جست‌وجوی استاد و پژوهشگر

Tayo Obafemi Ajayiمشاهده پروفایل

دانشیار

• Explainable Artificial Intelligence
• Bioinformatics
• Data Mining
• +۴ مورد دیگر

Dr. Tayo Obafemi Ajayi is an Associate Professor in the Department of Electrical and Computer Engineering at Missouri State University, where she holds the Mace/Turblex Professor of Engineering title. She also serves as an Adjunct Professor at Missouri University of Science and Technology and directs the Computational Learning Systems (CLS) Lab. As site coordinator for the Missouri Louis Stokes Alliance for Minority Participation (MoLSAMP), she champions diversity in STEM while leading committees in IEEE organizations like the Bioinformatics and Bioengineering Technical Committee and the Engineering in Medicine and Biology Society. Primary Affiliation: Missouri State University Secondary Affiliation: Missouri University of Science and Technology Labs: Computational Learning Systems Lab Leadership: IEEE Technical Committees, MoLSAMP Her research focuses on Explainable Artificial Intelligence (XAI) for biomedical applications, integrating Data Mining , Machine Learning , and Bioinformatics to address complex health problems. Key projects include: Anemia prediction models for spinal surgery outcomes Alzheimer’s disease severity analysis Autism genotype-phenotype mapping Traumatic brain injury subgroup identification Recent publications span IEEE Access , Frontiers in Human Neuroscience , and the Pacific Symposium on Biocomputing . Her work emphasizes model transparency, statistical rigor, and practical validation through biomedical case studies. Scientific Awards Bear Bridge Outstanding Mentoring Award (2023) IEEE CIBCB Best Student Paper Award (2021) College of Natural and Applied Sciences Faculty Research Award (2019) Dr. Ajayi's research combines Computational Learning with Clinical Applications , securing grants through collaborative projects with institutions like Missouri S&T and participation in national conferences. Her work has been cited over 560 times with an h-index of 14, reflecting sustained impact in AI-driven healthcare solutions.

Dimitrios Diochnosمشاهده پروفایل

استادیار

• Supervised Learning
• Semi-Supervised Learning
• Adversarial Learning
• +۴ مورد دیگر

Dr. Dimitrios Diochnos is an Assistant Professor in the School of Computer Science at the University of Oklahoma (OU) . His research focuses on theoretical and practical aspects of machine learning, including adversarial learning, semi-supervised learning, and imbalanced data classification. Prior to OU, he was a Hobby Postdoctoral Research Fellow at the University of Virginia and a Research Associate at the University of Edinburgh. He holds a PhD in Mathematics from the University of Illinois at Chicago, an MS in Mathematics from the University of Athens, and a BS in Informatics and Telecommunications from the University of Athens. Research Interests: Dr. Diochnos works on foundational aspects of machine learning, particularly under adversarial conditions. His current projects include developing semi-supervised learning techniques, analyzing online/streaming learning algorithms, and exploring theoretical guarantees for imbalanced classification. He is also involved in the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), focusing on trustworthy AI applications in environmental science. Awards and Recognition: He has received NeurIPS Top Reviewer awards (2023, 2019), NSF reviewer status, and the Teaching Award (2009). His postdoctoral fellowship at UVA was supported by the Hobby Endowment. He has held fellowships from the Zossima Brothers Foundation and the University of Illinois at Chicago. Service and Editorial Work: Dr. Diochnos serves as Managing Associate Editor of the Annals of Mathematics and Artificial Intelligence and has been a program committee member for major conferences like NeurIPS, AAAI, and IJCAI. He has organized events such as the Symposium on AI & ML at OU and served on the Scientific Committee for the International Olympiad in Informatics. Grants and Collaborations: His work is supported by NSF grants, including leadership in AI2ES. He collaborates with researchers in meteorology, oceanography, and climate science to address challenges in trustworthy AI for environmental systems. Labs and Affiliations: Dr. Diochnos is affiliated with the OU School of Computer Science and contributes to interdisciplinary initiatives like AI2ES. His research lab focuses on advancing machine learning theory with practical applications in adversarial robustness and environmental forecasting.

• AI and Robotics
• Human-Robot Interaction (HRI)
• Autonomous Agents
• +۷ مورد دیگر

Dr. Abolfazl Zaraki is a Senior Lecturer in AI and Robotics at the University of Hertfordshire's Department of Computer Science, part of the School of Physics, Engineering & Computer Science. He leads the Robotics Research Group and previously held roles at Cardiff University's School of Engineering and the IROHMS Research Centre. His academic journey includes a Master's in Mechatronics from University Technology Malaysia (2010) and a PhD in Automatic Robotic and Bioengineering from the University of Pisa (2014). He has held Research Fellow positions in Italy and the UK until 2019. Dr. Zaraki's research focuses on AI-driven autonomous systems, social robotics, and assistive technologies. Key projects include the EASEL, BabyRobot, and JAMES EU initiatives, alongside the Innovate UK-funded InSight project. His work emphasizes Human-Robot Interaction (HRI), trusted autonomy, and applications in healthcare and industrial contexts. Notable contributions include the development of the Kaspar humanoid robot for autism therapy and advancements in reinforcement learning for robotic control. His recent publications (2021–2025) explore agentic AI, memory-driven systems, and personalized LLMs for HRI, alongside technical advancements in robotic control, communication systems, and bio-inspired robotics. His research bridges theoretical AI innovation with practical applications in healthcare, education, and industrial automation. Zaraki has collaborated internationally across institutions and industry partners, contributing to 35+ research outputs. His work aligns with global trends in ethical AI, explainable systems, and human-centric robotics design.

• Information Systems Development
• Digital Transformation
• Agile Software Development
• +۵ مورد دیگر

Dr. Bartosz Marcinkowski serves as Professor and Head of the Department of Business Informatics at the University of Gdańsk's Faculty of Management, concurrently holding the positions of Deputy Dean for Research and Head of the Doctoral School. His academic leadership spans departmental administration, faculty research strategy, and doctoral program oversight within Poland's prominent management education institution. Marcinkowski's research centers on the intersection of information systems and practical business applications, with dominant focus areas including agile software development methodologies, digital transformation frameworks, and facility management technology adoption. His work consistently addresses contemporary challenges such as post-pandemic recovery in IT projects, generative AI integration, and sustainable business practices through empirical industry-academia collaborations. Recent publications demonstrate particular expertise in scaling agile frameworks for distributed teams and implementing blockchain solutions in enterprise environments. Analysis of his 2022-2025 publications reveals a strategic research trajectory emphasizing practical solutions for complex business-technology challenges. His work shows increasing integration of sustainability considerations across domains, from facility management to corporate governance, while maintaining strong methodological focus on agile approaches and systems integration. The recurring industry-academia collaboration theme highlights his commitment to bridging theoretical research with real-world business applications.

Jatinder Singhمشاهده پروفایل

استاد

• Accountability in AI Systems
• Responsible AI Development
• Data Governance and Stewardship
• +۷ مورد دیگر

Jatinder Singh is a Professor at the RC Trust and Principal Research Associate (equivalent to Research Professor) at the Department of Computer Science & Technology, University of Cambridge. He is primarily affiliated with the University of Duisburg-Essen, Germany, where he leads the Compliant and Accountable Systems research group within the Law department. His work operates at the critical intersection of computer science, legal frameworks, and societal impact, focusing on practical implementations that align technology with regulatory requirements while addressing user and community concerns. Research interests center on accountability mechanisms for AI systems, responsible development practices, data governance, and privacy/security in emerging technologies. He examines governance, agency, trustworthiness, and transparency gaps in algorithmic systems through interdisciplinary socio-technical lenses. Current work addresses bias in LLMs, stakeholder participation frameworks, and human rights implications in domains like healthcare, maritime enforcement, and consumer IoT, emphasizing contextual awareness and real-world applicability. His 15 most recent publications (2025-2024) reveal dominant trends in AI transparency, fairness proxy development, and legal-compliance engineering. Key focus areas include stakeholder involvement in AI governance, bias mitigation in language models, data justice applications for vulnerable populations, and operationalizing human-centered AI in clinical settings. The work consistently bridges technical implementation with regulatory frameworks like the EU Cyber Resilience Act and GDPR. Scientific Awards: No awards or fellowships were mentioned in the provided text. Advising and Grants: The text does not specify PhD/Master's students or grant details. As leader of an active research group publishing high-impact work on EU regulations and human rights, he likely directs funded projects and mentors early-career researchers, though concrete evidence is absent in the source material. His position suggests involvement in interdisciplinary grant consortia addressing socio-technical challenges. Labs and Teams: Singh leads the Compliant and Accountable Systems research group at University of Duisburg-Essen, which collaborates across university-wide clusters including Artificial Intelligence and Society, Human-AI Interaction, Trustworthy Human Language Technologies, and Verification of Machine Learning. The group develops frameworks for legal compliance in AI, focusing on demonstrable accountability through tools for transparency, bias auditing, and stakeholder engagement in real-world deployments.

• Cognitive Science
• Philosophy of Technology
• Digital Ethics
• +۴ مورد دیگر

Anastasia Kozyreva is a Senior Research Scientist at the Max Planck Institute for Human Development, leading the research group Cognition in Online Environments within the Adaptive Rationality Research Area. With a background in philosophy, her work bridges disciplines by integrating conceptual and empirical approaches to analyze the cognitive and ethical impacts of digital technologies on society. Education: PhD (Dr.Phil.) in Philosophy, Heidelberg University (2016) M.Phil in Europhilosophie, Université catholique de Louvain-la-Neuve, Université de Toulouse II, Bergische Universität Wuppertal (2012) Her research focuses on desinformation policy , public attitudes toward content moderation, and cognitive interventions to combat misinformation. Key projects include developing tools for digital resilience and analyzing algorithmic personalization ethics. Recent publications examine misinformation mitigation , digital citizenship , and public trust in technology . These works span psychology, political science, and digital ethics, addressing challenges like online manipulation and democratic integrity. Kozyreva collaborates with interdisciplinary teams and contributes to policy reports, including the 2020 EU publication Technology and Democracy . She co-authored the influential 2020 Psychological Science in the Public Interest paper on cognitive tools for confronting digital challenges.

• Computer Vision
• Medical Image Analysis
• Pattern Recognition
• +۵ مورد دیگر

Jaime S. Cardoso is a prominent researcher at the University of Porto and Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) in Portugal. His extensive publication record spanning two decades demonstrates his leadership in computer vision, medical image analysis, and pattern recognition. His research primarily focuses on applying artificial intelligence to healthcare challenges, particularly in medical imaging and diagnostics. Cardoso's research interests center on explainable AI for medical applications, biometrics, and computer vision. His work bridges the gap between theoretical machine learning and practical medical solutions, with significant contributions to breast cancer diagnosis, medical image segmentation, and biometric security systems. He has developed innovative approaches to medical image analysis, including virtual staining techniques and privacy-preserving explanation methods for medical AI systems. His recent publications (2023-2025) reveal a strong emphasis on explainable AI in medical contexts, with multiple papers addressing how to make deep learning models more transparent and trustworthy for healthcare applications. He has also made significant contributions to face recognition technology, video anomaly detection, and specialized medical imaging techniques for breast cancer and neonatal EEG analysis. Among his scientific contributions are numerous collaborations with researchers across Portugal and internationally. His work has appeared in top-tier journals including IEEE Access, Medical Image Analysis, and Neurocomputing, reflecting the high impact of his research. Cardoso has supervised numerous students who have become established researchers in their own right, including Ricardo P. M. Cruz, Kelwin Fernandes, and Ana Filipa Sequeira. His research group appears to focus on the intersection of deep learning, medical imaging, and biometrics, with strong connections to clinical applications.

Emanuel Vahid Towfighمشاهده پروفایل

استاد

• Public Law
• Constitutional Law
• Empirical Legal Research
• +۷ مورد دیگر

Emanuel Vahid Towfigh is a Professor of Public Law, Empirical Legal Research and Law & Economics at EBS University of Business and Law in Germany. He holds the Chair in Public Law at EBS Law School and is Professor of Law & Economics at EBS Business School. Since October 2024, he serves as a Max Planck Fellow at the Max Planck Institute for Comparative Public Law and International Law in Heidelberg, where he heads the Center for Diversity in Law funded by Stiftung Mercator. He is also Director of the BRYTER Center for Digitalization & Law and supports the EBS Diversity & Refugee Law Clinic. Additionally, he is a Distinguished Scholar in Residence at Peking University's School of Transnational Law and a Research Affiliate at the Max Planck Institute for Research on Collective Goods. Having earned his doctorate from the University of Münster in 2005 with a thesis on religious communities (focusing on the Bahá'í faith), Towfigh completed his habilitation at the same university in 2014 with his work 'The Party Paradox.' His academic journey includes research positions at the Max Planck Institute for Research on Collective Goods (2007-2016), a Global Fellowship at NYU School of Law (2011/12), and a Visiting Professorship at the University of Virginia School of Law (2012/13). He served as Dean of EBS Law School from 2018 to 2020 and has been Vice Dean for Research since 2023. Towfigh's research spans interdisciplinary governance, combining interests in public and constitutional law, democracy theory, religious constitutional law, party law, municipal law, European law, and corporate law. His work employs doctrinal, comparative, economic, and empirical methodologies. His recent publications reflect a strong focus on diversity in law, algorithmic decision-making systems, digitalization's impact on legal frameworks, and the intersection of constitutional principles with contemporary social challenges. The trend in his scholarship shows increasing attention to how legal systems can accommodate diversity while maintaining constitutional principles, with growing emphasis on digital governance and algorithmic fairness. 2005 Dissertation Prize by the University of Münster 2015 Prize for the Promotion of Young Academics by the University Society of Münster Member of Young Academy at Brandenburg Academy of Sciences and Leopoldina (2011-2016) As Co-Editor in Chief of the German Law Journal since 2016 (previously Editor since 2011), Towfigh has significantly shaped scholarly discourse in comparative constitutional law. His leadership extends to directing the BRYTER Center for Digitalization & Law, which focuses on legal education in the digital age and the intersection of law and technology. He also heads the Center for Diversity in Law, examining how legal systems can better address diversity perspectives. Towfigh serves on the supervisory board of Freudenberg SE and as a member of the National Spiritual Assembly of the Bahá'í Community in Germany. His professional memberships include the Vereinigung der Deutschen Staatsrechtslehrer, International Society of Public Law (ICON•S), and Society for Empirical Legal Studies. Through the BRYTER Center, Towfigh has pioneered innovative teaching approaches including 'Legal Engineering' courses and workshops on legal tech automation. His 'Smartbook Fundamental Rights' integrates 67 learning videos with traditional legal education. The Center for Diversity in Law under his direction examines diversity perspectives in legal research, law as an instrument for managing human diversity, and legal pluralism.

Ramin Hasaniمشاهده پروفایل

پژوهشگر

• Machine Learning
• Robotics
• Neural Networks
• +۳ مورد دیگر

Ramin Hasani is a researcher at TU Wien's Cyber-Physical Systems department. He holds a Dr.techn. (Doctor of Engineering) and specializes in machine learning applications for robotics, control systems, and biologically-inspired neural networks. His work focuses on developing interpretable neural architectures like Liquid Time-Constant Networks and Neural Circuit Policies, emphasizing safety and stability in autonomous systems. Hasani's research bridges neural network theory with practical robotics challenges, including autonomous racing, medical data analysis, and adversarial robustness. Key research areas include continuous-time neural networks, formal verification of neural ODEs, and bio-inspired control mechanisms derived from biological neural circuits (e.g., Caenorhabditis elegans). He collaborates extensively with institutions like MIT and ETH Zurich, contributing to projects in health-monitoring systems and end-to-end robot learning frameworks. His publications consistently address real-world challenges such as sepsis prediction via reinforcement learning and robust CNN architectures for image classification. Recent work highlights include developing stable recurrent networks through Gershgorin loss functions and advancing zero-shot transfer learning for autonomous systems. Hasani's interdisciplinary approach integrates principles from neuroscience, control theory, and machine learning to create auditable, high-performance AI solutions for cyber-physical environments.

• Service-Oriented Architectures
• Data Management
• Cloud Computing
• +۵ مورد دیگر

Dimosthenis Kyriazis is a Professor at the University of Piraeus, affiliated with the Research Center. He currently teaches courses such as C Programming, e-Business, and Information Systems. His research focuses on service-oriented architectures, cloud/edge computing, data management, and healthcare informatics. Kyriazis holds a PhD from the National Technical University of Athens (NTUA) and has contributed to EU-funded projects like BigDataStack and CrowdHEALTH, addressing quality of service, workflow management, and IoT applications. He leads research on data management in cloud/edge environments, socially-enhanced IoT management, and big data applications in sectors like finance and e-health. His expertise spans distributed systems, software engineering, and interdisciplinary collaborations with industries and academia. He has participated in EU working groups on Future Internet Architecture and Cloud QoS&SLAs. Kyriazis actively seeks interns and collaborates on initiatives like AI-driven healthcare platforms (iHELP) and sustainable computing practices. His work emphasizes human-centric AI, data interoperability, and ethical AI frameworks such as AI4Gov for transparent governance. Education: Diploma in Electrical and Computer Engineering (NTUA, 2001), MSc in Techno-economics (NTUA/University of Athens/University of Piraeus, 2004), PhD in Service-Oriented Architectures (NTUA, 2007). Key research areas include federated data marketplaces (FAME), healthcare data integration (holistic health records), and AI applications in finance (DeepVaR). His publications address topics like explainable AI (XAI), defect detection in manufacturing, and environmental risk correlation with health. Grants and collaborations involve coordinating EU projects targeting data governance frameworks, energy-efficient mobility data spaces (Mobispaces), and AI for policy-making (e.g., OECD AI policy analysis). His contributions bridge technical innovation with societal impact through sustainable computing and ethical AI practices.

Mohammad Ibahrineمشاهده پروفایل

استاد

• Media Studies
• Digital Transformation
• Social Media Impact
• +۷ مورد دیگر

Mohammed Ibahrine is a Professor in Residence in the Journalism and Strategic Communication Program at Northwestern University in Qatar. He holds a distinguished academic career with previous roles including Professor at the American University of Sharjah (AUS), coordinator of the Innovation and Entrepreneurship Program in AUS's School of Business and Administration, and teaching positions at the University of Hamburg, University of Erfurt (Germany), and Al-Akhawayn University in Morocco. His interdisciplinary research focuses on technology, business, and human interaction across cultural, political, social, and economic contexts. His research interests span media accountability, digital transformation in Arab media, algorithmic transparency, social media's impact on religious practices, and the platformization of news ecosystems. Notable contributions include studies on Moroccan media dynamics, algorithmic fairness, and the domestication of streaming platforms in Gulf states. He has published extensively in journals like Journalism Practice and Online Information Review , with a Google Scholar profile showcasing over three decades of academic output. Ibahrine's work emphasizes critical analysis of media systems in the Middle East, particularly addressing challenges like misinformation, media capture, and the role of digital platforms in socio-political movements. He has advised on telecommunications strategies in Morocco and pioneered courses on innovation in arts and humanities education.

Giancarlo Manziمشاهده پروفایل

دانشیار

• Machine Learning
• Multivariate Statistics
• Bayesian Statistics
• +۵ مورد دیگر

Giancarlo Manzi is an Associate Professor of Statistics at the Department of Methods and Models for Economics, Territory, and Finance, University of Rome La Sapienza. He holds a PhD from the University of Milan-Bicocca and conducted thesis research at the University of Toronto. His career includes roles at the Medical Research Council Biostatistics Unit in Cambridge and the University of Milan. University of Rome La Sapienza (Current) Medical Research Council Biostatistics Unit (Former Researcher) University of Milan (Former Researcher and Associate Professor) University of Milan-Bicocca (PhD) University of Toronto (Thesis collaboration) His research spans Machine Learning , Bayesian Statistics , and Smart Mobility , with a focus on Covid-19 analytics , data visualization , and epidemiological modeling . He integrates Multivariate Statistics with Public Health to address complex challenges in health systems and urban environments. The 15 most recent publications highlight expertise in quantile regression , Bayesian networks , time-series analysis , and smart mobility optimization . His methodological contributions include wavelet analysis, cross-correlation models, and SIRD modeling frameworks applied to pandemic dynamics and bike-sharing systems. Scientific awards and honors are not explicitly mentioned in the provided texts. Giancarlo Manzi has taught at the University of Verona, Catholic University of the Sacred Heart, and Universidad Carlos III in Madrid, maintaining strong ties with Italy's academic institutions.

Federica Riccaمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Network Optimization
• Portfolio Selection
• +۵ مورد دیگر

Federica Ricca is an Associate Professor (SECS-S/06) at the Department of Methods and Models for Economy, Territory and Finance (MEMOTEF) at Sapienza University of Rome. She teaches courses including Project Management, Financial Optimization and Asset Management, and Quantitative Portfolio Selection for Management at the Faculty of Economics. Her academic career includes: Associate Professor at MEMOTEF Department since 2015 Researcher (MAT/09) at the Department of Statistical Sciences, University of Rome 'La Sapienza' from December 30, 2008 to September 30, 2015 Federica Ricca's research focuses on applied mathematics, combinatorial optimization, and network optimization . Her work has significant applications in electoral system mathematics (particularly biproportional seat allocation and electoral districting), service location problems and customer center assignment, and classification problems. She has developed innovative approaches to portfolio selection problems using combinatorial optimization and financial network analysis. Her recent publications demonstrate a strong focus on the intersection of mathematical optimization with practical applications in finance and political systems. She has made significant contributions to portfolio optimization through network approaches, political districting with attention to minority representation, and combinatorial optimization for financial decision-making. Her work bridges theoretical mathematical concepts with real-world applications in finance and electoral systems. Dr. Ricca is actively involved in research projects including: Mathematical Models for Portfolio Selection Problems: Innovative Combinatorial Optimization and Financial Network Analysis Approaches Quantitative models and efficient procedures for territorial partition and aggregation problems with applications in the public and private services sector She maintains regular office hours for student consultations and follows institutional protocols for student communications, requiring students to use their institutional email addresses when contacting her.

• Robot Cooperation
• Human-Robot Interaction
• People Motion Behavior
• +۵ مورد دیگر

Anaís Garrell Zulueta is an Associate Professor at the Polytechnic University of Catalonia (UPC) and a Robotics Researcher at the Institut de Robòtica i Informàtica Industrial (CSIC-UPC) . She serves as Vice-Director of the Mobile Robotics and Intelligent Systems subline and supervises the RAIG - Mobile Robotics and Artificial Intelligence Group . PhD (2013): European Doctorate with highest honors from UPC B.S. in Mathematics (2006) from University of Barcelona Diploma d'Estudis Avançats (DEA) in Control, Vision, and Robotics from UPC Her research focuses on Human-Robot Interaction (HRI) and robot cooperation , particularly in urban environments . Key themes include: Explainable AI for robot transparency Human motion behavior prediction Socially aware navigation systems Collaborative transport robotics Autonomous last-mile delivery systems Cybernetic avatars and societal implications Recent projects (2023-2025) include: TORNADO: Foundation models for robots handling deformable objects HandIA: AI-based rehabilitation tools LENA: Lifelong navigation learning TRIFFID: First responder assistance robotics SOCIAL PIA: Cybernetic avatar modeling Scientific recognition includes: Second Prize for Best Spanish Robotics Thesis Best Paper Award Nomination (IEEE/RSJ IROS, 2009) As an advisor, she supervises: PhD students: Ferran Gebelli Guinjoan, Lavinia Hriscu, Edison Bejarano Final year projects: 8 students on topics like LLM-enhanced interaction and LiDAR SLAM systems She operates within the Institut de Robòtica i Informàtica Industrial (IRI) and collaborates with Carnegie Mellon University.

Özalp Özerمشاهده پروفایل

استاد

• Supply Chain Management
• Distribution Channel Management
• Incentive Mechanisms and Contracts
• +۷ مورد دیگر

Özalp Özer is a leading academic and industry executive specializing in Operations Management , Supply Chain Strategy , and Behavioral Operations . Currently, he serves as Director of Fulfillment by Amazon (FBA) Science & Innovation and as a Visiting Professor at MIT Sloan School of Management . He has held prestigious academic roles at The University of Texas at Dallas (George and Fonsa Brody Professor), Columbia University , and Stanford University , where he was a Consulting Associate Professor and Hellman Faculty Fellow . PhD, MS, Columbia University (Operations Research) BS, Bilkent University (Industrial Engineering) Özer's research spans end-to-end global supply chains , behavioral operations , pricing management , and inventory coordination . His work integrates Operations Research , Machine Learning , and Behavioral Economics to solve real-world business challenges. He pioneered the concept of Genuine Intelligence (GI) , combining analytical tools with human insights. His publications in top journals like Management Science and Operations Research address topics such as trust in supply chains , dynamic pricing , and RFID technology . Özer has received numerous accolades, including the Wickham Skinner Early-Career Award , NSF Grants , and teaching honors from MIT, Columbia, and Stanford. Özer actively contributes to editorial boards of major journals and has advised industry leaders like General Motors, IBM, and Amazon. His work bridges academic research and practical implementation , focusing on optimization algorithms , seller recommendation systems , and resource management .