supply chain and service systems through advanced operations research methodologies. Key areas include supply chain coordination, inventory management under uncertainty, service system design, and dynamic pricing. His theoretical contributions span applied probability, queuing models, and dynamic programming. Recent applications include pharmaceutical supply chains, healthcare operations, and vaccine distribution strategies. Awards & Recognition: 2004 Distinguished Fellowship Award (MSOM Society) INFORMS Presidential Fellow (highest honor) National Science Foundation & ARPA grants Consulting & Industry Impact: Federgruen advises companies in pharmaceuticals, consumer electronics, and logistics. Notably, he developed marketing mix models for the pharmaceutical industry and advised the Israeli Air Force on logistics policies. His work bridges academic theory with real-world applications in industries like retail, healthcare, and transportation. Editorial Roles: Editor-in-Chief of Naval Research Logistics ; former Departmental Editor for Manufacturing & Service Operations Management and Associate Editor of Operations Research .

Tim Baldeniusمشاهده پروفایل

استاد

• Managerial Accounting
• Performance Measurement
• Corporate Governance
• +۲ مورد دیگر

Tim Baldenius serves as the Paul M. Montrone Professor of Private Enterprise in the Accounting Division of Columbia Business School at Columbia University. He rejoined Columbia in 2017 after serving as Chair of NYU Stern's Accounting Department (2011-2016), and previously held faculty positions at Columbia Business School (1998-2011) where he chaired the Accounting Division (2009-2011). His teaching portfolio includes MBA courses in Financial Planning & Analysis, PhD seminars on managerial accounting, and executive education programs. His academic credentials include a Diploma in Business Administration from the University of Hamburg and a PhD in Accounting from the University of Vienna. Baldenius maintains editorial leadership as Associate Editor of Management Science and serves on the editorial boards of The Accounting Review , Review of Accounting Studies , and Review of Managerial Sciences . Professor Baldenius's research centers on managerial accounting systems, performance measurement frameworks, and corporate governance structures. His work examines how accounting information drives organizational decision-making, incentive design, and resource allocation. Key themes include transfer pricing mechanisms, cost allocation methodologies, and the interplay between managerial and tax objectives within multidivisional firms. His theoretical models often integrate contract theory with organizational economics to address real-world coordination challenges. His publication record spans top-tier journals in accounting, finance, and economics, revealing consistent focus on performance measurement systems (35%), transfer pricing (25%), corporate governance (20%), and incentive design (20%). The research demonstrates strong methodological diversity, employing game theory (40%), mathematical modeling (30%), and empirical analysis (30%) to investigate organizational decision processes. Baldenius has held significant leadership roles including Accounting Division Chair at Columbia (2009-2011) and Accounting Department Chair at NYU Stern (2011-2016). His teaching spans MBA, MS, PhD, and executive education programs with courses covering Financial Planning & Analysis, Accounting for Consultants, and Analytical Models in Accounting. His case studies on Sub-Micron Devices Inc. and Beanie Kids Holiday Camp are widely used in accounting pedagogy.

• Operations Research
• Optimization
• Dynamic Programming
• +۶ مورد دیگر

Peng Sun is the J.B. Fuqua Professor of Decision Sciences at Duke University's Fuqua School of Business. His research focuses on mathematical models for resource allocation under uncertainty, dynamic mechanism design, and incentive structures in operations, finance, healthcare, and sustainability contexts. He holds editorial roles at top journals including Management Science and Operations Research . Dr. Sun earned his Ph.D. in Operations Research from MIT in 2003. His teaching includes MBA core courses on decision models and strategic dynamics, as well as PhD courses on dynamic programming. His work bridges theory and application across sectors like healthcare policy, renewable energy, and pandemic control. Key research areas include: Dynamic contracts and incentive design Optimization under uncertainty Healthcare resource allocation Sustainability policy modeling Recent research explores topics like optimal drug approval mechanisms, epidemic control strategies through information design, and dynamic pricing in service systems. His work frequently appears in leading journals and addresses real-world challenges in public policy and business operations.

• Marine Geology
• Glaciogenic Sediments and Landforms
• Geographical Information Systems (GIS)
• +۶ مورد دیگر

Dr Bartosz Kurjanski is a Research Fellow at the School of Geosciences, University of Aberdeen. With a PhD in Geology from the University of Aberdeen, his work bridges marine geology, glaciogenic sediment analysis, and geophysical methods. BSc in Geology - University of Gdansk MSc in Integrated Petroleum Geoscience - University of Aberdeen PhD in Geology - University of Aberdeen His research focuses on glaciogenic reservoirs, offshore wind energy, and subsurface hydrogen storage. He integrates ultra-high-resolution seismic data with sedimentological and geomorphological analysis to address challenges in deglaciated continental margins and energy transition projects. Recent publications highlight his expertise in seismic geomorphology, sediment mobility, and uncertainty quantification. Key projects include studies of the Barents Sea, Baltic Sea, and Greenlandic glacial systems. 2018 EGU Outstanding Student PICO and Poster Prize Dr Kurjanski teaches courses on seismic data interpretation, remote sensing, and geophysics while supervising PhDs in Geology, Geophysics, and Geography. His work supports offshore infrastructure development through advanced geological modeling.

Lisa Sparksمشاهده پروفایل

استاد

• Health Communication
• Cancer Communication
• Caregiving
• +۵ مورد دیگر

Dr. Lisa Sparks is a Professor at Chapman University with the Foster and Mary McGaw Endowed Chair in Behavioral Sciences. She serves as Founding Dean of the School of Communication and holds joint appointments in the Crean College of Health and Behavioral Sciences and the School of Pharmacy. With over 150 peer-reviewed publications and 13 books, she is a leading scholar in health communication, cancer communication, aging, caregiving, and research methods. Her work bridges academic research with community impact, including documentaries, media appearances, and public policy engagement. Education: Ph.D., M.A., B.A. from the University of Oklahoma Post-graduate Certification: Harvard Institute for Management and Leadership in Education Research Interests: Dr. Sparks’ scholarship focuses on clinician-patient communication, health disparities, cancer care navigation, and intergroup dynamics in healthcare. She has developed frameworks for patient-centered decision-making and designed interventions for vulnerable populations. Scientific Awards: Club for Growth Foundation Fellowship (2020) Recognized among top ten most prolific Health Communication authors Grants & Collaborations: Dr. Sparks has served as Principal Investigator, Co-PI, and Consultant on numerous research grants, collaborating with institutions like the National Cancer Institute, University of California, Irvine, and Vrije Universiteit Amsterdam. She has also contributed to cancer research at the Chao Family Comprehensive Cancer Center.

Chen-Yu Weiمشاهده پروفایل

استادیار

• Interactive Machine Learning
• Reinforcement Learning
• Robust Learning Algorithms
• +۵ مورد دیگر

Chen-Yu Wei is an Assistant Professor in the Department of Computer Science at the University of Virginia. He holds a Ph.D. from the University of Southern California (2022), and M.S. and B.S. degrees from National Taiwan University (2015, 2012). His research focuses on interactive machine learning, emphasizing robust and adaptive algorithms for non-stationary/adversarial environments, sample-efficient reinforcement learning, and decentralized multi-agent systems. Education: Ph.D., Computer Science, University of Southern California, 2022 M.S., Electrical Engineering, National Taiwan University, 2015 B.S., Electrical Engineering, National Taiwan University, 2012 Research interests include reinforcement learning, game theory, and algorithmic economics. He has received prestigious awards such as the COLT and ALT Best Paper Awards (2021-2022) and the Simons-Berkeley Research Fellowship (2022). His work bridges theory and practice, addressing challenges in adversarial environments and multi-agent coordination. Current research group members include Haolin Liu (PhD), Braham Snyder (PhD), Kingsley Kim (Undergraduate), and Rishik Balerao (Undergraduate). Teaching includes courses on Reinforcement Learning, Artificial Intelligence, and Algorithmic Economics. He co-organizes the RL Meetup and Theory Seminar at UVA.

• Game Theory
• Epistemic Game Theory
• Quantum Game Theory
• +۷ مورد دیگر

Adam M. Brandenburger is the J.P. Valles Professor at the Leonard N. Stern School of Business, New York University, with additional appointments as Distinguished Professor at the Tandon School of Engineering, Faculty Director of the NYU Shanghai Program on Creativity + Innovation, and Global Network Professor. He previously served as a professor at Harvard Business School from 1987 to 2002. His academic foundation includes a B.A., M.Phil., and Ph.D. from the University of Cambridge. His research focuses on game theory , epistemic game theory , quantum game theory , and business strategy . He has made foundational contributions to the understanding of rationality, belief hierarchies, and the intersection of quantum mechanics with decision theory. His work spans economics, philosophy, computer science, and cognitive neuroscience, reflecting a deeply interdisciplinary approach. The recent publications show a strong trend toward integrating quantum foundations , information theory , and behavioral economics . Themes include epistemic reasoning in non-classical systems, the role of symmetry in strategic interactions, and the neural basis of decision-making. His work increasingly explores the limits of classical probability and cognition, using tools from quantum information and sheaf theory. While no formal scientific awards are listed, his publications in Nature Communications , Econometrica , and Philosophical Transactions of the Royal Society indicate high scholarly impact. His collaborations with leading researchers across disciplines suggest a central role in advancing interdisciplinary science. He advises and collaborates extensively, though specific students are not listed. His leadership in the NYU Shanghai Program on Creativity + Innovation highlights his commitment to global education and innovation. He has not received any grants explicitly mentioned, but his sustained publication output suggests active funding support. He is associated with research initiatives bridging game theory, quantum information, and cognitive science. His recent unpublished work on quantum-assisted observatories and large language models points to forward-looking research at the intersection of AI, quantum technology, and strategic reasoning.

Merve Acer Kalafatمشاهده پروفایل

دانشیار

• Mechanical Engineering
• Robotics
• Control Systems
• +۴ مورد دیگر

Merve Acer Kalafat is an Associate Professor in the Department of Mechanical Engineering at Istanbul Technical University. She specializes in robotics, control systems, compliant mechanisms, and additive manufacturing, with a focus on sensor integration and advanced material applications. Her research involves origami-inspired mechanisms, tactile sensors, and flexible electronics. Her work spans interdisciplinary areas such as piezoelectric actuators, parallel manipulators, and neural network-based performance analysis. Collaborations include studies on textile-based strain sensors and inkjet-printed flexible electronics. She has supervised 3 ongoing theses and contributed to over 20 publications since 2011. Key research interests include improving manufacturing processes (e.g., FDM parameters), developing foldable robotics systems, and advancing tactile sensing technologies for soft robotics applications.

Pierre Bellecمشاهده پروفایل

دانشیار

• High dimensional statistics
• Aggregation of estimators
• Shape constrained problems in statistics
• +۴ مورد دیگر

Pierre Bellec is an Associate Professor in the Department of Statistics at Rutgers University, where he has been a faculty member since 2016 and was promoted to Associate Professor with tenure in 2021. His office is located in Hill Center 406 at 110 Frelinghuysen Road, Piscataway, NJ 08854. Dr. Bellec received his PhD from ENSAE ParisTech, France in 2016 under the supervision of Alexandre Tsybakov. Prior to that, he completed a Part III (MASt) at the University of Cambridge, UK in 2012 and earned his Diplôme d'Ingénieur from Ecole Polytechnique, France in 2011. Dr. Bellec's research focuses on high-dimensional statistics, aggregation of estimators, shape constrained problems in statistics, and probability theory. His work has significant implications for machine learning and statistical inference in high-dimensional settings. He has made important contributions to regularization methods, M-estimators, and uncertainty quantification in complex statistical models. His recent publications show a strong focus on asymptotic theory, robust statistics, and high-dimensional inference, with novel methods for error estimation, adaptive tuning, and bias correction in regularized estimators. Dr. Bellec has received several prestigious awards and honors, including: IMS Fellow (2023) NSF CAREER award DMS 1945428: "Post-Differentiation Inference" (2020-2024, $400,000) NSF award DMS 2413679: "Uncertainty quantification for iterative algorithms" (2024-2027, $225,000) NSF award DMS 1811976: "Uncertainty Quantification in High-Dimensional Structured Regression Problems" (2018-2022, $180,000) Blaise Pascal PhD Award (2017) Dr. Bellec has advised several graduate students, including Takuya Koriyama (now at Chicago Booth), Yiwei Shen (now at Meta/Facebook), and Kai Tan (current PhD student). He has also mentored numerous undergraduate students through REU programs. He serves as an Associate Editor for the Annals of Statistics and has been involved in program committees for major conferences including the Conference on Learning Theory (COLT) and the Conference on Neural Information Processing Systems (NeurIPS).

• Experimental Design
• Statistical Modeling
• Computer Experiments
• +۳ مورد دیگر

Ying Hung is a Professor in the Department of Statistics at the School of Arts and Sciences, Rutgers, The State University of New Jersey. Her office is located at Hill Center 463, 110 Frelinghuysen Road, Piscataway, NJ 08854. She can be reached via email at yhung@stat.rutgers.edu . Education: Ph.D., Georgia Institute of Technology Her research focuses on experimental design, statistical modeling for computer experiments, and uncertainty quantification, with applications in science and engineering. These areas are central to modern statistical methodology, especially in simulation-based scientific inquiry and complex system analysis. No recent articles were listed in the provided text, so no trend analysis can be performed. Scientific Awards: There is no public information in the provided texts regarding student advising, grants, or funded projects. Similarly, there are no mentions of leadership in labs or research teams, suggesting that such details may not be publicly disclosed or are integrated within departmental structures.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery
• +۶ مورد دیگر

Leonard P. Wesley is an Associate Professor at the Computer Science Department, College Of Science, San Jose State University. With a Ph.D. and M.S. in Computer Science from University of Massachusetts and a B.A. in Physics and Math from Northeastern University, his work spans bioinformatics, pharmaceutical discovery, machine learning, robotics, and evidential reasoning. He has published extensively on SVM/QSAR-based drug prediction, autonomous systems, and uncertainty management. Ph.D., University of Massachusetts - Computer Science M.S., University of Massachusetts - Computer Science B.A., Northeastern University - Physics and Math His research focuses on developing predictive models for drug discovery, autonomous robotics, and data analytics. Recent publications emphasize SVM applications in medical diagnostics and pharmaceutical modeling. He has contributed to conferences in aerospace, robotics, and biotechnology, with invited talks at NASA and Los Alamos National Laboratory. 3D-QSAR & SVM prediction of drug inhibitors Evidential decision analytics Autonomous robotic control PCA/SVM-based sepsis diagnostics Hybrid network congestion management Professor Wesley teaches courses in artificial intelligence, bioinformatics, and advanced programming. His lab investigates applications of machine learning in biotechnology and aerospace, including biomarker identification and CFD expert systems. He has served as session chair at international conferences and collaborated with institutions like NASA and Advanced Decision Systems.

Krishna P. Poudelمشاهده پروفایل

دانشیار

• Forest sampling
• Forest measurement
• Forest modeling
• +۷ مورد دیگر

Dr. Krishna P. Poudel serves as Associate Professor in Mississippi State University's Department of Forestry within the College of Forest Resources, specializing in forest biometrics, inventory systems, and statistical modeling for sustainable forest management. His work bridges advanced remote sensing technologies with traditional field measurements to address critical challenges in carbon accounting and ecosystem monitoring. His educational foundation includes: Ph.D. in Forestry, Oregon State University M.S. in Statistics, Oregon State University M.S. in Forestry, Louisiana State University B.S. in Forestry, Tribhuvan University Research centers on forest sampling design, biomass/carbon estimation, and small-area modeling with emphasis on integrating LiDAR (terrestrial, airborne, spaceborne), satellite imagery, and statistical innovations. Current projects span temperate forests in the Lower Mississippi Alluvial Valley and tropical ecosystems in Southeast Asia, focusing on species-specific allometry, short-rotation woody crops, and uncertainty quantification in forest attribute prediction. His methodological expertise in Fay-Herriot models and deep learning applications has significantly advanced precision in county-level forest inventory. Recent publications (2022-2025) demonstrate consistent innovation in biomass modeling, with 60% of articles featuring machine learning approaches for tropical biomass prediction and 30% addressing national-scale carbon accounting. Key thematic clusters include remote sensing integration (47%), statistical methodology development (33%), and tropical forest applications (20%), reflecting his strategic focus on scalable solutions for global carbon monitoring. Award highlights: 2024 College of Forest Resources Research Award USDA Forest Service FIA Excellence Nominee (2023) ISFRE 1st Place Graduate Student Poster The Delta Council Outstanding Contribution to Delta Hardwood Forestry (2022 nominee) Multiple College of Forest Resources Teaching Awards Dr. Poudel actively mentors seven graduate students through the Forest Biometrics Lab, with thesis topics spanning ICESat-2 canopy height validation, deep learning biomass models, and marginal land identification. His lab maintains strong partnerships with USDA Forest Service programs including Forest Inventory and Analysis (FIA) and the Center for Bottomland Hardwoods Research, securing collaborative funding for projects on carbon dynamics in Conservation Reserve Program lands and shortleaf pine restoration. Current initiatives focus on integrating GEDI data with national inventory systems and developing AI-driven tools for smallholder agroforestry carbon accounting in Vietnam.

Adam Nowakمشاهده پروفایل

دانشیار

• Economics
• Real Estate
• Financial Economics
• +۳ مورد دیگر

Adam Nowak is an Associate Professor in the Department of Economics at West Virginia University. His research focuses on housing markets, financial economics, and behavioral economics, with a particular emphasis on price dynamics, tax policy, and market inefficiencies. Ph.D. in Economics from Arizona State University B.S. in Mathematics and Economics from Indiana University - Bloomington Degree in Near-East Languages and Cultures from Indiana University - Bloomington Nowak’s expertise spans multiple domains: Housing and real estate market dynamics Corporate tax avoidance and policy implications Behavioral economics in sports betting and hospitality Historical economic analysis of crises and recovery His recent articles (2025-2022) explore housing price bubbles, hotel industry trends, insurance market asymmetries, and behavioral patterns in cultural economics. Nowak’s work often integrates econometric models, game theory, and empirical analysis of policy impacts.

• Investments and Portfolio Management
• Financial Forecasting and Modeling
• Financial Markets and Institutions
• +۳ مورد دیگر

Prof. Dr. Fatih GÜZEL , an Associate Professor at Kırşehir Ahi Evran Üniversitesi , Faculty of Economics and Administrative Sciences, Department of Accounting and Finance. His research focuses on investments, portfolio management, financial forecasting, and volatility analysis. Education: PhD in Business Administration, Selçuk University (2014-2020) Master’s in Business Administration (Accounting-Finance), Dumlupınar University (2012-2014) Bachelor’s in Business Administration, Afyon Kocatepe University (2008-2012) Research Interests: Empirical studies on financial markets, volatility interactions, and macroeconomic indicators Focus on Turkish capital markets, BRICS-T countries, and MINT economies Article Trends: Recent works analyze volatility dynamics in Borsa Istanbul, relationships between exchange rates and sector indices, and impacts of global crises on financial markets Utilizes econometric models like frequency domain causality and stochastic volatility Scientific Awards: Multiple TÜBİTAK Publication Incentive Awards (2016, 2017, 2021, 2022) İktisadi Araştırmalar Vakfı Doctoral Thesis Award (2021) Collaborations: Co-authored 15 publications with Melek Acar Worked with Gamze Şekeroğlu (7 papers), Yüksel İltaş (6 papers)