جست‌وجوی استاد و پژوهشگر

Suzanne H. Mitchellمشاهده پروفایل

استاد

• Risky and impulsive decision-making
• Alcohol use disorder
• Neurobiology of choice
• +۲ مورد دیگر

Suzanne H. Mitchell is a tenured Professor at Oregon Health & Science University (OHSU) in the Department of Behavioral Neuroscience, with secondary appointments in Psychiatry and the Oregon Institute for Occupational Health Sciences. She holds a B.Sc. and M.Sc. from the University of Hull, England, and a Ph.D. from SUNY-Stony Brook, USA, where her dissertation examined behavioral economics in rodent foraging decisions. Education: B.Sc./M.Sc. (Hull), Ph.D. (SUNY-Stony Brook) Secondary Appointments: Psychiatry, Oregon Institute for Occupational Health Sciences Her research spans behavioral economics, impulsivity neuroscience, and addiction models , focusing on: Decision-making in substance users Delay discounting mechanisms Energetic cost-benefit analysis Translational rodent-human studies Behavioral genetics of impulsivity Recent publications show expertise in fMRI, behavioral paradigms (e.g., patch depletion tasks) , and genetic models applied to: Alcohol use disorder neurobiology Chronic pain decision-making Neuroplasticity in enriched environments STEM education behavioral influences Scientific contributions include: NIH-funded grants (NHLBI, NIAAA, NIDA, NIMH) Awards for education and mentoring Leadership in behavioral economics societies She collaborates with researchers like Abraham A. Palmer and Jerry B. Richards, applying human/animal models to clinical populations while maintaining active NIH study section participation.

• Supply Chain Management
• Business Analytics
• Operations Research
• +۳ مورد دیگر

João Nuno Gonçalves is a full-time Invited Assistant Professor in Data Science at Universidade Católica Portuguesa (UCP) and a Researcher at CEGE - Research Centre in Management and Economics, Católica Porto Business School. He also holds academic positions at the University of Porto and University of Minho. He earned his PhD in Industrial and Systems Engineering (Business Analytics) from the University of Minho in 2021, following a Master's (1st in class) and Bachelor's in Mathematics (Top 10%). His research focuses on business analytics models for improving supply chain management (SCM), including demand forecasting and sequential decision-making. His work has been recognized with awards such as the Logistics Excellence Award Academy 2022 (APLOG) and multiple pedagogical merit distinctions. He coordinates the BSc in Applied Data Science and serves on the board of the Institute of Computing and Data Science at UCP. Research interests span decision support systems, supply chain optimization, and operations research. He actively contributes to academic success through predictive modeling and has supervised research in warehouse operations and fraud management. He participates in projects like UCP4SUCCESS (2024-2026) and reviews for journals like Computers and Operations Research and Journal of Purchasing and Supply Management . Education: PhD in Industrial and Systems Engineering (2017–2021), University of Minho Master's in Systems Engineering (2015–2017), University of Minho Bachelor's in Mathematics (2012–2015), University of Minho His pedagogical excellence is highlighted by six awards for teaching in Operations Research and Supply Chain Management. Research collaborations extend to logistics, automotive industries, and cybersecurity, emphasizing practical implementation of analytics.

Jeffrey Blumeمشاهده پروفایل

استاد

• Data Science
• Biostatistics
• Statistical Inference
• +۱۷ مورد دیگر

Jeffrey Blume is a tenured Professor of Data Science and Associate Dean for Academic and Faculty Affairs at the University of Virginia's School of Data Science. He previously held leadership roles at Vanderbilt University, including Director of Graduate Education at the Data Science Institute and Vice-Chair of Education in the Department of Biostatistics, with secondary appointments in Biomedical Informatics and Biochemistry. Ph.D. in Biostatistics, Johns Hopkins University B.A. in Statistics, State University of New York at Buffalo His research centers on the philosophical and methodological foundations of statistical inference, with a focus on likelihood-based approaches and evidential reasoning. He has made significant contributions to the development of second-generation p-values and empirical Bayes methods, particularly in biomedical contexts such as cancer diagnostics, nephrology, and neuroimaging. His work integrates rigorous statistical theory with practical applications in radiology, women’s health, and translational medicine. Though specific publications are not listed in the provided text, his research portfolio indicates a strong emphasis on methodological innovation in data science and biostatistics, particularly in areas involving prediction modeling, mediation analysis, ROC analysis, and sequential trial design. These works span both theoretical advancements and real-world applications in clinical and biomedical research. While no scientific awards are explicitly mentioned, his leadership in founding graduate programs in data science and public health underscores his national impact in academic education and program development. Blume has advised numerous graduate students and led major educational initiatives, though specific advisees are not listed. He has secured significant academic grants through his leadership roles and research programs, particularly in data science education and biomedical methodology development. As Associate Dean, he oversees academic and faculty affairs, shaping the strategic direction of the School of Data Science. He is affiliated with the PRISM Lab at the University of Virginia, where his team conducts research on statistical evidence and inference. His website, statisticalevidence.com, serves as a hub for his scholarly work on evidential approaches to data analysis.

Eric Millerمشاهده پروفایل

استاد

• Signal and Image Processing
• Tomographic Image Formation
• Inverse Problems
• +۴ مورد دیگر

Eric Miller is a Professor of Electrical and Computer Engineering at Tufts University's School of Engineering. He also holds adjunct professorships in Computer Science, Biomedical Engineering, and Mathematics. His academic roles include serving as Chair of the Electrical and Computer Engineering department and leading the Lab for Imaging Science Research (LaISR). Miller earned his SB, SM, and PhD in Electrical Engineering from MIT (1990–1994). His research focuses on signal and image processing, particularly inverse problems, tomographic imaging, and applications in medical imaging, environmental monitoring, and security screening. He has pioneered methods like the parametric level-sets (PaLEnTIR) for reconstruction and shape-based inversion algorithms. His work integrates physics-based modeling with computational techniques, addressing challenges in subsurface sensing, biomedical diagnostics, and materials science. Miller is a Fellow of IEEE and a member of honor societies like Tau Beta Pi and Phi Beta Kappa. Over 489 publications reflect his contributions to imaging science, with recent advancements in AI-driven pedestrian behavior analysis and X-ray anomaly detection.

Lan Liمشاهده پروفایل

استاد

• Educational Technology
• Teacher Education
• Online Learning
• +۳ مورد دیگر

Lan Li, Ph.D., serves as Professor and Classroom Technology Program and Endorsement Coordinator at Bowling Green State University's School of Inclusive Teacher Education within the College of Education & Human Development. Based in Education Building 521, she teaches undergraduate and graduate courses focused on technology integration across K-12 educational contexts. Her academic credentials include: Ph.D. from University of Nebraska-Lincoln M.S. from University of Nebraska-Kearney B.A. from ChongQing University Dr. Li's research centers on technology-facilitated teaching , teacher preparation , and online education , with emphasis on peer assessment systems and digital tool implementation. Her work investigates how anonymity affects feedback quality, how structured assessment models enhance learning outcomes, and how digital-native teachers adopt classroom technology through microblogging and Web 2.0 platforms. Analysis of her publication history (2010-2015) reveals consistent focus on peer assessment dynamics across achievement levels, with significant contributions to understanding assessor/assessee role interactions in technology-mediated environments. Her research frequently employs mixed-methods approaches to examine real-world classroom technology integration. Dr. Li actively contributes to academic discourse as reviewer for the British Journal of Educational Technology and Journal of Educational Technology & Society , while serving on scientific committees for international publication series. Her teaching portfolio demonstrates extensive mentorship in technology leadership development through courses like EDTL 6320 and EDTL 6800.

Katherine M. Kinnairdمشاهده پروفایل

دانشیار

• Machine Learning
• Mathematics
• Cultural Analytics
• +۸ مورد دیگر

Katherine M. Kinnaird is an Associate Professor of Computer Science and Statistical & Data Sciences at Smith College, where she chairs the Department of Computer Science. Her research focuses on developing domain-neutral methodologies for representing high-dimensional sequential data in low-dimensional spaces, with applications in music information retrieval, biology, literature, and health care. Education Ph.D. in Mathematics, Dartmouth College (2014) A.M. in Mathematics, Dartmouth College (2010) A.B. in Mathematics, Wellesley College (2008) Her work spans computational approaches to music structure analysis, text analysis, and data science education. Peer-reviewed publications include ISMIR 2016, ISMIR 2017, ISMIR 2019, and TISMIR 2021 papers, emphasizing multi-scale representations, similarity thresholds, and reproducibility in computational music research. Scientific Awards NSF GK-12 Fellowship (2013-2014) Dartmouth Graduate Teaching Award (2013) Dartmouth Graduate Community Service Award (2011) Project NExT Fellow (MAA Red '15 Cohort) Kinnaird founded the Data Science TRAIn Lab to train undergraduates in STEM research and has co-organized initiatives like the Women in Machine Learning (WiML) Workshop (2013) and Women in Music Information Retrieval (WiMIR, 2018). Her teaching philosophy emphasizes active learning and collaborative environments.

Lihua Leiمشاهده پروفایل

استادیار

• High Dimensional Statistical Inference
• Causal Inference
• Econometrics
• +۴ مورد دیگر

Lihua Lei is an Assistant Professor of Economics at Stanford Graduate School of Business (GSB) and holds a courtesy appointment in the Department of Statistics at Stanford University. He earned his Ph.D. in Statistics from UC Berkeley (2019) under advisors Peter Bickel and Michael Jordan, followed by postdoctoral work at Stanford's Statistics Department with Emmanuel Candès. Current affiliations: Stanford GSB, Department of Statistics, and Institute for Economic Policy Research (SIEPR) Previous training: UC Berkeley (Ph.D.), Carnegie Mellon University (undergraduate) His research spans causal inference, conformal inference, and high-dimensional statistics, with a focus on methodology development and theoretical guarantees. Key contributions include adaptive false discovery rate control and conformal prediction frameworks. Recent publications appear in Annals of Statistics , Journal of the Royal Statistical Society , and SIAM Journal on Optimization . Collaborators include prominent researchers like Emmanuel Candès, Michael Jordan, and Peter Bickel. He has received teaching awards as Graduate Student Instructor and develops R packages for methodological implementations including adaptMT and mkn .

• Design for Testability
• Automatic Test Pattern Generation
• Electronic Design Automation
• +۳ مورد دیگر

Haluk Konuk is a Visiting Professor at the Faculty of Engineering, Özyeğin University. With a PhD in Electrical Engineering from the University of California, Santa Cruz (1996), he specializes in VLSI testing, Design for Testability, and Electronic Design Automation. He worked at Hewlett-Packard/Agilent Technologies and Broadcom Corporation for over 25 years, contributing to the development of critical internet infrastructure ASICs and processors. Since 2021, he has founded Palo Alto Test Technologies, focusing on advanced testing solutions. PhD in Electrical Engineering, University of California, Santa Cruz (1996) MS in Electrical Engineering, Case Western Reserve University (1989) BS in Electrical & Electronics Engineering, Boğaziçi University (1986) His research focuses on Design for Testability (DFT), Automatic Test Pattern Generation (ATPG), and Electronic Design Automation (EDA), addressing challenges in VLSI and CMOS circuit testing. His work includes modeling open-defects, fault simulation, and optimizing test efficiency for digital circuits. Haluk Konuk's publications span test compression, delay fault testing, and fault modeling, reflecting his long-term contributions to VLSI test methodologies. He holds 9 U.S. patents and has served on IEEE conference program committees. Fulbright Scholarship 9 U.S. Patents in VLSI Test Technology

Guo Xunhuaمشاهده پروفایل

استاد

• Management Information Systems
• E-commerce
• Social Networks
• +۴ مورد دیگر

Guo Xunhua is a Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management. He serves as Party Branch Secretary and holds significant leadership roles including Executive Director and Secretary-General of the China National Association for Information Technology (CNAIS), Vice President of the China Society of Information Economics, and Secretary-General of the Information Management Committee of the China Management Modernization Research Association. His educational background includes dual bachelor's degrees in Management Information Systems and Computer Science and Technology from Tsinghua University (2000), followed by master's and doctoral degrees in Management Science and Engineering from the same institution (2005). He has been teaching at Tsinghua since 2005 and maintains international academic connections through visiting positions at RWTH Aachen University and MIT Sloan School of Management. Guo's research spans Management Information Systems, E-commerce, Social Networks, and Business Intelligence, with a focus on business intelligence methods in internet environments and behavioral patterns under emerging information technologies. His work integrates both 'technology' and 'behavior' perspectives within information systems research. His recent publications reveal a strong trend toward AI applications in e-commerce, personalized recommendation systems, social commerce dynamics, and the psychological aspects of digital interactions. Ministry of Education Changjiang Scholar Young Scholar (2019) Ministry of Education Outstanding Achievement Award for Scientific Research in Humanities and Social Sciences Beijing Philosophical and Social Sciences Outstanding Achievement Award Beijing Higher Education Teaching Achievement Award Multiple Tsinghua University Teaching Achievement Awards Professor Guo serves as Assistant Editor-in-Chief of the Journal of Information Systems and sits on editorial boards for international journals including Information Technology & People, Electronic Commerce Research, and Journal of Global Information Management. His teaching portfolio includes graduate courses in IT and Organization, and undergraduate courses in Principles of Computer Systems, Management Information Systems, and Introduction to Management Science and Engineering Research.

Arvids Ziedonisمشاهده پروفایل

استاد پژوهشی

• Technology Transfer
• Intellectual Property Law
• University-Industry Collaboration
• +۳ مورد دیگر

Arvids Ziedonis is a Research Professor in the Strategy and Innovation department at Boston University's Questrom School of Business. His work focuses on technology transfer, intellectual property law, and academic entrepreneurship, with a particular emphasis on university-industry collaboration and patent commercialization. His research highlights the role of patent prosecution, licensing strategies, and institutional learning in shaping the commercialization of academic innovations. Collaborations with scholars like David Mowery and Bhaven Sampat have produced influential analyses of university patenting trends before and after the Bayh-Dole Act. Ziedonis has published extensively in journals such as Management Science , Research Policy , and The Journal of Technology Transfer , addressing topics like material transfer agreements, real options in licensing, and the economic value of patents. His work bridges legal, economic, and strategic frameworks to understand innovation ecosystems.

• Information Retrieval
• Data Science
• Quantum-inspired Information Retrieval
• +۲ مورد دیگر

Massimo Melucci serves as Associate Professor of Computer Science at the University of Padua's Department of Information Engineering, maintaining an active research and teaching profile with office location in Building DEI/G, Room 312, Padova, Italy. His instructional responsibilities include undergraduate Information Retrieval and Databases courses, alongside graduate-level Computing Methods for Data Science instruction, complemented by freely available lecture notes on information retrieval fundamentals. His research program centers on two pioneering domains: Quantum-inspired Information Retrieval , where he develops mathematical frameworks applying quantum probability to model contextual relevance and interference effects in search systems, and Algorithmic Fairness , investigating trade-offs between ranking effectiveness and equitable outcomes. These threads converge in his exploration of fairness-effectiveness optimization through eigensystems and variation modeling, while his interdisciplinary work extends into diving medicine neurophysiology , analyzing EEG-based brain connectivity disruptions in professional divers under hyperbaric conditions. Recent publication analysis (2020-2025) reveals three dominant trajectories: quantum-inspired neural architectures for multimodal sentiment analysis, rigorous fairness-effectiveness quantification in ranking algorithms, and biomedical applications of signal processing in extreme environments. He actively fosters academic collaboration through initiatives like the BIRDS workshop series and CIRCLE conference, which bridge information science, retrieval, and data science communities. His work demonstrates consistent innovation in applying non-classical probability models to information access challenges while maintaining strong connections to real-world applications in both search technology and human safety.

• Statistical Power Analysis
• Optimal Experimental Design
• Multilevel Data Analysis
• +۴ مورد دیگر

Mirjam Moerbeek is an Associate Professor at the Department of Methodology and Statistics , Faculty of Social and Behavioural Sciences , Utrecht University , Netherlands. She holds a PhD in Applied Statistics (Maastricht University, 2000) and a MSc in Biometrics (Wageningen Agricultural University, 1996). Her work focuses on statistical power analysis and optimal experimental design for hierarchical and survival data , with over 100 peer-reviewed publications. Education MSc in Biometrics (cum laude), Wageningen Agricultural University (1996) PhD in Statistics, Maastricht University (2000) Research Focus Statistical power analysis Optimal design theory Multilevel modeling Survival analysis Cluster randomized trials Stepped-wedge trials Recent Publications Bayesian sample size determination for longitudinal studies Optimal group sizes in Bayes factor analysis Robustness in cluster randomized trials Cost-efficient designs for social and biomedical sciences Scientific Awards NWO Veni Grant (2003) NWO Vidi Grant (2008) NWO Open Competition Grants (2006, 2022) Ius Promovendi (2023) Organizational Roles President, European Association of Methodology (2023–2025) Vice President, European Association of Methodology (2021–2023) Co-Organizer, International Conference on Multilevel Analysis (2009–2022) Chair, VI European Congress of Methodology (2014) Editorial & Review Activities Editorial Board, PLOS ONE (2014–2017) Peer Reviewer, Tijdschrift voor Psychiatrie Scientific Committee, European Congress of Methodology Consultant for multilevel analysis software

Wolfgang Wörndlمشاهده پروفایل

استاد

• Interactive Recommender Systems
• Mobile Computing
• Tourism Recommender Systems
• +۵ مورد دیگر

Dr. Wolfgang Wörndl is a Professor at the Technical University of Munich (TUM), affiliated with the School of Computation, Information and Technology (CIT) and the Chair of Connected Mobility. His research focuses on interactive recommender systems in mobile scenarios, particularly in tourism applications. Wörndl's research interests span interactive recommender systems, mobile computing, tourism recommender systems, sustainable city trips, and user interaction design. His work addresses challenges in personalization, sustainability, and user experience in mobile recommendation contexts. He has made significant contributions to understanding how to design recommender systems that balance user preferences with environmental considerations in tourism contexts, with recent publications demonstrating a strong focus on sustainable tourism through integration of CO2 emissions, popularity metrics, and seasonal variations into recommendation algorithms. Wörndl actively contributes to the academic community as Workshop & Tutorial Co-Chair for ACM UMAP 2025, Co-Chair for the ACM Europe School on Recommender Systems 2025, and Co-Organizer for multiple workshops including the Workshop on Recommenders in Tourism (RecTour) at ACM RecSys 2025. Best/Outstanding Reviewer at ACM RecSys multiple times As an educator, Wörndl teaches courses including Connected Mobility Basics, Edge Computing and the Internet of Things, and Seminar Human-Centered Recommender Systems. He mentors students through thesis projects focused on user interaction with responsible recommender systems, hybrid user interfaces with agentic AI for travel destination recommendation, and privacy in group recommender systems. His research bridges technical innovation with practical user experience considerations, with several implemented systems including the Green Destination Recommender web application that encourages responsible city trip recommendations through thoughtful interface design.

Alfonso Diz-Lois Palomaresمشاهده پروفایل

پژوهشگر ارشد

• Bayesian Inference
• Spatio-Temporal Modeling
• Environmental Health
• +۳ مورد دیگر

Alfonso Diz-Lois Palomares is a Doctoral Research Fellow at the University of Oslo , affiliated with the Faculty of Mathematics and Natural Sciences and the Statistics and Data Science research group. His work focuses on Bayesian inference, spatio-temporal modeling, environmental health, and epidemiology. Role: Doctoral Research Fellow Institution: University of Oslo Research Group: Statistics and Data Science His research explores the interplay between environmental factors (temperature, air pollution) and public health outcomes, particularly mortality patterns. He employs computational biology and epidemiological modeling to analyze climate-health relationships in Norway and globally. Recent publications highlight collaborations on temperature-related mortality risks , air pollution interactions , COVID-19 transmission dynamics , and vaccination strategy modeling . His methodological work includes sequential Monte Carlo approaches for disease modeling and global climate-health analyses. Current affiliations: University of Oslo , Faculty of Mathematics and Natural Sciences , and Statistics and Data Science research group.

• Applied Economics
• Sustainability and Triple Bottom Line
• Business-to-Business Marketing & Supply-Chain Relationships
• +۴ مورد دیگر

Maria Carmen Padin Fabeiro is a contracted full-time Assistant Professor (Doctor) of Applied Economics at the University of Vigo , where she is affiliated with the Faculty of Commerce and the HI8 ERENEA Research Group on the Economics of Natural and Environmental Resources. Based on the Vigo campus, she has built a prolific research portfolio that bridges economics, marketing, sustainability and tourism studies. Education Ph.D. in Applied Economics, University of Vigo, 2004 Thesis: “Local Endogenous Development: Study of Tourist Activity as a Form of Resource Utilisation – Application to the Case of Baixo Miño” (supervised by Dr. Julio José Pardellas de Blas) Research Interests Padin Fabeiro’s research agenda is organised around three tightly interwoven pillars: Sustainability & Triple Bottom Line: development of frameworks and indices to measure and report sustainable business practices across industries and supply-chain networks. Business-to-Business Marketing & Supply-Chain Relationships: investigation of satisfaction, trust, commitment, conflict and opportunism in long-term manufacturer–supplier relationships. Tourism Economics & Cross-Border Development: economic analysis of tourism as an engine for local endogenous growth, with particular attention to Galicia–Northern Portugal cross-border cooperation. Methodologically, she favours large-scale survey designs, structural equation modelling (PLS-SEM), and comparative case studies that integrate quantitative and qualitative insights. Publication Trends Her 60+ peer-reviewed outputs (2013-2025) reveal a clear evolution from foundational tourism-development studies to sophisticated B2B relationship-quality models and, most recently, to sustainability-oriented health-policy analytics. A recurring pattern is the fusion of economic variables with behavioural constructs such as trust, commitment and satisfaction, applied to contexts ranging from aquaponics systems to COVID-19 policy planning. Scientific Awards No specific awards, fellowships or medals are mentioned in the provided sources. Research Group & Collaborations She is an active member of the HI8 ERENEA Research Group (Economics of Natural and Environmental Resources), where she collaborates on projects that evaluate sustainable business models, stakeholder engagement and cross-border tourism strategies in the Galicia–Northern Portugal Euro-region. Contact Email: padin@uvigo.es