جست‌وجوی استاد و پژوهشگر

Tiancheng Zhaoمشاهده پروفایل

پژوهشگر

• Multimodal Foundation Models
• AI Agents
• Vision-Language Models
• +۳ مورد دیگر

Tiancheng Zhao is a principal researcher at the Binjiang Institute of Zhejiang University and founder of the Om Artificial Intelligence Laboratory (Om AI Lab), dedicated to frontier open multimodal AGI research for building next-generation agents that transform work and life through advanced human-machine interaction. His academic credentials include: Ph.D. in Computer Science from Carnegie Mellon University (2016-2019) under Prof. Maxine Eskenazi, Prof. Louis-Philippe Morency, Prof. William W. Cohen, and Dr. Dilek Hakkani-Tur, with pioneering dissertation “Learning to Converse With Latent Actions” in end-to-end generative conversational models M.S. in Computer Science from Carnegie Mellon University (2014-2016) B.S. in Electrical Engineering from UCLA (2010-2014) with Summa Cum Laude, focusing on speech signal processing under Prof. Abeer Alwan Dr. Zhao’s research centers on multimodal foundation models and agents, tackling three core challenges: Multimodal Models for cross-modal representation learning in high-dimensional data, Learning to Learn for effective skill acquisition from diverse signals (supervised labels, rewards, meta-learning), and AI Agents for open-world understanding and complex decision-making. His work bridges computer vision, natural language processing, and real-world applications including healthcare analytics and remote sensing. Analysis of his 50+ publications reveals accelerating innovation in multimodal large language models (2024-2025), with emphasis on stable vision-language architectures (VLM-R1), agent orchestration frameworks, and domain-specific applications in geospatial analysis and healthcare. Key trends include solving long-tail distribution challenges in satellite imagery, developing human-like zooming capabilities for multimodal LLMs, and creating unified benchmarks for autonomous GUI testing. His scientific recognition includes: National Breakthrough Technology Award by Ministry of Science and Technology (2021) Microsoft Research Best & Brightest PhD (2018) BEST PAPER AWARD at SIGDIAL 2018 Best Paper Nomination at SIGDIAL 2016 Top 1 Outstanding Bachelor of Science Award at UCLA (2014) As Om AI Lab founder, Dr. Zhao leads research teams developing computational building blocks for human-AI collaboration. While specific student mentorship details aren’t public, his extensive publication record with junior co-authors indicates active research supervision. Current projects focus on practical system implementations for real-world multimodal agent deployment across diverse domains.

Hamsa Bastaniمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Healthcare Operations
• +۵ مورد دیگر

Hamsa Bastani is an Associate Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania, with a secondary appointment in Statistics and Data Science. She co-directs the Wharton Healthcare Analytics Lab and serves as an Associate Editor for Operations Research, M&SOM and OR Letters. Her academic journey began with summa cum laude graduation from Harvard in 2012 with an A.M. in physics and A.B. in physics and mathematics. She completed her PhD in Stanford's Electrical Engineering department under Mohsen Bayati, followed by a Herman Goldstine postdoctoral fellowship at IBM Research. Professor Bastani's research focuses on developing novel machine learning algorithms for data-driven decision-making, with applications spanning healthcare operations, social good, and revenue management. Her work demonstrates particular expertise in sequential decision-making (bandits, reinforcement learning), learning from auxiliary data sources (transfer learning, meta-learning), and designing effective human-AI interfaces (interpretability, fairness). She has made significant contributions to understanding how AI systems affect and augment human behavior, with the goal of designing AI tools that help humans thrive. Her publications reveal a strong trend toward high-impact applications of machine learning in critical societal domains. A significant portion of her recent work focuses on healthcare applications, including optimizing health supply chains in low- and middle-income countries, designing clinical trial protocols, and creating targeted public health interventions. Another major theme examines the complex relationship between humans and AI systems, particularly how AI affects learning outcomes and decision-making processes. Her work frequently bridges theoretical advances with practical implementation, as evidenced by country-scale deployments in Greece and Sierra Leone. Wagner Prize for Excellence in Operations Research Practice (2021) Pierskalla Award for Best Paper in Healthcare (2021, 2019, 2016) Behavioral OM Best Paper Award (2021) Public Sector in OR Best Paper Award (2024) INFORMS Data Mining Best Paper Award (2022) Wharton Teaching Excellence Award (2019, 2020, 2021) Professor Bastani has advised numerous PhD students who have gone on to prominent positions, including Pia Ramchandani (Director of Responsible AI at PwC), Arielle Anderer (Assistant Professor at Cornell Johnson), and Kan Xu (Assistant Professor at ASU Carey). Her research has been supported by collaborations with national governments, including the Greek government where she co-designed Eva, the national-scale reinforcement learning system for targeted COVID-19 testing, and the Government of Sierra Leone where she improved patient access to essential medicines by nearly 20% via decision-aware learning. She has also conducted the first large field study deploying generative AI tutors in high school math classes. She leads the Wharton Healthcare Analytics Lab and serves on the Steering Committee for the Penn Center for Health Incentives and Behavioral Economics and on the statistics advisory committee for the AHA Food is Medicine Initiative. Outside academia, she serves on the Workday AI Advisory Board, demonstrating her commitment to translating academic research into practical applications.

Soraya Fatehiمشاهده پروفایل

استادیار

• Operations Management
• Supply Chain Logistics
• On-Demand Platforms
• +۵ مورد دیگر

Soraya Fatehi is an Assistant Professor in the Department of Operations Management at the Jindal School of Management (JSOM), University of Texas at Dallas. Her research focuses on operations management challenges in on-demand and crowdsourced systems, retail operations, and the OM-Finance interface. She holds a PhD in Operations Management from the University of Washington, an MS in Systems Engineering from the University of Arizona, and a BS in Industrial Engineering from the University of Tehran. Education: PhD, Operations Management, University of Washington, 2020 MS, Systems Engineering, University of Arizona, 2015 BS, Industrial Engineering, University of Tehran, Iran, 2013 Her research interests span the operational dynamics of on-demand platforms, crowdsourcing in logistics, sustainable transportation solutions, and the intersection of operations management with financial strategies. She has contributed to advancing methodologies for optimizing inspection policies in manufacturing and developing revenue-sharing frameworks in crowdfunding contexts. In her recent publications, Dr. Fatehi explores the integration of autonomous vehicles in food delivery, green initiatives in ride-hailing, and strategies to combat greenwashing in competitive markets. Her work also addresses the optimization of last-mile delivery through crowdsourcing and the operational management of on-demand systems. Earlier contributions include algorithmic approaches for production process inspections and revenue-sharing models in crowdfunding. Scientific Awards: Outstanding Teaching Award, Foster School of Business, University of Washington, 2019 Outstanding Research Award, Foster School of Business, University of Washington, 2018 Advising and Grants: No specific advising or grant information is provided in the text.

Milos Prvulovicمشاهده پروفایل

استاد

• Computer Architecture
• Hardware Security
• Side Channels
• +۴ مورد دیگر

Milos Prvulovic is a Professor in the School of Computer Science at Georgia Institute of Technology's College of Computing. His research focuses on computer architecture, hardware security, and physical side channels, particularly leveraging electromagnetic emissions for program monitoring, malware detection, and secure execution. He has published extensively in top-tier conferences like HPCA, MICRO, and IEEE Transactions series. His work has been recognized with awards including ACM Senior Member (2009) and multiple best paper awards. Teaching includes courses such as High Performance Computer Architecture (OMS CS 6290/CS 4290), Processor Design (CS 3220), and advanced topics like Reliability & Security in Computer Architecture (CS 7292/8804). His research lab explores innovative solutions for embedded system security, IoT protection, and side-channel vulnerabilities. Key contributions include the EMSim tool for electromagnetic side-channel simulation, REMOTE malware detection framework, and the EDDIE anomaly detection system. Collaborations with Alenka Zajic and others highlight interdisciplinary work in hardware-software security interfaces.

• Empirical Operations Management
• Healthcare Operations Management
• OM/Information Systems Interface
• +۵ مورد دیگر

Yao Li is an Assistant Professor at the Department of Information Systems and Management Engineering within the College of Business at Southern University of Science and Technology (SUSTech). She joined SUSTech in 2021 after completing her doctoral studies at Tsinghua University and has established herself as a rising scholar in operations management with a focus on healthcare applications. Education: Ph.D. in Management Science and Engineering, Tsinghua University (2015-2021) CSC Jointly Trained Doctoral Student, Purdue University Krannert School of Management (2018-2019) B.S. in Industrial Engineering, Beihang University (2011-2015) Dr. Li's research sits at the intersection of operations management and information systems, with particular emphasis on healthcare operations. Her work investigates how information technology impacts healthcare delivery systems, especially in areas like interhospital patient transfers, health IT interoperability, and the application of network analysis to healthcare systems. She also explores broader applications of operations management principles in sustainable manufacturing and new energy vehicle industries. Her research methodology combines empirical analysis with network science approaches to examine complex operational systems. Her publication record demonstrates a clear trajectory from manufacturing supply chains toward healthcare operations, with recent work focusing on health information exchange, patient care seeking behavior, and the impact of digital technologies on healthcare delivery. This evolution reflects both her growing expertise and the increasing importance of digital health systems in modern healthcare. Scientific Awards: Finalist for Best Paper Award & Best Student Paper Award at INFORMS CIST 2020 Best CTO Division Paper at Academy of Management First prize in SUSTech Young Faculty Teaching Competition Outstanding Graduate of Beijing Outstanding Doctoral Dissertation at Tsinghua University Dr. Li currently leads multiple research projects including a National Natural Science Foundation of China Youth Project on data-driven regional collaborative medical service research for cardiovascular diseases (2024-2026), a Shenzhen Science and Technology Innovation Commission project on new energy vehicle consumption markets, and a Shenzhen Excellent Science and Technology Innovation Talents project on complex network analysis applications. Her research funding demonstrates strong institutional support for her work at both national and municipal levels. Her research appears to be conducted through interdisciplinary collaborations, often working with colleagues from healthcare institutions, engineering departments, and business schools to address complex operational challenges in healthcare delivery systems and manufacturing networks.

• Retail Operations
• Operations Management
• Supply Chain Management
• +۳ مورد دیگر

HU Honggang is an Assistant Professor at the Advanced Institute of Business (AIB), Tongji University, since October 2022. He holds a Ph.D. in Operations Management from the University of Florida and has academic backgrounds in Computer Science (M.S.) and Mathematics (B.A.). Education : Ph.D. in Operations Management, Warrington College of Business, University of Florida, 2022 M.S. in Computer Science (Computational Operations Research), College of William and Mary, 2017 B.A. in Mathematics and Applied Mathematics, Shanghai University, 2015 His research focuses on interdisciplinary topics bridging Retail Operations, Operations Management-Marketing/Information Systems (OM-Marketing/IS Interface), Supply Chain Management, Behavioral Economics, and Sustainability & Social Responsibility. His work examines pricing strategies, product substitutability, distribution models, and robust optimization methods. The articles in his profile highlight trends in Supply Chain Management, particularly Retail Pass-Through dynamics, Distribution Channels, and Robust Optimization. These studies integrate analytical frameworks with real-world retail and supply chain challenges. Scientific Awards & Grants : Shanghai Lingjun Talent (Overseas) – Youth Program, 2023 NSFC Youth Program Grant #72401218 (Supply Chains in Modern Retailing), PI, 2025–2027 Supply Chain Management (SCM) Center Research Grant, University of Florida, 2022 COR Graduate TA Teaching Award, College of William and Mary, 2017 HU Honggang has taught courses such as Principles of Management – Management in China at Tongji University, Managerial Operations Analysis II at the University of Florida, and Brief Calculus with Applications at the College of William and Mary. He has served as a Conference Session Chair and Journal Reviewer for leading operations and management science conferences and journals.

Longyuan Duمشاهده پروفایل

دانشیار

• Operations Management
• Business Analytics
• Revenue Management
• +۵ مورد دیگر

Longyuan Du is an Associate Professor in the Department of Business Analytics and Information Systems at the School of Management, University of San Francisco. He holds a Ph.D. in Operations Management from the Rotman School of Management, University of Toronto (2018), an M.Sc. in Civil Engineering from the University of Maryland, College Park (2012), and a B.Sc. in Mathematics from Fudan University, Shanghai, China (2010). Prior to his academic career, he worked as an Operations Research Analyst at 4R Systems from 2012 to 2014. His research focuses on the intersection of operations management and business analytics, particularly addressing operational challenges in emerging industries with significant social interactions. Key research areas include revenue management, pricing strategies, and the OM-Marketing interface. He explores topics such as crowdfunding dynamics, sales effort optimization, and policy analysis in transportation systems. Dr. Du’s recent work includes studies on dynamic pricing models, contingent stimulus in crowdfunding platforms, and revenue management strategies in the sharing economy. His earlier research has addressed congestion mitigation through rationing and pricing, as well as economic models for vehicle ownership policies in China. These contributions highlight his expertise in applying analytical frameworks to real-world problems across multiple sectors. Notably, his work has been published in journals like Transportation Research Part B and through industry collaborations.

Benjamin Shaoمشاهده پروفایل

استاد

• IT Impacts
• Data Analytics
• Digital Platforms
• +۵ مورد دیگر

Benjamin B.M. Shao is a Professor of Information Systems and Associate Dean for Asia-Pacific Programs and Initiatives at Arizona State University's W. P. Carey School of Business. He co-directs the Digital Society Initiative and leads efforts in international academic collaborations, particularly in China. His research focuses on IT impacts, data analytics, digital platforms, cybersecurity, healthcare IT, and the interface between information systems and operations management. Shao has been recognized with multiple teaching awards, including the Outstanding Graduate Teaching Award and the DISC Professor of the Year Award. He serves on editorial boards for journals such as the Journal of the Association for Information Systems and Decision Support Systems , and has consulted for organizations like Honeywell and IARPA. His work bridges academic research and practical applications, addressing challenges in global supply chains, healthcare systems, and digital innovation. Education : Ph.D., Management Information Systems (SUNY Buffalo, 2000); M.S. and B.S. in Information & Computer Science (National Chiao Tung University, Taiwan). Research Projects : Includes studies on telecommunications productivity, AI perception in socio-economic contexts, and critical supplier identification in supply networks. Shao’s publications span leading journals like MIS Quarterly , Decision Support Systems , and Information Systems Research , with media coverage in Harvard Business Review and NPR. His teaching spans graduate and executive education courses on IT strategy, data analytics, and global finance.

• Pricing and Revenue Management
• Data Analytics
• Forecasting Applications
• +۶ مورد دیگر

Thunyarat (Bam) Amornpetchkul is an Assistant Teaching Professor in the Department of Information Systems and Analytics (ISA) at Santa Clara University’s Leavey School of Business. Previously, she served as an Associate Professor in Operations Management at NIDA Business School in Bangkok, Thailand, and was a Visiting Professor at Boston College’s Carroll School of Management. Her expertise spans Pricing and Revenue Management, Data Analytics, and Supply Chain Management. Prof. Amornpetchkul holds a Ph.D. in Business Administration (Operations and Management Science) from the University of Michigan’s Ross School of Business (2014), and dual degrees from the University of Pennsylvania: a B.S. in Economics (Wharton School) and a B.A.S. in Computer Science (School of Engineering and Applied Science), both Summa Cum Laude (2008). Her research focuses on strategic decision-making, startup ecosystems, and innovation, with publications in journals like Production and Operations Management and Journal of Entrepreneurship in Emerging Economies . She has led over $1.2M in consulting projects addressing cluster competitiveness, logistics systems, and blockchain technology. Prof. Amornpetchkul teaches across undergraduate, MBA, and executive programs, emphasizing practical applications of analytics and operations management. Her work bridges academic theory with real-world challenges in industries such as healthcare, finance, and technology.