جستجوی استاد راهنمای دانشگاهی

Osman Yağan is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with affiliate faculty status in the School of Computer Science. He is also a core member of CyLab Security and Privacy Institute. Prior to joining CMU in 2013, he was a Postdoctoral Research Fellow at CyLab. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2011) and a B.S. from Middle East Technical University (2007). His research focuses on modeling, analysis, and optimization of computing systems, leveraging applied probability, network science, data science, and machine learning. Key areas include multi-armed bandits, resilient machine learning, contagion processes in networks, and cybersecurity. Research Interests include Machine Learning, Data Science, Network Science, Cybersecurity, and Robustness in Cyber-Physical Systems. He has advised numerous students, including current PhD candidates Yurun Tian, Orkun İrsoy, and Ishank Juneja, as well as notable alumni such as Mansi Sood (now at MIT) and Jun Zhao (Assistant Professor at Nanyang Technological University). Key Awards include the CIT Dean's Early Career Fellowship, IBM Academic Award, and Best Paper Awards at ICC 2021, IPSN 2022, and ASONAM 2023. His work spans theoretical contributions (e.g., contagion models in multi-layer networks) and applied research (e.g., mitigating cascading failures in power systems). He leads or co-leads grants from ONR, NSF, and ARO, focusing on resilient machine learning, network robustness, and pandemic modeling.

• Machine Learning
• Data Science
• Network Science
• +۷ مورد دیگر

Larry Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU). He is also the Department Head of CMU’s ECE Department and has held prior roles at Westinghouse Research and Development and the University of Texas at Austin. His work bridges academic research and industry innovation, with co-founding ventures like Fabbrix Inc., Extreme DA, and Pearl Street Technologies. Dr. Pileggi earned his Ph.D. in Electrical and Computer Engineering from CMU (1989), following an M.S. (1984) and B.S. (1983) in Electrical Engineering from the University of Pittsburgh. His research focuses on three core areas: secure integrated circuit hardware (mitigating supply-chain threats), integrated circuits design methodologies (supporting sub-20nm CMOS and heterogeneous technologies), and power systems simulation (developing robust grid analysis tools like SUGAR). He has been recognized with numerous awards, including the prestigious 2023 Phil Kaufman Award for contributions to electronic system design, and is an IEEE Fellow. His academic leadership includes fostering maker initiatives and interdisciplinary research programs to address future challenges in energy and computing systems. Pileggi’s advising record includes over 47 Ph.D. students, many of whom collaborate with him in industry ventures. Current and past grants support his work on resilient power grids and novel memory technologies, reflecting a commitment to both theoretical and applied research. His lab, the Pileggi Lab, develops cutting-edge solutions for energy and integrated systems, emphasizing scalable simulation, secure hardware design, and next-generation memory architectures. Collaborations span institutions like ETH Zurich and industry partners in EDA and semiconductor sectors.

• Secure Integrated Circuit Hardware
• Integrated Circuits Design Methodologies
• Power Systems Simulation and Optimization
• +۳ مورد دیگر

Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.

• Additive Manufacturing
• Advanced Materials Processing and Manufacturing
• Digital Twins
• +۶ مورد دیگر

Jack Beuth is a Professor of Mechanical Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He has been on the faculty since 1992 and leads the NextManufacturing Center, focusing on additive manufacturing (AM) research. His work emphasizes process mapping for AM, material science, and machine learning integration in manufacturing processes. Key affiliations include the Engineering Research Accelerator and the Manufacturing Futures Institute. Education: Ph.D. in Engineering Sciences, Harvard University (1992) M.S. in Engineering Sciences, Harvard University (1989) M.S. in Engineering Science and Mechanics, Virginia Tech (1987) B.S. in Engineering Science and Mechanics, Virginia Tech (1984) Research Interests: Additive Manufacturing (process modeling, material characterization, and defect analysis) Melt pool dynamics and thermal modeling Machine learning for process optimization and quality control Advanced materials for AM (e.g., Ti-6Al-4V, Inconel 718) His research has led to innovations like 'process map' approaches for AM, enabling better control over variables such as melt pool geometry and microstructure. Awards and Recognition: Ralph R. Teetor Educational Award (1998) George Tallman and Florence Barrett Ladd Development Professorship (2000) ASME Curriculum Innovation Award (2005) Benjamin Richard Teare Teaching Award (2009) Grants and Collaborations: $3.5M cooperative agreement with the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) for AI-driven AM process optimization. Collaborations with Westinghouse Electric Company on 3D-printed nuclear components, such as spacer grids for pressurized water reactors. Labs and Teams: NextManufacturing Center: A research hub for AM innovation, emphasizing industrial partnerships and applied research. Beuth’s Additive Lab: Specializes in melt pool analysis, process mapping, and material behavior under AM conditions.

• Additive Manufacturing
• Manufacturing Processes
• Solid Mechanics
• +۶ مورد دیگر

Constantine (Costa) Samaras is the Trustee Professor of Civil and Environmental Engineering and Director of the Wilton E. Scott Institute for Energy Innovation at Carnegie Mellon University. He is also affiliated with the Department of Engineering and Public Policy and holds a courtesy appointment in the Heinz College of Information Systems and Public Policy. Director, Scott Institute for Energy Innovation Trustee Professor, Civil and Environmental Engineering Affiliated Faculty, Engineering and Public Policy Courtesy Faculty, Heinz College of Information Systems and Public Policy His research focuses on systems engineering approaches to climate resilience , clean energy transitions , and infrastructure security . Key areas include: Transportation electrification and automation Climate adaptation for infrastructure Energy policy under uncertainty AI impacts on energy systems Equity in decarbonization National security implications of energy Costa Samaras co-authored 15 recent studies spanning energy burden analysis, climate hazard indices, AI training energy optimization, and nature-based infrastructure solutions. His work emphasizes transdisciplinary collaboration between engineering, policy, and climate science. Notable scientific recognition includes being named Professor of the Year by the Pittsburgh Section of the American Society of Civil Engineers in 2018. He has led significant policy engagements including White House service (2021-2024) as Principal Assistant Director for Energy and Chief Advisor for Clean Energy Transition. Current affiliations include: Founder/Director, Center for Engineering and Resilience for Climate Adaptation Founder/Director, Power Sector Carbon Index Former Senior Researcher, RAND Corporation (2009-2014) Former Adjunct Senior Analyst, RAND Corporation (2014-2021)

• Climate Resilience
• Energy Systems
• Transportation Engineering
• +۴ مورد دیگر

Yiming Yang is a Professor at the Language Technologies Institute and Machine Learning Department within the School of Computer Science at Carnegie Mellon University , where he has held faculty positions since 2003. His research spans foundational and applied aspects of machine learning , artificial intelligence , and scientific computing . Professor, Carnegie Mellon University (2003–Present) Associate Professor, Carnegie Mellon University (1996–2003) Yang's research focuses on LLM-based problem-solving agents , combinatorial optimization , and scalable oversight frameworks . His work explores diffusion models, Langevin dynamics, and Fourier neural operators for NP-hard problems, while advancing reinforcement learning techniques for self-play supervision and principle-driven fine-tuning of large language models. Recent publications highlight his contributions to code synthesis , PDE solving , and multi-agent reinforcement learning . Key methodologies include demonstration-guided control, retrieval-augmented reasoning, and test-time scaling laws. His team has developed frameworks like FEEDER for efficient in-context learning and μTransfer-FNO for zero-shot hyperparameter transfer in PDE solvers. Notable scientific achievements include: Best Student Paper Runner Up (2013) Best Theoretical Paper Award (1994) Best Theoretical Paper Award (1993) Yang has mentored over 20 PhD students and postdocs, including Shengyu Feng , Zhiqing Sun , and Aman Madaan , across domains like graph learning , extreme multi-label classification , and language model alignment .

• Machine Learning
• Artificial Intelligence
• Combinatorial Optimization
• +۱۳ مورد دیگر

Amritanshu Pandey is an Assistant Professor in Electrical Engineering at the University of Vermont, with a part-time adjunct appointment in Electrical and Computer Engineering at Carnegie Mellon University. His research focuses on enhancing the efficiency, reliability, and security of electric grids through methods in circuit theory, optimization, and machine learning. He pioneered the SUGAR simulation engine for power systems and collaborates globally on grid challenges. Research Interests: Pandey's work spans renewable integration, grid cybersecurity, digital twins, and decarbonization. Key projects include developing algorithms for large-scale grid optimization, anomaly detection, electric vehicle infrastructure modeling, and cyber-resilient energy systems. His research addresses real-world challenges in rapidly evolving grids across Asia and Africa. Awards: Best Paper Award, IEEE PES General Meeting (2017, 2021) Best-of-the-Best Paper Award, IEEE PES General Meeting (2021) Best Student Paper Runner-up, ECML-PKDD (2018) Students & Labs: He advises 7 PhD students and has graduated 11 advisees (PhD/MS/BS). His lab focuses on power systems innovation, including the SUGAR simulation framework and projects on grid cybersecurity and sustainable electrification.

• Grid Simulation and Optimization
• Grid Cybersecurity
• Modeling of Future Energy Systems
• +۳ مورد دیگر

Shixiang (Woody) Zhu is an Assistant Professor in Data Analytics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University. He holds a PhD in Machine Learning from Georgia Institute of Technology (2022) and B.S./M.S. in Computer Science from Beijing University of Posts and Telecommunications (2017). His research bridges machine learning, operations research, and statistics, focusing on sequential modeling, human-AI collaboration, and energy systems operations. He has received awards including the IEEE Power & Energy Society Best Paper Award (2025) and was a finalist for the INFORMS Wagner Prize (2021). Education : PhD in Machine Learning, Georgia Tech (2017–2022) B.S./M.S. in Computer Science, BUPT (2010–2017) His research emphasizes spatio-temporal data analysis , decision making under uncertainty , and applications to energy systems, healthcare, and public policy. Notable projects include optimizing police zone design (Wagner Prize finalist) and enhancing grid resilience through robust optimization. He actively collaborates with institutions like Argonne National Laboratory and NSF-funded projects. Awards : Best Paper Award, IEEE Power & Energy Society (2025) Gen-AI Fellows (2024) Finalist, INFORMS Wagner Prize (2021) Advising & Grants : Advises PhD students Zekai Fan, Wenbin Zhou, and others Recipient of Block Center Seed Grant (2024), NSF funding (2024) His work spans energy resilience, public policy optimization, and causal inference in social systems. He co-leads the INFORMS Data Mining Society and reviews for top journals like Operations Research and Management Science.

• Machine Learning
• Data Science
• Operations Research
• +۷ مورد دیگر

Keenan Crane is the Michael B. Donohue Associate Professor of Computer Science and Robotics at Carnegie Mellon University , with membership in the Center for Nonlinear Analysis and mentorship in the Geometry Collective . His research bridges differential geometry and computer science to develop fundamental algorithms for geometric data processing. Education : BS from University of Illinois at Urbana-Champaign, PhD from Caltech Fellowships : Google PhD Fellow, NSF Mathematical Sciences Postdoctoral Fellow Research focuses on Discrete Differential Geometry , addressing PDE solutions, mesh processing, and geometric modeling through methods like: Walk on Spheres for PDEs Intrinsic Triangulations for robust geometry Repulsive Energy formulations for collision avoidance Recent publications span 2025–2021 , emphasizing grid-free algorithms , anisotropic mesh generation , and differentiable systems . Scientific accolades include Packard Fellowship and NSF CAREER Award . Students include Nicole Feng , Olga Gutan , and Zoë Marschner . During his 2024 sabbatical at Roblox , he does not accept new researchers. Key software contributions include Penrose (math diagram generation) and I♥Mesh (domain-specific language for mesh algorithms).

• Computer Science
• Mathematics
• Scientific Computing
• +۷ مورد دیگر

Barry Rawn is an Associate Teaching Professor in Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He focuses on stressed centralized electricity infrastructure and off-grid energy systems, particularly in Nigeria. His research contributes to the IEEE Working Group on Sustainable Energy for Developing Communities and emphasizes renewable energy integration, grid stability, and smart grid technologies. Education: All degrees from the University of Toronto: Ph.D. in Electrical Engineering MASc in Electrical Engineering BASc in Engineering Science Research Interests: Rawn explores the interplay between centralized grids and decentralized energy solutions in developing regions. His work spans transmission/distribution system optimization, renewable energy modeling, and circular economy frameworks for plastics in Africa. He also investigates battery reuse and smart grid innovations, often collaborating with industry and international partners. Key Article Trends: Recent work emphasizes circular plastics economies in Africa, vehicle-to-grid integration, and Nigerian grid modernization. Earlier research focused on wind power integration, grid stability under reverse power flows, and HVDC transmission planning. Awards: No specific awards listed, though his work aligns with IEEE sustainability initiatives. Advising/Grants: No grant details provided; maintains affiliations with CMU Africa and Brunel University London’s Smart Power Networks Theme. Collaborative activities include industrial partnerships and cross-sectoral projects in Africa. Labs/Teams: Engaged with the Institute of Energy Futures (UK) and leads fieldwork in Nigeria/Rwanda. Active in IEEE committees and African energy policy dialogues.

• Renewable Energy Integration
• Power Systems Modeling
• Sustainable Energy
• +۵ مورد دیگر

Dr. Yiqun Pan is a Special Faculty at Carnegie Mellon University's Center for Building Performance and Diagnostics, and a Visiting Professor at Lawrence Berkeley National Laboratory. With 25+ years of experience, she specializes in building performance simulation, energy efficiency, and sustainable design. Her work integrates machine learning and big data to enhance building performance and occupant well-being. Research focuses include low-carbon building technologies, energy flexibility optimization, and carbon reduction strategies. She has led projects funded by the China National Science Foundation and U.S. Energy Foundation. Dr. Pan has authored six books and over 150 publications, including 42 English journal papers. Teaching includes courses on LEED certification, green infrastructure, HVAC systems for low-carbon buildings, and building energy systems integration. Awards include IBPSA Fellow and ASHRAE Membership. She chaired the 2023 Building Simulation Conference, demonstrating global leadership in building science. Her contributions span tool development (e.g., DeST 3.0 simulation platform) and interdisciplinary collaborations. Current work bridges academic research with practical applications, advancing sustainable urban development and zero-carbon building practices.

• Building Performance Simulation
• Energy Efficiency
• Sustainable Building Design
• +۵ مورد دیگر

Sean Qian is a Professor at Carnegie Mellon University (CMU), jointly appointed in the Department of Civil and Environmental Engineering, Heinz College of Information Systems and Public Policy, and the Department of Electrical and Computer Engineering. He directs the Mobility Data Analytics Center (MAC) and co-founded TraffiQure Technologies to commercialize AI-driven infrastructure solutions. His research focuses on dynamic network modeling, intelligent transportation systems, climate resilience, and infrastructure interdependency. Supported by NSF, U.S. DOT, and industry partners, his work integrates AI, big data, and policy analysis to address urban mobility challenges. Education: PhD in Civil Engineering (UC Davis, 2011), MS in Statistics (Stanford, 2012), and dual MS/BS in Civil Engineering (Tsinghua University, 2006/2004). Research emphasizes smart cities, EV integration, cybersecurity for infrastructure, and equity in mobility policies. He serves on editorial boards for Transportation Research journals and TRB committees. Awards include the NSF CAREER Award (2018) and Greenshields Prize (2017). Grants and collaborations include projects with Fujitsu, IBM, and state agencies, addressing curbside management, climate adaptation, and rural mobility. His lab develops tools like the Rural Access Mobility Platform and social digital twin technologies for infrastructure resilience.

• Transportation Engineering
• Intelligent Transportation Systems
• Infrastructure Resilience
• +۷ مورد دیگر

Ramteen Sioshansi is a Professor in the Department of Engineering and Public Policy, the Department of Electrical and Computer Engineering, and Heinz College at Carnegie Mellon University, where he also serves as Associate Department Head for Graduate Affairs and Director of the Carnegie Mellon Electricity Industry Center. He is additionally an Adjunct Professor at The Ohio State University’s Department of Integrated Systems Engineering. His work bridges engineering, economics, and policy with a focus on energy systems and market design. His research interests include energy storage, electricity market design, renewable integration, decarbonization, grid resilience, and energy justice. He employs advanced optimization and modeling techniques to analyze how energy systems can be operated and regulated more efficiently and equitably. His work often addresses the economic and policy challenges of integrating low-carbon technologies and distributed energy resources. Ramteen's recent publications highlight a strong trend in analyzing the role of energy storage in providing multiple grid services, reforming market designs to accommodate long-duration storage, and ensuring equitable access to resilient energy. His work spans technical modeling, economic analysis, and policy implications, frequently appearing in high-impact journals such as Current Sustainable/Renewable Energy Reports and The Energy Journal . Energy Justice Through Energy Storage Long-Duration Energy Storage (LDES) Policy Electric Vehicle Integration Demand Flexibility and Aggregators Hydrogen and Carbon Removal Economics Small Modular Reactors and Nuclear Policy Ramteen has received recognition as a top researcher in energy and energy storage domains. He actively contributes to the academic community through INFORMS, particularly in the Energy, Natural Resources, and the Environment (ENRE) section, and encourages nominations for prestigious awards like the Harold Hotelling Medal. He advises graduate students, including recent PhD graduate Dr. Hyeong Jun Kim and former student Joe Duggan. His research is supported by collaborations across academia, national labs (e.g., Argonne), and industry. He frequently engages with media on topics such as natural gas supply risks, EV integration, and the future of nuclear energy. Ramteen leads the Carnegie Mellon Electricity Industry Center, a hub for interdisciplinary research on electricity markets and policy. He is also a Faculty Affiliate at the Wilton E. Scott Institute for Energy Innovation, where he contributes to CMU’s broader energy innovation ecosystem.

• Energy Systems
• Electricity Markets
• Energy Storage
• +۱۲ مورد دیگر

Dr. Burcu Akinci is the Paul Christiano Professor and Department Head of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Electrical and Computer Engineering. She holds a BS from Middle East Technical University, an MBA from Bilkent University, and MS/PhD from Stanford University. Her research focuses on integrating BIM with 3D imaging/sensor data to create digital twins for construction and infrastructure management, emphasizing predictive operations and fault diagnosis in HVAC systems. She has secured over $16M in grants, authored 70+ journal papers, and pioneered methodologies for as-built BIM generation and infrastructure monitoring. Education : PhD 2000 - Stanford University (Civil & Environmental Engineering) MS 1995 - Stanford University MBA 1993 - Bilkent University BS 1991 - Middle East Technical University Research Interests : Dr. Akinci develops technologies to streamline construction and infrastructure operations through digital twins. Key areas include: BIM integration with IoT/sensor networks 3D imaging for asset management Fault detection in HVAC systems Autonomous environmental control for space habitats Predictive maintenance using AI Grants & Patents : $6M+ PI grants, $10M+ co-PI grants (federal/state/industry) 2 patents issued, 1 provisional patent Labs & Teams : Active in the Scott Institute for Energy Innovation, leading projects on smart buildings and infrastructure resilience.

• Construction Engineering and Management
• Building Information Modeling (BIM)
• Infrastructure Systems
• +۵ مورد دیگر

Mario Bergés is a Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), where he serves as faculty co-director of the Smart Infrastructure Institute and director of the Intelligent Infrastructure Research Lab (INFERLab). His work focuses on enhancing infrastructure efficiency and resilience through information technologies, particularly in energy systems and smart buildings. Education: B.Sc. in Civil Engineering (2004), Instituto Tecnológico de Santo Domingo M.Sc. (2007) and Ph.D. (2010) in Civil and Environmental Engineering, Carnegie Mellon University Graduate Certificate in Construction Management (2005), Instituto Tecnológico de Santo Domingo Research Interests: Smart infrastructure systems Data-driven energy efficiency Sensor data analytics for civil infrastructure Climate-resilient technologies Building automation and digital twins Awards: ASCE Pittsburgh Chapter Professor of the Year (2018) FIATECH Outstanding Early Career Researcher (2010) Dean’s Early Career Fellowship (CMU, 2015) Grants and Collaborations: Recipient of 2025 Scott Institute seed grants for clean energy research Amazon Scholar collaborating on sustainability solutions Principal investigator on NSF-funded projects in smart infrastructure His lab (INFERLab) explores AI-driven solutions for infrastructure challenges, including grid-interactive buildings and space habitat systems.

• Smart Infrastructure
• Energy Efficiency
• Sensor Data Analysis
• +۷ مورد دیگر