جست‌وجوی استاد و پژوهشگر

• Multinational Management
• Industrial Relations
• Political Economy
• +۳ مورد دیگر

Greg Distelhorst is an Associate Professor at the University of Toronto, holding appointments in the Rotman School of Management and the Centre for Industrial Relations and Human Resources. Previously, he taught at MIT Sloan School of Management and Saïd Business School, Oxford. He holds a BA in Cognitive Science from Yale University and a PhD in Political Science from MIT. His research focuses on global trade and worker rights, as well as politics and policy in contemporary China. Key areas include multinational management, industrial relations, and the intersection of political economy with Chinese governance. His work explores how corporate practices in global supply chains affect labour standards, and how authoritarian regimes manage public discourse and accountability. Distelhorst has published in leading journals including Management Science , Organization Science , and American Journal of Political Science . His research has been recognized with awards such as the 2018 Responsible Research in Management Award and the American Political Science Association Dorothy Day Award. His research on Chinese governance examines mechanisms of public accountability under authoritarian rule, including how social media activism and grassroots participation influence policy outcomes. He has conducted fieldwork in China, including fellowships with the U.S. Fulbright Program and the Yale-China Association. Distelhorst’s work bridges management studies, political science, and labour economics, with a focus on systemic challenges in global supply chains and the socio-political dynamics of emerging markets.

Peter Newmanمشاهده پروفایل

استاد

• Visitor management in protected areas
• Soundscape/acoustic management in parks
• Transportation management and planning
• +۷ مورد دیگر

Peter Newman, Ph.D., serves as Dean of the Rubenstein School of Environment and Natural Resources at the University of Vermont since July 1, 2024, and holds the Suzie and Allen Martin Professor title. With a career spanning decades, he has conducted extensive research on visitor management in protected areas, soundscape management, and transportation planning, partnering with the National Park Service's Natural Sounds and Night Sky Division since 2012. Education Ph.D. in Natural Resources, University of Vermont M.S. in Forest Resource Management, SUNY College of Environmental Science and Forestry B.A. in Political Science, University of Rochester His research focuses on social carrying capacity decision-making in protected area management, with fieldwork across major U.S. parks including Denali, Grand Canyon, and Great Smokies. He has developed frameworks for acoustic management and Leave No Trace efficacy, contributing to sustainable outdoor recreation practices. Scientific Awards: Cooperative Ecosystem Studies Unit National Award (2012) George Wright Society National Award for Achievement in Social Sciences (2013) Throughout his career, Newman has led high-quality teaching at Penn State's Graduate Degree Program in Acoustics and mentored numerous students through research projects on wildlife approach norms, pandemic recreation shifts, and waste management strategies in national parks. He previously served as a Park Ranger in Yosemite and Backcountry Patrol member in Idaho.

Bing Yanمشاهده پروفایل

استادیار

• Power System Optimization
• Grid Integration of Renewables
• Microgrid Operation
• +۳ مورد دیگر

Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.

• Emerging memory and storage technologies
• Embedded systems
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.

• Ergonomics
• Digital Human Modeling
• Manufacturing Systems
• +۵ مورد دیگر

Lars Hanson is a Professor of Product Design Engineering at the University of Skövde's School of Engineering Science. His research focuses on ergonomics, digital human modeling, and optimizing manufacturing systems with a strong emphasis on human well-being and sustainable production. He leads projects like LITMUS (Industry 4.0 to 5.0 transition) and has contributed to developing tools such as IPS IMMA for ergonomic simulations. Active in virtual verification of human-robot collaboration and smart textile systems for workplace safety Published extensively in journals like International Journal of Human Factors Modelling and Simulation and IEEE Access Editor of conference proceedings and contributor to industry standards in automotive and healthcare sectors Research interests include multi-objective optimization of factory layouts, musculoskeletal risk assessment, and integrating ergonomic evaluations into product design processes. Current projects address Industry 5.0 sustainability challenges through digital twin technologies and smart manufacturing solutions.

Ari Jantunenمشاهده پروفایل

استاد

• Strategy and Management
• Strategic Change and Renewal
• Organizational Cognition
• +۸ مورد دیگر

Ari Jantunen is a Professor in Strategy Research at the LUT Business School, LUT University, Lappeenranta, Finland. He is affiliated with the Department of Business Studies and has been actively contributing to academic research in strategic management and organizational behavior. University: LUT University School: LUT Business School Department: Business Studies Position: Professor, Strategy Research Email: Ari.Jantunen@lut.fi He earned his D.Sc. (Econ.) from Lappeenranta University of Technology in 2005, establishing a long-standing academic career focused on strategic change and innovation. Ari Jantunen’s research centers on strategic change and renewal, organizational cognition, dynamic capabilities, dominant logic, and industry dynamics . His work explores how managerial cognition influences strategic decisions and organizational performance, particularly in industries undergoing transformation such as media, energy, and forest sectors. He also investigates sustainability strategies, the circular bioeconomy, and corporate social performance. His recent publications reflect a strong trend in using cognitive mapping, qualitative comparative analysis (fsQCA), and simulation modeling to understand strategic phenomena. Articles on dominant logic, strategic renewal, and cognitive diversity highlight his focus on the cognitive underpinnings of strategic management. Among his notable works are studies on the bioeconomy transition in the pulp and paper industry, innovation races in high-tech sectors, and the interplay between corporate social and financial performance. Jantunen has collaborated extensively with researchers such as Anni Tuppura, Satu Pätäri, Kalevi Kyläheiko, and Anssi Tarkiainen, often co-authoring studies in journals like European Management Journal , Journal of Business Research , and Futures . Ari Jantunen is actively engaged in research and supervision, though no specific students are listed in the provided sources. He does not appear to have received any explicitly mentioned scientific awards, but his consistent publication record in high-impact journals underscores his academic contributions. He has been involved in interdisciplinary research projects, particularly those examining the interface between the energy and forest sectors, the diffusion of energy services, and innovation in cleantech firms. His work often combines theoretical rigor with practical insights, contributing to both academic discourse and industry applications.

• Operations Management
• Business Statistics
• Queueing Theory
• +۳ مورد دیگر

Taiwo Amoo is an Assistant Professor of Business and Quantitative Methods at Brooklyn College, CUNY , where he has been employed since 1999. His academic career spans institutions including Baruch College (substitute and adjunct roles, 1993-1999) and Kaduna Polytechnic, Nigeria (1987-1988). With a PhD in Operations Research (University of Exeter, 1992) and a BSc in Statistics (University of Ibadan, 1986), Amoo specializes in operations management, statistical analysis, and educational innovation. Current position: Assistant Professor (Brooklyn College, CUNY) Key expertise: Operations Management, Queueing Theory, Rating Scale Methodology Technological proficiency: SAS, SPSS, Oracle Database Systems His research focuses on optimizing rating scale design , integrating technology in education , and interdisciplinary approaches to business programs . Publications from 2000-2002 examine biases in survey construction, humor as an educational tool, and the relevance of traditional disciplinary structures in modern academia. Notable awards include PSC CUNY Grants and recognition as the Best Statistics Student at the University of Ibadan. Current affiliations: Brooklyn College (CUNY) Past affiliations: Baruch College (CUNY), University of Exeter, Kaduna Polytechnic

Joseph Mahoneyمشاهده پروفایل

استاد

• Corporate Governance
• Organizational Economics
• Strategic Management
• +۶ مورد دیگر

Joseph Mahoney is a Professor of Business Administration and Caterpillar Chair of Business at the University of Illinois at Urbana-Champaign, holding dual appointments as Associate Director of the Illinois Strategic Organizational Initiative (ISOI). He holds a Ph.D., M.S., and B.A. in Economics from the University of Pennsylvania (1989, 1984, 1980). His academic roles include Director of Graduate Studies (2008-2012) and leadership in strategic management education. Research Interests: Corporate Governance & Organizational Economics Transaction Cost Economics & Property Rights Theory Stakeholder Theory & Behavioral Firm Theory Dynamic Capabilities & Strategic Responses to Shocks Supply Chain Efficiency & Value Creation Publications Highlight: Recent work explores organizational misconduct's impact on performance (e.g., Astros scandal), corporate personhood, resource redeployment dynamics, and Penrose's growth theories. Articles frequently appear in top journals like Strategic Management Journal and Academy of Management Review . Awards: Strategic Management Society Fellow (2013), Academy of Management Fellow (2012), and 2021 Dean's Impact Award. Active in editorial roles for Strategic Management Review and Strategic Management Journal . Teaching: Leads undergraduate Business Policy, PhD seminars on strategic theory, and philosophy of science in management. Courses emphasize integration of functional areas and societal roles of firms.

Tho Leمشاهده پروفایل

استادیار

• Transportation Modeling
• Logistics and Supply Chain Optimization
• AI/Machine Learning Applications
• +۶ مورد دیگر

Tho Le is a tenure-track Assistant Professor of Industrial Engineering Technology at Purdue University’s School of Engineering Technology. He leads the Smart Logistics (SmartLogs) Systems Research Lab and is affiliated with the Institute for Control, Optimization, and Network (ICON), Realizing the Digital Enterprise (RDE) initiative, Integrative Data Science Initiative (IDSI), and Semiconductors @ Purdue. His research focuses on system-scale transportation modeling using optimization, AI/ML, and econometrics to guide industry and policy decisions. Education: Ph.D. in Transportation Systems, Purdue University MSc in Industrial Engineering (Operations Research), Purdue University M.Eng. in Transportation Engineering (Best Thesis Award), Hiroshima University Research Interests: Emerging technologies: sidewalk delivery robots, indoor service robots, drones Semiconductor supply chain resilience and Lean Six Sigma applications Digital twins for logistics systems and fleet management Freight transport, connected/autonomous vehicles, travel behavior modeling Awards & Recognition: Recipient of National Science Foundation grant for energy efficiency modeling (2024) Polytechnic Research Awards (July 2024) Lab & Collaboration: SmartLogs Lab: develops data-driven solutions for urban logistics and asset management Leadership in Purdue’s semiconductor initiatives aligned with the CHIPS Act

Nikos Hardavellasمشاهده پروفایل

استاد

• Computer Architecture
• Quantum Computing Systems
• Parallel Systems
• +۴ مورد دیگر

Nikos Hardavellas is a Professor of Computer Science and Electrical and Computer Engineering at Northwestern University, affiliated with the McCormick School of Engineering. He leads the Parallel Architecture Group at Northwestern (PARAG@N), focusing on energy-efficient parallel computing and quantum systems. His research spans quantum computing systems, fault-tolerant quantum error management, memory-centric architectures, and photonics-based interconnects. Education: Ph.D. Computer Science, Carnegie Mellon University (2009) M.S. Computer Science, Carnegie Mellon University (2006) M.S. Computer Science, University of Rochester (1997) B.S. Computer Science, University of Crete (1995) Research Interests: Quantum system software stack and error mitigation Memory-centric computing and programmable memory systems Energy-efficient architectures and dark silicon Photonics and optical interconnects Parallel systems and compiler-hardware co-design Key Contributions: Developed SupermarQ, a scalable quantum benchmark suite Pioneered optical cache hierarchies (Pho$) and energy-proportional photonic networks Advanced compiler-driven virtual memory systems (CARAT) and MPI autotuning (ACCLAiM) Awards & Honors: NSF CAREER Award (2015) Future CRA Leader (2024) Best Paper Awards at HPCA (2022) and ISLPED (2021 nomination) Test-of-Time Award at EDBT (2019) Grants & Service: Secured $4.8M in research funding from NSF, industry partners, and university initiatives Executive Committee member of Northwestern’s INQUIRE Institute for Quantum Research General Co-chair of IEEE/ACM MICRO 2022 Extensive service on departmental committees and thesis advisory boards Labs & Teams: Directs PARAG@N, collaborating on quantum computing, photonics, and energy-efficient architectures. Engages with industry partners like AMD, Intel, and Synopsys.

Cathy Wuمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Machine Learning
• Large-scale Optimization
• +۶ مورد دیگر

Cathy Wu is the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering at MIT, affiliated with the Institute for Data, Systems, and Society (IDSS). Her research bridges machine learning, optimization, and urban systems, with a focus on mixed autonomy systems in mobility. She holds degrees from MIT (B.S., M.Eng in EECS) and a Ph.D. from UC Berkeley (EECS). Education: B.S. and M.Eng in Electrical Engineering and Computer Science, MIT (2012-2013) Ph.D. in Electrical Engineering and Computer Science, UC Berkeley (2018) Research Interests: Reinforcement Learning and Machine Learning Large-scale Optimization and Control Theory Mobility Systems and Urban Infrastructure Implications of AI and Automation Her work emphasizes interdisciplinary collaboration, involving transportation, computer science, and public policy. She founded the Interdisciplinary Research Initiative within the ACM Future of Computing Academy to advance cross-disciplinary computing research. Key Projects: Includes Flow (open-source RL framework for traffic control), eco-driving incentive mechanisms, and mixed autonomy traffic optimization. Her articles address congestion mitigation, autonomous vehicle integration, and scalable supervision strategies. Awards: Recipient of fellowships, best paper awards, and teaching honors (specific names unlisted). Engagement: Collaborations with institutions like Microsoft Research, OpenAI, and Caltrans. Active in policy-oriented initiatives and education through IDSS programs.

Chen Zhiمشاهده پروفایل

استادیار

• Innovation Sourcing
• AI Development
• Wisdom of Crowds
• +۲ مورد دیگر

Chen Zhi is an Assistant Professor in the Department of Analytics and Operations at the NUS Business School, National University of Singapore, where he has been employed since July 2020. His academic work focuses on operational challenges in innovation-driven value chains, with particular expertise in new product development, innovation sourcing, AI economics, and wisdom of crowds methodologies. Dr. Chen received his Ph.D. in Management (Decision Sciences) from INSEAD (2014-2020) and his B.E. with First Class Honors in Industrial and Systems Engineering from the National University of Singapore (2009-2013). During his academic journey, he completed an overseas exchange at the Georgia Institute of Technology and a research internship at École Polytechnique in France. Chen's research spans two primary streams. The first addresses R&D phase challenges in new products, examining how firms can optimally design supplier bases and informational policies to procure innovation from suppliers, with recent focus on policy impacts on AI-based product development such as autonomous vehicles. The second stream investigates demand forecasting for new products, exploring how to aggregate diverse expert insights into consensus forecasts and quantify underlying uncertainty through obtained forecasts. His publication record demonstrates a strong trajectory in top-tier operations and management journals, with recent work appearing in Management Science, Manufacturing & Service Operations Management, and International Journal of Forecasting. Chen's research shows increasing focus on AI development challenges, uncertainty quantification in forecasting, and strategic approaches to innovation sourcing in complex technological environments. At NUS Business School, Chen teaches Managerial Operations and Analytics for the MBA program and Decision Analytics Using Spreadsheets for undergraduate students. Previously at INSEAD, he taught tutorials for Uncertainty, Data and Judgment, and Production and Operations Management courses.

Hamed Rahimianمشاهده پروفایل

استادیار

• Stochastic Optimization
• Data-Driven Optimization
• Risk-Averse Optimization
• +۳ مورد دیگر

Dr. Hamed Rahimian is an Assistant Professor in the Department of Industrial Engineering at Clemson University. He holds a Ph.D. in Industrial and Systems Engineering from The Ohio State University (2018), an M.Sc. from The University of Arizona (2012), and B.Sc./M.Sc. degrees from Sharif University of Technology (2008/2011). Prior to Clemson, he was a Postdoctoral Research Fellow at Northwestern University under Prof. Sanjay Mehrotra. His research focuses on data-driven decision-making under uncertainty, including stochastic optimization, distributionally robust optimization, and risk-averse methodologies. He has published in top journals such as Mathematical Programming , SIAM Journal on Optimization , and Operations Research . Education: Ph.D. Industrial and Systems Engineering, The Ohio State University (2018) M.Sc. Industrial Engineering, The University of Arizona (2012) B.Sc./M.Sc. Industrial Engineering, Sharif University of Technology (2008/2011) His research has been recognized with awards including the Harold W. Kuhn Award (2022), Runner-Up INFORMS Computing Society Student Paper Award (2017), and 2nd Place IISE Pristker Dissertation Award (2019). He serves as an Associate Editor for INFORMS Journal on Computing and Sharif Journal of Industrial Engineering & Management . Grants & Advising: He secured an Air Force grant (2024) on multistage stochastic programming. His research group focuses on advancing optimization under uncertainty with applications in healthcare, energy, and supply chains. Labs/Teams: Leads a research group in Clemson’s Industrial Engineering department, collaborating on projects in distributionally robust optimization and data-driven decision-making.

Zhen Ming Jiangمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence
• Computer Systems
• +۶ مورد دیگر

Zhen Ming (Jack) Jiang is an Associate Professor and York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems at York University's Department of Electrical Engineering and Computer Science. His research bridges software engineering, artificial intelligence, and computer systems with significant industrial impact. Dr. Jiang earned his Ph.D. from Queen's University's School of Computing and MMath/BMath degrees from the University of Waterloo's David R. Cheriton School of Computer Science. During his doctoral studies, he collaborated with BlackBerry's Performance Engineering team, developing tools now used daily to monitor commercial software systems. His research focuses on engineering rigor for AI-powered applications , software engineering evolution in the Generative AI era , and performance optimization of large-scale systems . Key areas include software performance engineering, mining software repositories, debugging distributed systems, source code analysis, and software visualization. His work combines empirical studies with practical tool development. Recent publications reveal strong trends in applying AI to software engineering challenges, particularly in machine learning systems reliability, blockchain efficiency, and AIOps solutions. His research consistently emphasizes empirical validation using real-world systems and industrial case studies. Scientific recognition includes: York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems NSERC Discovery Accelerator Supplements (DAS), 2020 Best Paper Award at ICST 2016 IEEE Software Best SEIP Paper at ICSE 2015 Ph.D. Research Achievement Award at Queen's University Multiple best paper awards at WCRE, MSR, and ICSE Dr. Jiang actively supervises graduate students and has secured competitive research funding including NSERC grants. His service includes program committee roles for top conferences (ICSE, ASE, ICSME) and editorial work for leading journals (TSE, TOSEM, EMSE). He leads research initiatives focused on foundation model-powered systems, collaborating with industry partners on performance monitoring and debugging solutions for large-scale distributed environments.

• Wireless Communications
• Reconfigurable Intelligent Surfaces
• Physical Layer Security
• +۷ مورد دیگر

Dr. Sylvester Boadi Aboagye is an Assistant Professor in the School of Engineering at the University of Guelph, Canada. His research focuses on next-generation wireless communication and sensing systems, including reconfigurable intelligent surfaces (RIS), physical layer security, visible light communication (VLC), terahertz networks, and integrated sensing-communication frameworks. He received his Ph.D. and M.Eng. from Memorial University (Canada) and B.Sc. (Honors) from Kwame Nkrumah University of Science and Technology (Ghana). Prior to joining University of Guelph, he was a Postdoctoral Fellow at York University (2023). Dr. Aboagye's expertise includes machine learning for resource allocation, energy-efficient network design, and prototyping optical RIS systems. He currently serves as an Editor for IEEE Communications Letters and has received notable awards including the Governor General’s Gold Medal and recognition as an Exemplary Reviewer. His work addresses challenges in 6G systems, underwater communications, and sustainable network architectures.