جستجوی استاد راهنمای دانشگاهی

Levent Burak Kara is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Robotics Institute. He is a leading researcher in AI-driven computational design, additive manufacturing, and intelligent engineering systems, leading the Visual Design and Engineering Lab (VDEL) at CMU. Education: B.S., Mechanical Engineering, Middle East Technical University (1998) M.S., Mechanical Engineering, Carnegie Mellon University (2000) Ph.D., Mechanical Engineering, Carnegie Mellon University (2005) His research focuses on integrating machine learning, optimization, and geometric modeling to revolutionize engineering design and manufacturing. Key areas include topology optimization, CAD intelligence, digital twins, generative design, bioengineering, and electronic design automation. His work enables automation of traditionally labor-intensive design processes using deep learning and reinforcement learning. His recent publications reveal a strong trend toward physics-informed surrogate modeling, real-time simulation, manufacturability prediction, and AI-driven automation in mechanical, biomedical, and electronic systems. These works frequently appear in top journals such as Journal of Mechanical Design and Journal of Applied Mechanics , and at premier conferences like NeurIPS and DAC. Scientific Awards: National Science Foundation CAREER Award ASME Design Automation Society Young Investigator Award Google AI for Social Good Impact Scholar Kara advises several Ph.D. students and has secured significant funding from federal agencies such as the NSF and the U.S. Army Research Laboratory, as well as collaborations with industrial leaders including Cadence Design Systems and NVIDIA. His research is also supported by CMU’s NextManufacturing Center and the Critical Technology Initiative. He is actively involved in developing intelligent design systems that leverage AI to automate product design, optimize manufacturing processes, and improve medical diagnostics, particularly in oral cancer screening and organ preservation. His lab, VDEL, is a hub for innovation in AI-enabled engineering.

• Machine Learning
• Artificial Intelligence
• Computational Design
• +۱۲ مورد دیگر

Maarten de Boer is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Materials Science and Engineering. He joined CMU in 2007 after roles as a process engineer at Hewlett-Packard (1983–1991) and principal member of technical staff at Sandia National Labs (1996–2010). He holds a Ph.D. in Materials Science (University of Minnesota, 1996), an MS in Electrical Engineering (University of Colorado, 1982), and a BS in Electrical Engineering (Cornell University, 1981). His research focuses on nanomechanical behavior of materials, MEMS, and additive manufacturing. Key projects include tantalum-based thermal actuators, high-entropy alloys, and micromachine reliability. His work is funded by the DOE, NSF, NASA, and the Army Research Lab. He has authored over 90 peer-reviewed articles, holds seven US patents, and advises students in the de Boer Group. Research Themes: Micro/Nano Manufacturing, Thin Film Mechanics, Friction & Wear, MEMS Reliability Funding Sources: NSF, DOE, NASA, ARL Courses Taught: Mechanics of Materials, Material Selection, Electronics for Sensing, Thermodynamics Notable collaborations include Gianluca Piazza (NSF LEAP-HI grant), Jack Beuth, and Bryan Webler (high-entropy alloys). Media highlights include breakthroughs in tantalum MEMS and ultra-strong polymer nanofibers. His group operates advanced test facilities for in-situ environmental studies of materials.

• Mechanics of Materials
• MEMS (Microelectromechanical Systems)
• Micro/Nano Manufacturing
• +۷ مورد دیگر

Bryan Webler is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU) since 2013, with a courtesy appointment in the Department of Mechanical Engineering. He serves as Co-Director of the Center for Iron and Steelmaking Research (CISR), an industry-supported consortium, and is affiliated with the NextManufacturing Center and Mill 19 digital backbone initiative. His expertise spans process metallurgy, additive manufacturing, and steelmaking technologies. Education: B.S. in Engineering Physics (2005) from the University of Pittsburgh; M.S. (2007) and Ph.D. (2008) in Materials Science and Engineering from CMU. Prior to academia, he worked as a Senior Engineer at the Bettis Atomic Laboratory's Materials Technology department. Research focuses on four core areas: chemical reactions during liquid steel refining, non-metallic inclusion control, continuous casting of steel, and additive manufacturing (laser powder bed fusion, directed energy deposition). His group integrates high-temperature experiments, computational thermodynamics, and kinetic modeling. Notable contributions include developing oxide dispersion strengthening methods and advancing digital twin applications in manufacturing. Key awards include the Kent D. Peaslee Junior Faculty Award (AIST Foundation) and the AIST Foundation Steel Professor title. He serves on editorial boards for Metallurgical and Materials Transactions B and Metallurgical Research and Technology , and actively contributes to industry partnerships. Beyond technical work, Webler explores the history of metallurgy, particularly Pittsburgh's steel industry legacy. His lab's innovations address carbon management, energy production, and advanced materials processing for extreme environments.

• Process Metallurgy
• Advanced Materials Processing
• Steelmaking Technology
• +۷ مورد دیگر

Hui Zhang is a Professor in the Computer Science Department at Carnegie Mellon University. His research focuses on data-driven networking systems, video streaming optimization, and network control frameworks. He has contributed to innovations in adaptive resource allocation, real-time analytics, and sustainable strategies for resource utilization. Key research themes include time-state analytics, network anomaly detection, and integrating machine learning for enhanced performance. His work addresses challenges in content delivery networks (CDNs), peer-to-peer systems, and environmental applications like waste management. Recent publications (2021–2024) highlight advancements in neural network-based prediction, timeline frameworks, and sustainable material science innovations. No scientific awards are mentioned in the provided text. His research emphasizes practical solutions for improving video quality of experience (QoE), network efficiency, and cross-disciplinary applications.

• Computer Science
• Networking
• Data-Driven Systems
• +۳ مورد دیگر

Dr. Siyang Zheng is a Professor at Carnegie Mellon University (CMU) in the Departments of Biomedical Engineering and Electrical and Computer Engineering. He leads the Micro & Nano Integrated Biosystem (MINIBio) Lab, focusing on developing micro/nano technologies for precision healthcare. His research bridges materials science, device engineering, and biomedicine, with key areas including liquid biopsy technologies for cancer diagnosis, nanomaterials for therapeutics, and virus detection platforms. Dr. Zheng holds over 50 peer-reviewed publications and 15 patents, and has been honored with the NIH Director's New Innovator Award and the American Cancer Society’s Research Scholar Award. Education: B.S., Biological Sciences and Biotechnology, Tsinghua University, China, 1996 M.S., Electrical Engineering, The Pennsylvania State University, 2000 Ph.D., Electrical Engineering, California Institute of Technology, 2007 Postdoctoral Research, Electrical Engineering, California Institute of Technology, 2008 Research Interests: Microfluidics/BioMEMS, nano-biotechnology, cancer diagnosis/treatment, infectious diseases, implantable devices. His lab pioneers technologies like lipid nanoprobes for EV isolation, flexible micro spring arrays for CTC enrichment, and carbon nanotube-based virus detection systems. Articles Trends: Recent work emphasizes liquid biopsy advancements, extracellular vesicle analysis, and nanomedicine innovations. Key themes include ultrafast protein digestion systems, drug delivery via nanomaterials, and point-of-care diagnostics for viral pathogens. Awards: NIH Director's New Innovator Award American Cancer Society (ACS) Research Scholar Award Advising & Grants: Supervised over 20 students (PhD, M.S., undergrad), with notable alumni in academia and industry. Active in translational research, including collaborations on clinical trials and device commercialization. Labs & Teams: MINIBio Lab at CMU fosters interdisciplinary projects with clinicians, engineers, and industrial partners. Current focus areas include thymus-on-chip models, metal-organic frameworks for drug delivery, and AI-driven biomarker discovery.

• Biomedical Engineering
• Nanotechnology
• Microfluidics
• +۷ مورد دیگر

Noa Marom is an Associate Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in Chemistry and Physics. She is a member of the Pittsburgh Quantum Institute (PQI) and an affiliate of the Wilton E. Scott Institute for Energy Innovation. Her research focuses on computational materials science, energy security, and quantum materials. Marom earned a B.A. in Physics and B.S. in Materials Engineering (cum laude) from the Technion-Israel Institute of Technology (2003) and a Ph.D. in Chemistry from the Weizmann Institute of Science (2010). She held postdoctoral positions at the University of Texas at Austin’s Institute for Computational Engineering and Sciences (ICES) before joining Tulane University as an Assistant Professor (2013–2016) and CMU in 2016. Her research interests include computational design of semiconductor materials, topological quantum computing, and crystal structure prediction. Key projects involve machine learning for materials discovery and quantum computing applications, such as optimizing semiconductor interfaces for stable qubits. Marom has received numerous awards, including the NSF CAREER Award (2016), DOE INCITE Awards (2017–2019), and the IUPAP Young Scientist Prize (2018). She serves as Associate Editor of npj Computational Materials. Her work spans collaborations with institutions like the Paul Scherrer Institute (Switzerland) and the Pittsburgh Supercomputing Center. Research highlights include computational studies of InAs/InSb semiconductors for quantum bits and machine learning-driven discovery of organic semiconductors.

• Computational Materials Science and Engineering
• Quantum Materials
• Semiconductor Materials
• +۵ مورد دیگر

Zachary Ulissi is an Adjunct Professor in the Department of Chemical Engineering at Carnegie Mellon University. He holds a B.S. in Physics and B.E. in Chemical Engineering from the University of Delaware (2009), an M.A.S. in Mathematics from the University of Cambridge (2010), and a Ph.D. in Chemical Engineering from MIT (2015). His research applies systems engineering and machine learning to nanoscale carbon nanotube devices, catalyst networks, and electrochemical reduction processes. His core research focuses on catalysis, surface science, energy systems, and machine learning applications in chemical engineering. Key areas include developing computational methods to optimize catalyst reactions for sustainable fuel production and designing nanoscale sensors. Dr. Ulissi has contributed to projects funded by the Scott Institute for Energy Innovation, including green chemistry initiatives aimed at reducing industrial emissions. He actively engages in academic discourse on energy innovation and reaction kinetics, as noted in Engineering & Technology Magazine. His work emphasizes cross-disciplinary collaboration, particularly in integrating machine learning with chemical engineering to address energy challenges.

• Catalysis
• Surface Science
• Energy Science
• +۳ مورد دیگر

Shawn Litster is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University, where he leads cutting-edge research in sustainable energy conversion technologies. He is affiliated with the Wilton E. Scott Institute for Energy Innovation and serves as a Scott Institute Energy Fellow, contributing to major national initiatives in hydrogen and fuel cell systems. His work is supported by significant funding from the U.S. Department of Energy (DOE), ARPA-E, and the Office of Naval Research. Education: Ph.D. in Mechanical Engineering, Stanford University (2008) Master of Applied Sciences, University of Victoria (2005) Bachelor of Engineering, University of Victoria (2004) His research focuses on micro- and nanoscale transport phenomena in electrochemical energy systems such as fuel cells, batteries, and electrolyzers. Key interests include electrochemistry, multiphase flow in porous media, microfluidics, catalytic gasification, and computational fluid dynamics . He pioneers innovations in ionomer-free electrodes, high-oxygen-permeability materials, and low-iridium anodes to improve efficiency, durability, and cost-effectiveness. His recent publications (2021–2025) reveal a strong trend toward advanced diagnostics, operando characterization, machine learning integration, and multiscale modeling of fuel cell and electrolyzer systems. These works emphasize performance optimization, degradation analysis, and material innovation for heavy-duty and transportation applications. Scientific Awards: George Tallman Ladd Research Award, Carnegie Mellon University National Science Foundation CAREER Award Lieutenant Governor’s Silver Medal, University of Victoria Best Paper/Presentation Award, The Electrochemical Society Best Paper/Presentation Award, American Society of Mechanical Engineers (ASME) Litster has secured over $50 million in research funding as a sub-awardee in DOE hydrogen projects and led a $3.2M ARPA-E OPEN 2021 project on disruptive fuel cell electrodes. He is an inventor on two U.S. patents related to fuel cell design. He advises graduate students and leads the Laboratory for Transport Phenomena in Energy Systems , where his team develops novel materials and diagnostics for next-generation energy technologies.

• Energy Conversion Technologies
• Fuel Cells
• Batteries
• +۱۵ مورد دیگر

Dr. Gerald Wang is an Assistant Professor in Civil and Environmental Engineering at Carnegie Mellon University with courtesy appointments in Chemical Engineering and Mechanical Engineering. He leads the M5 Lab (Mechanics of Materials via Molecular and Multiscale Methods), focusing on nanoscale mechanics using computational approaches to solve civil engineering challenges related to water-energy systems, material resilience, and sustainable polymers. Education: Ph.D. in Mechanical Engineering and Computation, MIT (2019) S.M. in Mechanical Engineering, MIT (2015) B.S. in Mechanical Engineering, Mathematics & Physics, Yale University (2013) His research integrates statistical physics, fluid mechanics, and high-performance computing to investigate nanoscale structural and transport phenomena. Key areas include climate-resilient infrastructure, energy-water nexus solutions, and nanoscale thermal transport in materials. Recent work explores molecular-scale separation processes and recyclable polymer design using advanced simulation techniques. Publication trends demonstrate consistent focus on nanoscale transport mechanisms, computational method development, and interdisciplinary applications from materials science to urban systems. Articles frequently bridge molecular dynamics with macro-scale engineering problems. Awards: Scott Institute Seed Grant for clean energy research CMU Celebration of Education Award for teaching excellence Current projects include NSF-funded work on nanoscale slip phenomena and polymer upcycling collaborations. The M5 Lab develops open-source simulation tools and maintains active industry partnerships in advanced materials.

• Nanoscale Transport Phenomena
• Fluid Mechanics
• High-Performance Computing
• +۵ مورد دیگر

Huaiying Zhang is an Assistant Professor in the Department of Biological Sciences at Carnegie Mellon University, part of the Mellon College of Science. His research focuses on the role of biomolecular condensates in cellular functions and cancer progression, particularly investigating phase transitions in telomere maintenance and cancer cell immortality. He holds a Ph.D. from McGill University and completed postdoctoral research at Dartmouth College, Princeton University, and the University of Pennsylvania. Research interests include engineering synthetic organelles, developing optogenetic tools to manipulate phase separation in live cells, and targeting phase transitions for cancer therapy. His work bridges biophysics, cell biology, and synthetic biology to address fundamental questions in nuclear organization and disease mechanisms. Education: Ph.D., McGill University Postdoctoral Fellowships: Dartmouth College, Princeton University, University of Pennsylvania Publications highlight advances in understanding telomere clustering in cancer cells, nuclear body formation, and applications of phase separation in therapeutic strategies. Collaborative projects emphasize interdisciplinary approaches, combining experimental and theoretical methods. Lab activities focus on biomolecular condensates' material properties, their roles in genomic processes, and translational applications in cancer treatment. The lab actively seeks students and researchers interested in cellular biophysics and disease biology.

• Biomolecular Condensates
• Cancer Biology
• Cellular Functions
• +۳ مورد دیگر

Carmel Majidi is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering. He leads the Soft Machines Lab, where his research focuses on soft robotics, wearable computing, and advanced materials that mimic biological systems. His work enables robots and machines to safely interact with humans through soft, deformable technologies. Education: Ph.D. in EECS, University of California, Berkeley (2007) B.S. in Civil and Environmental Engineering, Cornell University (2001) His research interests span soft robotics, stretchable electronics, liquid metal materials, and bio-inspired engineering. He develops soft electromechanical materials for applications in haptics, medical devices, and human-machine interfaces. His group pioneers fabrication methods for soft composites and microfluidic systems that function as artificial skin, nervous tissue, and muscle. The recent trend in his publications highlights a strong focus on soft actuators, self-healing materials, liquid metal composites, and haptic interfaces for virtual and augmented reality. His work integrates materials science, robotics, and advanced manufacturing to enable scalable, robust, and practical soft systems. Scientific Awards: 2023 Inno Fire Award for Trailblazing Innovators, Pittsburgh Business Times Majidi leads a major research thrust in a new NSF Engineering Research Center (ERC) dedicated to improving robot dexterity, funded up to $52 million. He has been instrumental in developing soft robotic systems inspired by prehistoric organisms, such as the pleurocystitid, and in creating healthcare devices powered by body heat using liquid metal technologies. His research has been featured in Popular Science , Communications of the ACM , and Ars Technica . He is actively involved in advancing scalable manufacturing of soft electronics and enabling robust integration between soft materials and conventional microelectronics. His lab collaborates across disciplines to push the boundaries of physical AI and wearable robotics.

• Soft Robotics
• Wearable Robotics
• Soft Electronics
• +۱۲ مورد دیگر

Subha R. Das is an Associate Professor of Chemistry at Carnegie Mellon University's Mellon College of Science. His research focuses on nucleic acid-polymer biohybrids, nanobiotechnology, and automated science. He holds a Ph.D. from Auburn University (2000) and has been on the faculty since 2006. Key projects include engineering DNA/RNA nanostructures, developing click-chemistry tools for RNA labeling, and creating exosome-polymer hybrids for biomedical applications. His research interests span organic chemistry, biomaterials, and nanotechnology. Notable contributions include backbone-branched DNA/RNA design for precise nanostructure assembly and RNA lariat synthesis to study splicing mechanisms. He also pioneered the Kitchen Chemistry Sessions course, linking molecular gastronomy to chemistry education. Education: Ph.D. in Chemistry (Auburn University, 2000), M.S.C. in Chemistry (BITS Pilani, 1994), B.E. in Computer Science (BITS Pilani, 1994) Key Research Themes: Nucleic acid-polymer hybrids, automated polymer synthesis, RNA nanotechnology, biomaterials for drug delivery Recent Trends in Publications: Focus on ATRP-driven biohybrid systems, RNA functionalization, and exosome engineering His lab collaborates extensively with the Matyjaszewski group on controlled radical polymerization techniques and has developed novel methods for biomolecule-polymer integration. Research spans from fundamental nucleic acid chemistry to applied biomedical systems.

• Organic Chemistry
• Nucleic Acids Chemistry
• Polymer Hybrids
• +۵ مورد دیگر

Olexandr Isayev is the Carl and Amy Jones Professor of Chemistry at the Department of Chemistry, Carnegie Mellon University (CMU), within the Mellon College of Science. He holds affiliate roles at the Scott Institute for Energy Innovation and the CMU-Pitt Computational Biology Program. His research focuses on applying artificial intelligence (AI), machine learning (ML), and computational chemistry to solve complex problems in drug discovery, materials science, and quantum mechanics. Notable collaborations include work with the CMU Cloud Lab and the development of the AIMNet2 molecular potential. Education: Postdoctoral Fellow at Case Western Reserve University (2009–2012), PhD in Theoretical Chemistry from Jackson State University (2008), M.S. in Chemistry from Dnepropetrovsk National University (2002). His research interests span generative AI for molecular design, ML-driven chemical intuition, and autonomous experimental platforms. Key achievements include groundbreaking work on universal ML potentials for quantum mechanics and GenAI methods for inverse molecular design. Awards include the Scialog Fellowship (2023) and NVIDIA GPU Computing Award (2014). Future goals aim to advance 'Chemical Intelligence' by integrating AI with expert decision-making frameworks. Awards: Scialog Fellow (2023) ACS Emerging Technology Award (2017, 2014) Eshelman Institute for Innovation Award (2016) Labs/Teams: Directs the Isayev Lab, which pioneers AI-driven molecular discovery through synergies between automated experiments and ML agents.

• Machine Learning
• Computational Chemistry
• Drug Discovery
• +۷ مورد دیگر

Hamish Gordon is an associate professor in the Department of Chemical Engineering and the Center for Atmospheric Particle Studies at Carnegie Mellon University (CMU). He holds affiliations with the Wilton E. Scott Institute for Energy Innovation and has been at CMU since 2019, following postdoctoral work at the University of Leeds. His research focuses on aerosol-cloud interactions, climate modeling, and air pollution impacts, leveraging advanced computational tools like the UK Met Office Unified Model. Education: Ph.D. in Physics, University of Oxford (2013) M.S. in Natural Sciences, University of Cambridge (2010) B.A. in Natural Sciences, University of Cambridge (2009) Research Interests: Dr. Gordon investigates how atmospheric particles influence weather and climate through interactions with clouds. Key areas include aerosol formation mechanisms (e.g., sulfuric acid and organic compounds), the role of anthropogenic and natural sources in climate feedbacks, and fog/visibility modeling. His work integrates laboratory experiments (e.g., CERN CLOUD project) with field campaigns (e.g., South Atlantic smoke studies). Publications & Grants: Recent studies address aerosol impacts on tropical cyclones, biomass burning radiative effects, and Delhi fog forecasting. He has secured NSF CAREER awards and DOE funding, collaborating with institutions like NASA and the National Center for Medium Range Weather Forecasting (India). Awards: NSF Faculty Early Career Development (CAREER) Award (2023) Lab Team & Outreach: The Gordon Group includes postdocs and Ph.D. students working on aerosol modeling, climate dynamics, and AI integration. Outreach efforts focus on STEM education and community engagement, including mentoring programs and public speaking on environmental issues.

• aerosol-cloud interactions
• air pollution
• climate modeling
• +۵ مورد دیگر

Marcel Just is the D.O. Hebb University Professor of Psychology and Biomedical Engineering at Carnegie Mellon University, where he also serves as the Director of the Center for Cognitive Brain Imaging. His academic journey began with a B.Sc. in Honors Psychology from McGill University in 1968, followed by a Ph.D. from Stanford University in 1972. Over his distinguished career, Just has pioneered the application of fMRI technology to investigate the neural basis of cognitive processes. His research focuses on understanding how concepts are neurally represented in the brain, with particular emphasis on: How familiar and technical concepts are represented through fMRI-measured brain activation patterns The decomposition of these patterns into meaningful components (e.g., how motor regions represent the action of holding an apple) Applications for diagnosing psychiatric illnesses by detecting alterations in concept representations Assessing how students learn new technical concepts in educational settings Just's work has made significant contributions to both conceptual and language processing research (funded by ONR and NIMH grants) and autism research (funded by NICHD). His laboratory developed the influential frontal-posterior underconnectivity theory of autism, which has shaped understanding of neural connectivity differences in autism spectrum disorders. His research employs machine learning and dimension reduction techniques applied to fMRI data, bridging cognitive psychology with advanced neuroimaging methodologies. This interdisciplinary approach has yielded insights across multiple domains including language comprehension, visual thinking, problem-solving, working memory, social judgment, and multi-tasking. Among his notable scientific awards are: Appointment as University Professor at Carnegie Mellon (2013) Distinguished Scientific Contribution Award from the Society for Text & Discourse (2012) Outstanding Research Award from the Advisory Board on Autism and Related Disorders (2001) NIMH Senior Scientist Award (1997) Throughout his career, Just has mentored numerous researchers and collaborated extensively with colleagues across disciplines. His work has been supported by multiple grants from organizations including the Office of Naval Research (ONR), National Institute of Mental Health (NIMH), and National Institute of Child Health and Human Development (NICHD). These collaborations have led to innovative applications of neuroimaging in understanding both typical cognitive processes and clinical conditions. At the Center for Cognitive Brain Imaging, Just leads a multidisciplinary team that combines expertise in psychology, neuroscience, biomedical engineering, and machine learning to advance the field of cognitive neuroimaging. The center serves as a hub for cutting-edge research that continues to deepen our understanding of the relationship between brain activity and cognitive processes.

• Cognitive Neuroscience
• fMRI Brain Imaging
• Neural Representation of Concepts
• +۳ مورد دیگر