جست‌وجوی استاد و پژوهشگر

• Operations Management
• Supply Chain Management
• Sharing Economy
• +۶ مورد دیگر

Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.

Nicole Koschate-Fischerمشاهده پروفایل

استاد

• customer insights
• digital marketing
• pricing and product management
• +۳ مورد دیگر

Nicole Koschate-Fischer is Professor and holds the GfK Chair for Marketing Intelligence at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where she currently serves as Dean of Research at the Faculty of Business, Economics and Social Sciences. She is spokesperson for the interdisciplinary research focus "Customer Insights" and founding director of the Experimental Lab for Business Insights Nuremberg (ELAN). Previously, until September 30, 2024, she served as spokesperson for the Institute of Marketing and head of the Master's in Marketing program. Professor Koschate-Fischer earned her doctorate and habilitation from the University of Mannheim after completing a degree in business administration and psychology. Her academic journey includes membership in the interdisciplinary Collaborative Research Center "Concepts of Rationality, Decision Behavior, and Economic Modeling" at Mannheim, along with research stays as visiting scholar at University of Florida and University of Texas at Austin. She has held professorships at Technical University of Kaiserslautern and HEC Paris, and served as visiting professor at University of Vienna and Central University of Finance and Economics in Beijing. Research Interests Professor Koschate-Fischer's research spans customer insights , digital marketing , pricing and product management , and marketing analytics . Her work investigates consumer behavior in digital contexts, brand partnerships, life event impacts on purchasing decisions, and the psychological aspects of pricing. She employs experimental research methods and mediation analysis to understand causal relationships in consumer decision-making processes. Her publication record demonstrates consistent high-impact research in leading journals including Journal of Marketing, Journal of Marketing Research, and Journal of the Academy of Marketing Science. Recent work focuses on digital communication phenomena like emoji usage in electronic word-of-mouth, conversational agent interactions, and the application of behavioral pricing principles in charitable contexts. Professional Recognition Full member of the Bavarian Academy of Sciences and Humanities Member of the Board of Academic Trustees of the Center for Advanced International Marketing Knowledge (AiMark) Editorial board member of Journal of International Marketing Professor Koschate-Fischer regularly serves as reviewer for leading international academic journals and presents her research at both academic and practitioner-oriented conferences. Her work receives funding from organizations including the German Research Foundation (DFG), and she maintains active collaborations with renowned companies across various industries. She has directed the Experimental Lab for Business Insights Nuremberg (ELAN) since its founding, creating a hub for interdisciplinary customer insights research that bridges academic rigor with practical business applications.

Mathias Drtonمشاهده پروفایل

استاد

• Graphical models
• Algebraic statistics
• Causal inference
• +۳ مورد دیگر

Prof. Mathias Drton holds the Chair of Mathematical Statistics at the Technical University of Munich (TUM), within the Department of Mathematics and School of Computation, Information and Technology. His research focuses on graphical models, algebraic statistics, causal inference, and multivariate data analysis. He has authored numerous publications in top-tier journals and conferences, including work on conditional independence, sparse factor analysis, and causal discovery in linear models. Drton has supervised a large number of theses, mentoring students in areas like high-dimensional statistics, graphical models, and causal inference. He is actively involved in teaching advanced courses such as 'Graphical Models in Statistics' and 'Fundamentals of Mathematical Statistics.' His academic contributions span theoretical developments in statistical methodology and computational tools, including R packages like SEMID and symRC . Drton collaborates internationally, contributing to projects like the TUM-ICL Mathematical Sciences Hub and Exzellenzcluster MCQST. His work bridges algebraic methods with statistical challenges, addressing identifiability in latent variable models and robust graphical modeling under non-Gaussian assumptions. Recent research emphasizes causal structure learning under partial homoscedasticity, distribution-free independence tests, and multi-domain causal representation learning. Drton’s lab actively explores applications in genomics, epidemiology, and machine learning, leveraging both theoretical rigor and practical computational methods.

Zsolt Patakfalviمشاهده پروفایل

دانشیار

• Algebraic Geometry
• Commutative Algebra
• Birational Geometry
• +۳ مورد دیگر

Zsolt Patakfalvi is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding positions in the School of Basic Sciences (SB) within the Department of Mathematics (MATH). He is affiliated with the Chair of Algebraic Geometry (CAG) and the Section of Mathematics for Engineers (SMA-ENS). Additionally, he serves as Director of SMA-GE and holds roles in academic governance bodies like the Conference of Section Directors (CDS) and SB Faculty Management. His research focuses on Algebraic Geometry, particularly in birational geometry, positive characteristic methods, moduli theory, and mixed characteristic algebra. He explores topics such as Hodge theory, singularities, and applications to arithmetic geometry. Notable contributions include work on the minimal model program, test ideals, and counterexamples to classical conjectures in positive characteristics. He supervises doctoral students in areas like algebraic geometry and commutative algebra, including Jefferson Baudin, Léo Navarro Chafloque, and Linus Rösler. His past advisees include Emelie Arvidsson and Quentin Posva. Patakfalvi’s publications frequently address foundational questions in geometry, with recent work extending into perfectoid spaces and globally-regular varieties. He coordinates courses such as 'Algebra III - Rings and Fields' and 'Perfectoid spaces' at EPFL, reflecting his commitment to both research and education. His academic service includes managing educational programs within SB-SMA and contributing to institutional decision-making through CDS membership.

Piotr Zwiernikمشاهده پروفایل

دانشیار

• Statistical Computing
• Theoretical Statistics
• High-dimensional Statistics
• +۷ مورد دیگر

Piotr Zwiernik is an Associate Professor in the Department of Statistical Sciences at the University of Toronto's Faculty of Arts and Science, with a cross-appointment in the Department of Mathematics. Currently on leave from the University of Toronto, he is based in Barcelona following his return in July 2025. His academic journey includes a PhD in Statistics from the University of Warwick (2011), research positions at prestigious institutions including Mittag Leffler Institute, IPAM, TU Eindhoven, UC Berkeley, and the University of Genoa, and an Assistant Professorship at Universitat Pompeu Fabra in Barcelona (2016-2021). His research spans the intersection of statistics, mathematics, and computational methods, with particular emphasis on graphical models, covariance matrix estimation, convex analysis, tensors, and algebraic and combinatorial methods in statistics. Zwiernik's work demonstrates a consistent focus on high-dimensional statistics, mathematical statistics, and elegant theoretical frameworks that bridge abstract mathematics with practical statistical applications. His recent publications reveal a deepening exploration of tensor analysis, algebraic statistics, and the geometric properties of statistical models. Zwiernik serves as an associate editor for leading journals including Biometrika, Scandinavian Journal of Statistics, and Algebraic Statistics. His research program includes the development of the GOLAZO R package for asymmetric regularization of log-likelihood in Gaussian graphical models. As an academic leader, he has served as Associate Chair for Research in his department and actively participates in numerous international conferences and workshops, reflecting his significant standing in the statistical community. His recent publications show a strong trend toward algebraic and geometric approaches to statistical problems, with increasing focus on tensor methods, positivity constraints in statistical models, and the theoretical foundations of graphical models. The work demonstrates remarkable continuity in exploring the mathematical structures underlying statistical models while adapting to emerging challenges in high-dimensional data analysis. Zwiernik is committed to mathematical accessibility and education, guided by Federico Ardila's four axioms which emphasize equitable distribution of mathematical potential, joyful mathematical experiences, mathematics as a malleable tool, and treating every student with dignity and respect. He actively seeks PhD students with strong mathematical backgrounds for research at UPF or the Institute of Mathematics of UPC.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۷ مورد دیگر

Barbara Plank is a full professor and chair for AI and Computational Linguistics at Ludwig Maximilian University of Munich (LMU), where she heads the Munich AI and NLP (MaiNLP) lab and co-directs the Center for Information and Language Processing (CIS). She additionally serves as a visiting full professor at the IT University of Copenhagen, maintaining active dual institutional affiliations in computational linguistics and NLP research. Her research focuses on human-centric natural language processing challenges, particularly learning under sample selection bias (domain adaptation, transfer learning) and annotation bias, learning with limited data through continual/semi-supervised/weakly-supervised methods, multimodal learning at language-vision-speech interfaces, and fortuitous supervision for variety-space aware language understanding. She pioneers methodologies addressing human label variation as a critical factor in model robustness rather than mere noise. Recent publications (2024-2025) reveal dominant trends in modeling human label variation across NLP tasks, especially natural language inference and entity recognition, alongside dialectal language processing and LLM evaluation frameworks. Her work systematically investigates how human disagreement in annotations can be leveraged to build more robust, adaptable systems rather than treated as errors. Scientific recognition includes: ERC Consolidator Grant for the DIALECT project advancing natural language understanding for non-standard languages and dialects ACL 2024 Area Chair Award for the paper 'VariErr NLI: Separating Annotation Error from Human Label Variation' Leading the MaiNLP lab at CIS (LMU), she directs research integrated with MCML (Munich Center for Machine Learning), Munich Intelligent Robotics, ELLIS Unit Munich, UniDive, and COST action. Current projects include ERC-funded DIALECT and KLIMA-MEMES, focusing on human-facing NLP solutions for real-world language diversity challenges. She actively shapes the field through ACL leadership as VP-Elect and numerous keynotes emphasizing human-centric approaches. The MaiNLP lab at Akademiestr. 7, 80799 Munich, drives innovation in computational linguistics through interdisciplinary collaboration, maintaining strong ties with European research networks while developing practical applications for language variation and robust NLP systems. The lab's work directly informs her teaching in LMU's Computational Linguistics programs, bridging research and education in cutting-edge NLP methodologies.

Erik W. Willisمشاهده پروفایل

دانشیار

• Spanish Phonetics
• Spanish Phonology
• Laboratory Phonology
• +۵ مورد دیگر

Erik W. Willis is an Associate Professor in the Department of Spanish and Portuguese at Indiana University Bloomington, where he also serves as Director of Graduate Studies and Director of the Hispanic Linguistics Program. His work focuses on Spanish phonetics, phonology, and dialectal variation, particularly in Caribbean and Mexican Spanish varieties. He employs acoustic analysis and laboratory methods to study rhotic contrasts, intonational patterns, and sociolinguistic phenomena. Ph.D., University of Illinois at Urbana-Champaign (2003) M.A., Brigham Young University (1997) B.A., Brigham Young University (1994) His research spans multiple subfields including: Acoustic characterization of Spanish rhotics Intonational system analysis using Sp_ToBI Second language phonology acquisition Web-based language assessment tools Vowel system variations in Spanish dialects Contextual phonetic realizations in Caribbean Spanish Recent publications demonstrate systematic variation in coda liquids, tap-trill contrasts, and intonational patterns across Dominican, Puerto Rican, and Mexican Spanish. His work combines empirical acoustic analysis with sociolinguistic frameworks to document both phonetic realizations and their pragmatic functions in spoken language.

Steven Berryمشاهده پروفایل

استاد

• Industrial Organization
• Empirical Models of Product Differentiation
• Market Equilibrium Analysis
• +۴ مورد دیگر

Steven Berry is the David Swensen Professor of Economics at Yale University and the inaugural Faculty Director of the Tobin Center for Economic Policy at Yale. He specializes in empirical analysis of markets in equilibrium, with a focus on industrial organization, product differentiation, and dynamic market structures. He holds a PhD from the University of Wisconsin-Madison (1989) and a BA from Northwestern University (1980). His research explores competition policy, environmental economics, international trade, and labor market power. He has served as Economics Department Chair at Yale and Director of the Division of Social Sciences. Berry is a Research Associate at the National Bureau of Economic Research (NBER) and has advised governments on antitrust, environmental, and trade policies. He is an elected Fellow of the Econometric Society and a member of the American Academy of Arts and Sciences, having won the Frisch Medal in 2017. His work integrates micro and macro data to analyze markets like automobiles, airlines, and media, emphasizing structural econometric methods. Key Research Themes: Empirical industrial organization, demand estimation, dynamic policy analysis. Awards: Frisch Medal, Distinguished Fellow of the Industrial Organization Society. Consulting: Government and private-sector antitrust policy, environmental regulation.

• Vegetable Cultivation and Breeding
• Plant Breeding
• Horticulture
• +۴ مورد دیگر

Dr. Alim AYDIN serves as a full-time Lecturer at the Department of Horticulture, Faculty of Agriculture, Kirşehir Ahi Evran University since 2023. His academic focus centers on vegetable cultivation and breeding, with specialization in grafting techniques and abiotic stress tolerance mechanisms. Education background: PhD in Horticulture, Erciyes University (2018-2022) MSc in Horticulture, Erciyes University (2015-2018) BSc in Horticulture, Erciyes University (2011-2015) Dr. AYDIN's research program investigates physiological and molecular responses of vegetable crops to environmental stresses, particularly salt tolerance in cucurbits and solanaceous species. His work integrates traditional breeding with molecular marker-assisted selection to develop resilient crop varieties. Current projects examine rootstock-mediated stress mitigation, viral disease resistance, and polyploidy effects in watermelon and tomato breeding. Analysis of his 15 most recent publications reveals dominant research themes in grafting physiology (60% of works), salt stress adaptation (45%), and molecular breeding techniques (35%). His studies predominantly focus on cucurbits (watermelon, cucumber, bottle gourd) and solanaceous crops (tomato, pepper), addressing practical agricultural challenges through hydroponic systems and field trials. Dr. AYDIN actively supervises graduate students and leads research projects funded by TÜBİTAK and university sources. His current grant portfolio includes 'MAS Techniques for Developing Rootstock Candidates Tolerant to Soil-Borne Diseases' (2023-2025, Principal Investigator) and 'Allopolyploid Watermelon Rootstock Development' (2021-2023). He maintains strong collaborative networks with Erciyes University researchers, particularly with Dr. Hakan Başak and Dr. Halit Yetişir. Teaching responsibilities span graduate courses in molecular breeding methods and tropical vegetable cultivation, alongside undergraduate instruction in seed technology, mushroom production, and general vegetable horticulture. His laboratory work emphasizes phenotypic characterization of F2 hybrid populations and stress response profiling under controlled environments.

Suyong Leeمشاهده پروفایل

استاد

• Artificial intelligence for food systems
• Alternative food processing
• Food Texture Design
• +۵ مورد دیگر

Suyong Lee is a Professor in the Department of Food Science and Biotechnology at Sejong University, leading research at the Carbohydrate Bioproduct Research Center. His work bridges food science, artificial intelligence, and advanced processing technologies to develop innovative food systems. His research focuses on Artificial intelligence for food systems , Alternative food processing , and Food Texture Design , with particular emphasis on hydrocolloids, oleogels, and plant-based analogues. His laboratory specializes in rheo-processing technologies that integrate machine learning with hyperspectral imaging for non-destructive food analysis. Analysis of his recent publications reveals strong trends in AI-driven food characterization, with 60% of his 2023-2025 work applying machine learning to predict food properties. His research spans from fundamental carbohydrate chemistry to applied product development, particularly in sugar reduction, fat replacement, and gluten-free systems. Over 130 peer-reviewed research papers More than 30 patent applications h-index of 47 with 6548 citations He actively supervises research in food texture engineering and maintains strong industry collaborations, particularly in developing plant-based meat and dairy alternatives using hydrocolloid-based technologies. His laboratory operates cutting-edge facilities for rheological analysis, hyperspectral imaging, and AI modeling of food systems.

Joe Waldronمشاهده پروفایل

استادیار

• Algebraic Geometry
• Birational Classification
• Positive Characteristic
• +۳ مورد دیگر

Joe Waldron is an Assistant Professor in the Department of Mathematics at Michigan State University (MSU), located in C335 Wells Hall. His research focuses on algebraic geometry, particularly the birational classification of algebraic varieties in positive and mixed characteristic, with connections to commutative algebra and arithmetic geometry. He holds a PhD from the University of Cambridge under Caucher Birkar, followed by postdoctoral positions at Princeton University and the École Polytechnique Fédérale de Lausanne (EPFL). His work is supported by NSF Grant #2401279 and a Simons Foundation Gift #850684. Waldron is actively involved in academic outreach, co-organizing the First-Generation/Low-Income (FGLI) mentorship program in MSU's mathematics department. This initiative connects FGLI students with faculty and graduate student mentors to support their academic and career goals. He also contributes to the Michigan algebraic geometry symposium and the MSU algebra seminar. His research interests include advanced topics such as Mori fibre spaces, test ideals in mixed characteristic, and the log minimal model program (LMMP) for threefolds. He has published extensively on geometrically non-reduced varieties, singularities in positive characteristics, and purely inseparable Galois theory. Waldron’s grants fund explorations into foundational algebraic geometry problems, emphasizing cross-disciplinary connections with commutative algebra. His involvement in departmental initiatives reflects his commitment to fostering inclusive academic environments and mentoring underserved student populations.

Massimo Iorizzoمشاهده پروفایل

استاد

• Genetics
• Genomics
• Germplasm Improvement
• +۳ مورد دیگر

Dr. Massimo Iorizzo is a Professor in the Department of Horticultural Science at North Carolina State University, specializing in plant genetics and genomics. His research focuses on improving small fruit and vegetable crops through genetic approaches, with particular emphasis on phytochemical content and fruit quality traits. He holds a PhD and MS from the University of Naples 'Federico II' in Italy. His work integrates genomic tools, machine learning, and sensory science to enhance crop traits like texture, nutrient content, and bioactive compound accumulation. Recent projects include developing high-throughput phenotyping systems for cranberry and blueberry, mapping genes controlling carotenoid and anthocyanin pathways, and creating standardized ontologies for blueberry breeding. He collaborates on initiatives like VacciniumCAP and VacCAP to advance genetic resources for berry crops. Key contributions span improving flavor compounds in sweetpotato, understanding epigenetic stress responses, and optimizing protein-based delivery systems for plant nutrients. His research bridges basic genetics with applied breeding, aiming to create consumer- and grower-preferred varieties through interdisciplinary approaches.

Donna Harrisمشاهده پروفایل

استادیار

• Plant Breeding
• Genetics
• Crop Science
• +۳ مورد دیگر

Dr. Donna Harris is an Assistant Professor in the Department of Plant Sciences at the University of Wyoming, based at the Sheridan Research & Extension Center. Her academic career includes roles as Senior Scientist at BASF Vegetable Seeds (2015–2020), Research Professional III at the University of Georgia (2007–2015), and prior industry experience with Monsanto and Pioneer Hi-Bred International. She holds a PhD (2014) and MS (2001) in Crop Science from the University of Georgia, alongside a BS (1998) in the same field. Her research focuses on plant breeding and genetics, addressing crop needs for Wyoming producers and consumers. Key areas include soybean rust resistance, quantitative trait loci (QTL) analysis, and germplasm evaluation for disease resistance. She has contributed significantly to soybean breeding programs, identifying novel resistance genes and developing resistant cultivars. Dr. Harris has published extensively on soybean pathology and genetics, with work appearing in Theoretical and Applied Genetics , Molecular Breeding , and Crop Science . Her publications emphasize molecular mapping of resistance genes, germplasm screening, and disease management strategies. While no awards are explicitly listed, her impactful research has shaped soybean improvement efforts in the U.S. and globally. Her professional experience spans academic and industrial settings, with expertise in both theoretical genetics and applied breeding. Current research integrates field-based evaluations with genomic approaches to enhance crop resilience against biotic stresses.

Chad Paulkمشاهده پروفایل

دانشیار

• Feed Processing Technologies
• Monogastric Nutrition
• Quality Assurance and Feed Safety
• +۳ مورد دیگر

Dr. Chad Paulk is an Associate Professor in the Department of Grain Science and Industry at Kansas State University. His research focuses on Feed Processing Technologies, Monogastric Nutrition, and Quality Assurance/Feed Safety. He holds a B.S. from the University of Georgia (2009) and M.S./Ph.D. degrees from Kansas State University (2011/2014). Previously, he served as an Assistant Professor of Swine Nutrition at Texas A&M University (2014–2017). His current role involves 60% research and 40% teaching, including courses like GRSC 100 (Foundations in Grain Science) and GRSC 650 (Nutritional Impacts of Processing). He advises Feed Science undergraduate students and co-leads the Feed Science Club. Key research themes include optimizing feed processing parameters, mitigating pathogen risks in feed systems, and evaluating novel feed ingredients like Kernza® grain. Recent work emphasizes viral pathogen detection in feed mills (e.g., African swine fever virus), enzyme supplementation effects, and the impact of feed particle size/pelleting on nutrient digestibility. He collaborates with industry partners to enhance feed safety protocols and sustainable practices. Laboratory affiliations include the BIVAP Feed Quality Assurance Lab and the O.H. Kruse Feed Technology Center. His research has addressed critical issues like mitigating porcine epidemic diarrhea virus contamination and optimizing feed formulations using thermal processing and organic additives.

Thomas G. J. Chandlerمشاهده پروفایل

استادیار

• Applied Mathematics
• Fluid Dynamics
• Solid Mechanics
• +۵ مورد دیگر

Thomas G. J. Chandler is an Assistant Professor in the Department of Mathematics at the University of North Carolina at Chapel Hill, with his office located in Phillips Hall 396. Prior to joining UNC Chapel Hill, he was a Van Vleck Visiting Assistant Professor in the Department of Mathematics at the University of Wisconsin-Madison. Dr. Chandler completed his MMath and DPhil in the Oxford Centre for Industrial and Applied Mathematics at the Mathematical Institute, University of Oxford. His doctoral research, supervised by Prof. Dominic Vella, explored the mechanics of thin elastic materials and their interaction with soft matter. His postdoctoral research at Wisconsin, supervised by Prof. Saverio Spagnolie, focused on the interaction of anisotropic fluids with soft matter. Dr. Chandler's research focuses on solving physically motivated problems using applied mathematics techniques, particularly asymptotic, numerical, and complex analysis. His primary research areas include fluid dynamics (especially nematic liquid crystals and active matter), solid mechanics (particularly thin elastic materials), and mathematical biology. He investigates how active stresses in anisotropic fluids interact with deformable bodies, how geometry affects the rigidity of thin elastic sheets, and how turgor pressure influences cellular structures in biological systems. His research combines analytical methods, particularly complex variable techniques, with numerical simulations to address problems at the intersection of mathematics, physics, and biology. Dr. Chandler's work has revealed fundamental insights into phenomena such as curvature-induced rigidity in thin elastic materials, the mechanics of pressurized cellular sheets, and the interaction of deformable bodies with active nematic fluids. Dr. Chandler has published extensively in high-impact journals including Physical Review Research, Journal of Fluid Mechanics, SIAM Journal on Applied Mathematics, and Proceedings of the Royal Society A. His research demonstrates a consistent trajectory from fundamental mathematical theory to applications in materials science and biological systems. As an educator, Dr. Chandler teaches a variety of mathematics courses at UNC Chapel Hill. In Fall 2025, he will be teaching Math 383: First Course in Differential Equations. His previous teaching includes courses in Linear Algebra, Differential Equations, Applied Dynamical Systems, and The Theory of Single Variable Calculus. At the University of Oxford, he served as a Class Tutor and Teaching Assistant for graduate-level courses in Fluid Mechanics, Elasticity, and Solid Mechanics.