جست‌وجوی استاد و پژوهشگر

Brooke A. Gazdagمشاهده پروفایل

دانشیار

• Leadership
• Negotiation
• Diversity and Inclusion
• +۵ مورد دیگر

Brooke A. Gazdag is Associate Professor of Management and Academic Director of Executive Education at Kühne Logistics University (KLU) in Hamburg, Germany. An organizational behavior scholar with a global footprint, she previously held faculty positions at the Technical University of Munich, Ludwig-Maximilians-University Munich, the University of Amsterdam, and visiting appointments in Australia and Israel. Education PhD in Management (Organizational Behavior & Management), State University of New York at Buffalo, 2012 BA Double-Major in Psychology & Spanish, State University of New York at Buffalo, 2008 Study Abroad, University of Seville, Spain, 2006 Research Focus Gazdag’s research integrates leadership, negotiation, diversity & inclusion, resilience, and intercultural communication . She examines how networking behaviors influence leadership emergence, how individuals and teams build negotiation resilience after setbacks, and how organizations can foster inclusive climates that strengthen relationships across demographic fault-lines. Recent projects analyze women’s representation in editorial roles across top management journals, the causal impact of gender-diverse strategic leadership on firm performance, and relational resilience in high-pressure humanitarian operations. Publication Landscape Across 2023-2025 she has produced influential pieces in The Leadership Quarterly, Production and Operations Management, Journal of Management and Harvard Business Review . Collectively, these works advance evidence-based conversations on gender in leadership, methodological rigor in diversity research, and resilient organizing under extreme conditions. Editorial & Scientific Service Editorial Board Member, Journal of Leadership and Organizational Studies Teaching & Executive Development At KLU she designs and delivers graduate and executive courses on Leadership & Organizational Behavior, Cross-Cultural Negotiation, Sustainability-focused Leadership, and Strategic Decision-Making , using blended learning and digital formats to co-create dynamic, values-based learning experiences.

• Agent Technology
• Artificial Intelligence
• Autonomous Driving
• +۹ مورد دیگر

Prof. Dr.-Ing. habil. Dr. hc Sahin Albayrak is a distinguished academic and entrepreneur at the Technical University of Berlin , where he founded and directs the Distributed Artificial Intelligence Laboratory (DAI Laboratory) . He leads the Agent Technologies in Business Applications and Telecommunications research group and serves as founding member of Deutsche Telekom Laboratories (2004) and European Center for ICT (EICT) (2005). As initiator of Connected Living e.V. (2009) and managing director of German-Turkish Advanced Research Center for ICT (2012), he bridges international collaborations. He also founded IOLITE GmbH (2014) and other startups. Research Focus: Agent technology, autonomous driving, smart cities, cyber security, machine learning, and AI applications in energy systems Awards: Federal Cross of Merit (2014), multiple Best Paper Awards Leadership: Director of DAI Laboratory, head of research group at TU Berlin His 20+ recent publications (2022-2025) demonstrate expertise in agent-based architectures , smart mobility solutions , context-aware computing , and AI-driven security systems . Notable trends include integrating large language models into database interfaces, optimizing multi-agent coordination for logistics, and advancing explainable AI through feature attribution frameworks. Scientific Contributions: Recipient of Germany's Bundesverdienstkreuz for German-Turkish cooperation Best Paper Award at Smart Grid Architectures conference

Bella Struminskayaمشاهده پروفایل

دانشیار

• Survey Methodology
• Smartphone Surveys
• Data Donation
• +۶ مورد دیگر

Bella Struminskaya is an Associate Professor at Utrecht University’s Department of Methodology & Statistics, Faculty of Social and Behavioural Sciences. She is also an affiliated researcher at Statistics Netherlands and previously held a senior researcher role at GESIS - Leibniz Institute for the Social Sciences. Her work bridges survey methodology with digital data collection techniques, focusing on smartphone sensors and passive data donation. Education: PhD in Survey Methodology, Utrecht University M.A. in Sociology, University of Mannheim B.A. in Sociology, Novosibirsk State University Her research explores innovative data collection methods, including smartphone surveys, mixed-mode designs, and ethical frameworks for data donation. She investigates how mobile technologies can reduce survey burden while addressing nonresponse bias and measurement errors. Recent work emphasizes integrating digital trace data with traditional surveys to enhance accuracy and scope. Key article trends highlight applications of smartphone sensors in health studies, GDPR compliance for data access, and methodological advancements in smart surveys. Her contributions span technical tools like the Port software and theoretical insights on panel conditioning and ethical data augmentation. Scientific Awards: GOR Thesis Award 2015 She serves as a board member for the German Society for Online Research, Program Chair for the General Online Research Conference (GOR), and holds advisory roles in organizations like the European Social Survey, SHARE ERIC, and ODISSEI. She is an associate editor for multiple journals, including the Journal of Survey Statistics and Methodology and Survey Research Methods.

Philip S Boonstraمشاهده پروفایل

دانشیار

• Bayesian methodologies
• Clinical Trials
• Data integration
• +۳ مورد دیگر

Philip S Boonstra is an Associate Professor with tenure in the Department of Biostatistics at the University of Michigan's School of Public Health. He holds a PhD (2012) and MS (2009) in Biostatistics from the University of Michigan and a BA in Mathematics and Political Science from Calvin College (2006). His office is located in the School of Public Health Tower, where he maintains an active research program. Research Focus: Dr. Boonstra specializes in Bayesian methodologies, clinical trial design, and data integration. His work addresses critical public health questions including: ECMO efficacy for severe COVID-19 patients Safety and efficacy of novel cancer treatments Integration of heterogeneous prediction models Statistical pedagogy for R programming He collaborates extensively with the Extracorporeal Life Support Organization (ELSO) and oncology research teams. Publication Trends: His recent articles demonstrate a strong focus on Bayesian statistical methods applied to clinical challenges. Dominant themes include COVID-19 ECMO outcomes (2021-2024), seamless oncology trial designs (2021), and methodological innovations in Bayesian updating (2020). Cancer research spans lymphoma, prostate cancer, and genetic anticipation in hereditary syndromes. Academic Contributions: Teaches graduate courses including 'Introduction to R Programming' and 'Design and Analysis of Biostatistics Investigations'. Maintains active software repositories for statistical methodologies and contributes to Cross Validated (2.2k reputation). Current projects involve dose optimization frameworks and shrinkage priors for binary data modeling.

Ananda Senمشاهده پروفایل

استاد پژوهشی

• Survival Analysis
• Bayesian Statistics
• Correlated Agreement
• +۳ مورد دیگر

Ananda Sen is a Lee A. Green Collegiate Research Professor in the Department of Biostatistics and a Research Professor in the Department of Family Medicine at the University of Michigan School of Public Health . He has over 180 peer-reviewed publications and is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. Education: PhD in Statistics (University of Wisconsin, 1993), MS and BS from the Indian Statistical Institute (1987, 1985). Dr. Sen specializes in survival analysis (competing risks, recurrent events), Bayesian methods , and correlated agreement with applications in cancer prevention, biomarker research, and genetic/spare data. His collaborative work includes dietary interventions for gastrointestinal cancers, women's health, disability research, and diagnostic testing. His methodological publications focus on Bayesian survival models, competing risks, and correlated agreement measures, while applied works emphasize cancer prevention, nutritional science, and clinical trial design. He served as Director of the NCI-funded Biostatistics Core in GI Cancer Research. Scientific Awards : Teaching Excellence Award (School of Public Health), Fellow (American Statistical Association), Elected Member (International Statistical Institute).

• Transportation Engineering
• Data Science
• Urban Planning
• +۴ مورد دیگر

S. van Cranenburgh is a researcher at the Delft University of Technology in the College of Technology, Policy and Management , specializing in the Transport and Logistics department. Their work bridges transportation engineering, data science, and urban analytics through innovative methodologies in machine learning and spatial-temporal modeling. Research Focus Transportation behavior modeling (e.g., residential location choice). Advanced collision risk prediction using naturalistic driving data. Integration of computer vision and discrete choice models. Psychological impacts of urban noise pollution on health. Proactive risk learning from large-scale driving datasets. Collective perception in historic urban landscapes. Recent Work Trends Their publications from 2025 emphasize deep learning applications in transportation safety (neural networks, contrastive learning), spatial-temporal data analysis , and social media-driven urban dynamics studies. Key themes include data-driven policy modeling and interdisciplinary approaches combining engineering, psychology, and social sciences. Collaborative Engagement Active collaboration with institutions like TU Delft's 4TU.ResearchData. Contributions to open-access datasets and software repositories. Participation in academic workshops and seminars (e.g., 2025 collective perception workshop). Media engagement on urban mobility topics (2016 coverage in Dutch outlets).

Xin Gengمشاهده پروفایل

دانشیار

• Operations Management
• Supply Chain Management
• Game Theory
• +۷ مورد دیگر

Xin Geng is an Associate Professor in the Department of Management at the Miami Herbert Business School, University of Miami. Their research spans operations management, supply chain dynamics, and game theory, with a focus on strategic decision-making in complex systems. Research Interests: Xin's work addresses challenges in supply chain risk mitigation , price competition , and inventory optimization . They also explore human-centered design in extended reality (XR) virtual displays for workplace metaverse applications, alongside algorithmic advancements in congestion prediction for integrated circuit design. Article Trends: Recent publications emphasize exogenous lead times in assemble-to-order systems, strategic postponement in decentralized supply chains, and label-correlation modeling for hardware design. Their studies integrate mathematical rigor with real-world applications in logistics, pricing, and XR technologies. Advising and Grants: While specific advisees are not listed, Xin collaborates with scholars like Huiqi Guan and Nan Yang. Research is supported by grants from the Research Grants Council of Hong Kong and the National Natural Science Foundation of China.

• innovation
• startup ecosystems
• economic security
• +۳ مورد دیگر

Professor Tetyana Oleksandrivna Pozhueva is a distinguished academic at Zaporizhzhia Polytechnic University, serving in the Department of Business and Management within the Faculty of Business Technologies and Economics. With a Doctor of Economics degree and Professor title, she has been actively contributing to the university since 2016. Her academic profile is characterized by dual expertise in Economics and Philology, reflecting her comprehensive educational background and multilingual capabilities. Professor Pozhueva's research centers on innovation, startup ecosystems, economic security, and improving distance education quality. Her work demonstrates how digital technologies transform crisis management and business continuity, with particular attention to economic diagnostics and security frameworks. She has developed methodologies for assessing enterprise competitiveness through ESG criteria and has explored the intersection of educational technology with learning outcomes. Her research consistently addresses practical business challenges while incorporating theoretical frameworks from economic security and strategic management. Her publications reveal a strong focus on contemporary economic challenges, particularly in crisis management, post-war reconstruction, and sustainable development. The recurring themes in her work include economic security diagnostics, digital transformation in business processes, and innovative approaches to educational delivery. Her research has evolved to address Ukraine's specific economic challenges while maintaining international relevance through comparative studies and methodological innovations. Certificate of appreciation for scientific guidance of students in the All-Ukrainian competition of diploma works (2019) Certificate of appreciation for scientific guidance of students in the All-Ukrainian competition of diploma works (2020) Certificate of appreciation for scientific guidance of students in the All-Ukrainian competition of qualification works (2021) Honorary distinction of the Ukrainian Federation of Scientists (2005) Appreciation for preparing winner of All-Ukrainian competition of diploma works (2024) Professor Pozhueva actively mentors students, with multiple recognitions for guiding successful participants in national competitions. She has participated in international educational initiatives, including USAID's DOBRE program and collaborations with Polish institutions. Her involvement in developing educational standards and programs demonstrates her commitment to advancing business education in Ukraine. As a member of the scientific school 'Modern strategy of business entity development as the basis for forming its economic security,' Professor Pozhueva contributes to a research collective that includes four doctors of science and nine candidates of science. Her work bridges theoretical research with practical applications in business management and economic security.

Parminder Singh Kangمشاهده پروفایل

دانشیار

• Supply Chain Management
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Parminder Singh Kang serves as Associate Professor in the Department of Decision Sciences at MacEwan University's School of Business, specializing in supply chain optimization through advanced analytics and machine learning. His cross-disciplinary research integrates people, process, and technology elements to solve complex industrial and service operations challenges. Education: PhD from De Montfort University M.Sc. from De Montfort University Dr. Kang's research centers on applying AI/ML, combinatorial optimization, and simulation modeling to enhance supply chain resilience and customer-centric service systems. His work bridges theoretical frameworks with industry applications, focusing on sustainable digitization, risk profiling, and process improvement through evolutionary algorithms and Lean/Six Sigma methodologies. Recent projects address circular economy integration and Service 4.0 transformation. His publication portfolio reveals strong trends in machine learning applications for supply chain risk analysis, text mining for competency mapping, and digital twin development for customer-centric operations. The research spans theoretical models like HI-TOP to practical case studies on pandemic disruptions and ERP implementation, demonstrating industry-relevant academic contributions. Scientific Awards: Best Paper Award, Administrative Sciences Association of Canada (2018) Horace Pops Medal Award, Wire Cable Conference (2015) Dr. Kang supervises senior student independent studies while teaching business intelligence, machine learning, and supply chain management courses at undergraduate, graduate, and MBA levels. His research is funded by NSERC, MITACS, Alberta Innovates, and industry partners including Fluor Canada, Apana Technologies, and the City of Calgary, supporting projects valued at over $2M annually. He leads collaborative research with Panjab University, CPA Canada, and TATA Steel Europe, focusing on supply chain digitization and process optimization. His work with UK-based SMEs and Canadian organizations drives practical implementation of analytics frameworks in real-world operational environments.

Christos Davatzikosمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Machine Learning
• Neuroimaging
• +۳ مورد دیگر

Christos Davatzikos holds the Wallace T. Miller Sr. Professor of Radiology position and serves as Director of the Center for Biomedical Image Computing and Analytics. His work pioneers the application of advanced computational methods to biomedical imaging, with emphasis on neurological disorders, aging, and multi-organ disease processes. His research portfolio spans: Biomedical Image Analysis and Machine Learning for medical diagnostics Neuroimaging of Alzheimer's disease, psychosis, brain tumors, and small vessel disease Multi-organ integration of imaging with genomics, proteomics, and metabolomics Fairness, reproducibility, and generalizability in healthcare AI systems Development of biological aging clocks through MRI-based biomarkers Analysis of Dr. Davatzikos's 2024-2025 publications reveals a dominant focus on leveraging artificial intelligence to decode disease heterogeneity across organ systems, particularly in the brain. His work demonstrates three critical trends: (1) creation of pan-organ AI endophenotypes that map biological aging through multi-modal data integration, (2) development of fairness-aware decentralized frameworks for healthcare algorithm validation, and (3) translation of neuroimaging biomarkers into clinical tools for early diagnosis of cognitive decline. These efforts consistently emphasize large-scale collaborative validation across diverse populations. No scientific awards are explicitly mentioned in the provided information. As Director of the Center for Biomedical Image Computing and Analytics, Dr. Davatzikos leads interdisciplinary research teams developing computational tools for precision medicine. His work involves extensive collaboration across radiology, neurology, oncology, and computer science departments, though specific advising relationships and grant details are not documented in the source text. The center's focus on synthetic data generation and federated learning indicates strong industry and multi-institutional partnerships. The Center for Biomedical Image Computing and Analytics operates as a hub for developing open-source neuroimaging analysis pipelines, with particular emphasis on pediatric brain tumor segmentation, Alzheimer's disease progression modeling, and cardiovascular-ocular-brain axis characterization. Current initiatives include the Federated Tumor Segmentation (FeTS) challenge and multi-ethnic studies of atherosclerosis-related cognitive decline.

Omar Khadeer Hussainمشاهده پروفایل

دانشیار

• Logistics and Supply Chain Management
• Distributed and Grid Systems
• Decision Support
• +۳ مورد دیگر

Dr. Omar Khadeer Hussain serves as an Associate Professor and Deputy Head of School (Research) at the School of Business, UNSW Canberra. He has been with the School since February 2014, initially working as a Lecturer and Senior Lecturer before his current appointment. Prior to joining UNSW, he worked as a Senior Research Fellow at Curtin University. Dr. Hussain's educational background includes a Bachelor of Technology in Computer Science from JNTU (2002), a Master of Research in Computer Science from La Trobe University (2004), and a Doctor of Philosophy in Information Management from Curtin University (2008). His research focuses on Logistics and Supply Chain Management, with particular emphasis on Supply Chain Risk Management, Distributed and Grid Systems, Decision Support, and Group Support Systems. Dr. Hussain applies these areas to develop knowledge synthesis from data for business applications such as decision making, risk management, cloud service management, new product development, and milk quality management. His work incorporates predictive analytics to enable informed business decision making, with recent research increasingly integrating artificial intelligence and large language models for supply chain risk identification and management. Analysis of Dr. Hussain's recent scholarly output reveals a strong focus on applying cutting-edge AI techniques to supply chain challenges. His work spans systematic literature reviews on supply chain risk modeling, development of frameworks for SLA violation prevention in Cloud of Things environments, and innovative applications of explainable AI in various domains. There is a clear trend toward leveraging large language models for event identification in supply chain risk management and developing dual-sided decision frameworks that integrate multiple stakeholder perspectives. His research bridges theoretical advances with practical applications in logistics and business engineering. Curtin Business School New Researcher of the Year award for 2012 Prize for Early Career Researcher, Curtin Business School (2013) Chancellor's thesis commendation award, Curtin University (2008) Master Prize – Computer Science, La Trobe University (2004) Dr. Hussain has successfully secured multiple competitive research grants, including ARC Linkage Projects on 'Economically Efficient Green Logistics through Cyber Physical Systems' (2016) and 'Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources' (2015), both with Professor Elizabeth Chang as lead CI. He has also supervised 9 PhD students to completion, serving as both main and joint supervisor. While specific lab or team information isn't explicitly mentioned in the available text, Dr. Hussain's research appears to be conducted within the School of Business at UNSW Canberra, likely collaborating with colleagues across business disciplines and computer science to address complex supply chain and logistics challenges through interdisciplinary approaches.

• Supply Chain Management
• Operations Management
• Production Planning
• +۷ مورد دیگر

Fernando Bernstein is a Professor in the Operations Management department at Duke University's Fuqua School of Business . He holds the William and Sue Gross Distinguished Professor of Business Administration title and serves as Associate Dean for Global Initiatives . Ph.D. in Operations Management, 2001, Columbia University Graduate School of Business Licentiate in Mathematics, 1995, University of Buenos Aires His research focuses on supply chain management , retail operations , and game theory applications in production systems. Recent publications explore dynamic assortment personalization , show-up profile modeling , and government regulation impacts on distribution networks. He has served as associate editor for leading journals like Operations Research and Management Science . Excellence in Teaching Award for core MBA course 2008 M&SOM Meritorious Service Award

• Authoritarian Regimes
• Democratic Backsliding
• Quantitative Methods
• +۵ مورد دیگر

Joan C. Timoneda is an Assistant Professor in the Department of Political Science at Purdue University. His research focuses on authoritarian regimes, democratic backsliding, and the application of big data and natural language processing techniques to comparative politics. He received his Ph.D. from the University of Maryland, College Park (2019), MPhil in Latin American Studies from Oxford University (2011), M.A. in Political Science from University of Maryland, College Park, and B.A. from Arizona State University. Ph.D. : Political Science, University of Maryland, College Park (2019) MPhil : Latin American Studies, Oxford University, St Antony's College (2011) M.A. : Political Science, University of Maryland, College Park B.A. : Arizona State University Timoneda's research spans authoritarian regime dynamics, democratic erosion, and computational methods. His book project How Dictators Survive examines institutional personalization in authoritarian regimes using archival work and NLP. He also develops forecasting models for political trends via Twitter and Google Trends, and contributes to methodological advancements in panel data analysis and political text classification. At Purdue, he co-leads the Advanced Methods at Purdue program and teaches courses on political methodology and dictatorship dynamics. Recent publications highlight his work on power personalization, social media's role in democratic subversion, transformer model performance in political science, and economic shocks in authoritarian systems. His projects include detecting racism in Spanish texts, analyzing cabinet formation in dictatorships, and addressing rare events data challenges in logistic regression.

James Emmett Herndonمشاهده پروفایل

استاد

• Cancer Clinical Trials
• Survival Analysis
• Longitudinal Data Analysis
• +۳ مورد دیگر

James Emmett Herndon is a Professor of Biostatistics & Bioinformatics at Duke University and a Member of the Duke Cancer Institute, specializing in statistical methodologies for cancer clinical trials with emphasis on neuro-oncology applications. Education Ph.D., University of North Carolina, Chapel Hill (1988) Research Interests Herndon pioneers biostatistical approaches for cancer trials, focusing on time-dependent covariates in survival models, phase II trial designs minimizing logistical barriers, and longitudinal analysis of quality-of-life data in advanced cancer. His neuro-oncology work addresses critical challenges in brain tumor research through innovative statistical frameworks. Publication Trends With 589 publications, Herndon's recent work (2024-2025) demonstrates dominance in neuro-oncology, integrating machine learning for brain tumor classification, analyzing clinical trial disparities, and developing novel therapeutic strategies for gliomas. Key themes include financial toxicity in brain tumor care, immune-based therapies, and prognostic tool validation. Grants Inflammasomes - a driver of sexual dimorphism to glioma therapies (NIH, 2025-2030) McCain/Bayh Glioblastoma Consortium (DoD, 2025-2029) ATRX mutations, innate immune activation and therapeutic vulnerability in malignant gliomas (NCI, 2022-2027) Enhancing efficacy of Radiation Therapy for brainstem glioma (NCI, 2022-2027) Randomized Phase 2 trial of Lerapolturev for recurrent glioblastoma (2024-2027) Targeting tumor-neural interactions in lung cancer brain metastasis (NIH, 2021-2026) ABL-regulated networks in breast cancer metastases (DoD, 2022-2025) Synergistic microglial activation for GBM response (NINDS, 2021-2025) Genomic analysis of oligodendroglioma (Doris Duke, 2022-2025) Reviving cancer immune surveillance with CD4 T cell help (NCI, 2022-2025) Collaborative Leadership As senior faculty, Herndon mentors junior researchers across Duke Cancer Institute and leads multi-institutional consortia including the McCain/Bayh Glioblastoma Consortium. His grant portfolio demonstrates exceptional collaboration with neurosurgeons, oncologists, and immunologists to translate statistical innovations into clinical impact.

Soheil Sibdariمشاهده پروفایل

استاد

• Business Analytics
• Operations Management
• Logistics
• +۴ مورد دیگر

Dr. Soheil Sibdari is a Professor in the Department of Decision & Information Sciences at the University of Massachusetts Dartmouth's Charlton College of Business. He holds a PhD in Industrial Engineering and an MS in Economics from Virginia Tech, complemented by a BS in Computer Science from Shahid Beheshti University. His teaching expertise includes Business Analytics, Operations Management, and Logistics and Supply Chain Management. Specific courses he teaches include: POM 651: Creating Value Through Operational Analysis POM 682: Technology Management Strategies Professor Sibdari's research spans operations optimization, sustainable supply chains, and decision analytics. His work integrates mathematical modeling with empirical analysis in domains including: Pricing strategies and revenue management Closed-loop supply chain design Risk management in transportation systems Behavioral operations and decision-making Technology adoption impacts His recent publications demonstrate strong focus on sustainability challenges, with research examining carbon taxation effects, green supply chain optimization, and post-pandemic operations strategies. Methodologically, he employs simulation-optimization hybrids, game theory applications, and data-driven decision models.