جستجوی استاد راهنمای دانشگاهی

James C. Hoeمشاهده پروفایل

استاد

• Computer Architecture
• Reconfigurable Computing
• High-Level Hardware Design and Synthesis
• +۴ مورد دیگر

James C. Hoe is Professor of Electrical and Computer Engineering at Carnegie Mellon University (College of Engineering). He is on sabbatical at MangoBoost and directs research in computer architecture, reconfigurable computing, and high-level hardware design. Education Ph.D., Electrical Engineering and Computer Science, MIT (2000) M.S., Electrical Engineering and Computer Science, MIT (1994) B.S., Electrical Engineering and Computer Science, UC Berkeley (1992) Research Interests Professor Hoe’s work spans computer architecture , reconfigurable computing , FPGA architectures , and high-level hardware synthesis . His group created the CoRAM abstraction for virtualized FPGA computing and leads efforts in power-efficient accelerators, in-network computing, and security-oriented FPGA systems. Scientific Awards IEEE Fellow (2013) Intel Outstanding Researcher Award (2021) Research Funding & Projects Intel / VMware Crossroads 3D-FPGA Academic Research Center – co-leading exploration of FPGA roles in future datacenters. DARPA BRASS program ($2.7 M, 4 years) – ensuring long-lived software systems remain robust to resource changes. Pigasus open-source IDS – world’s fastest FPGA-accelerated intrusion-detection system (100 Gb/s on one server). Labs & Teams He heads activities within the Computer Architecture Lab at Carnegie Mellon (CALCM) , supervising graduate researchers on CoRAM++, SPIRAL autotuning, and FPGA overlays for stream processing.

George H. Chenمشاهده پروفایل

دانشیار

• Trustworthy Machine Learning
• Time-to-Event Prediction
• Survival Analysis
• +۳ مورد دیگر

George H. Chen is an Associate Professor at Carnegie Mellon University , with dual affiliations in the Heinz College of Information Systems and Public Policy and the Machine Learning Department . His research focuses on trustworthy machine learning methods for temporal reasoning , particularly in health applications such as time-to-event prediction (survival analysis) and electronic health records analysis . He has extensive experience in nonparametric methods requiring minimal data assumptions. Educational Background PhD in Electrical Engineering and Computer Science, MIT (2015) SM in Electrical Engineering and Computer Science, MIT (2012) BS in Electrical Engineering and Computer Sciences & Engineering Mathematics and Statistics, UC Berkeley (2010) His work spans survival analysis , deep learning , and time series modeling , with applications in neurological prognostication , medical adherence , and health equity . He has developed self-contained educational resources including a 2024 monograph on deep survival analysis and tutorials at CHIL and SIGMETRICS. His 2025 course 95-865: Unstructured Data Analytics focuses on practical unstructured data analysis techniques. Notable projects include advising the AgriTech startup CoolCrop , which provides cold storage and market forecasts for Indian farmers serving 9,000+ farmers across 7 states. His Google Scholar publications reveal a strong focus on temporal modeling in healthcare, with recent advancements in neural survival analysis and fairness-aware temporal prediction.

Franz Franchettiمشاهده پروفایل

استاد

• High-Performance Computing (HPC)
• Parallel Computing
• Algorithm and Hardware Co-Synthesis
• +۵ مورد دیگر

Franz Franchetti is the Kavčić-Moura Professor of Electrical & Computer Engineering at Carnegie Mellon University. He serves as Associate Dean for Research and Director of the Engineering Research Accelerator at CMU. Education: Ph.D. in Computational Mathematics (Vienna University of Technology, 2003) M.Sc. in Technical Mathematics (Vienna University of Technology, 2000) His research interests focus on automatic performance tuning and program generation for emerging parallel computing platforms , including multicore CPUs , GPUs , and 3DIC chip design . He leads the SPIRAL effort to automate highly optimized software libraries and explores domain-specific compiler transformations in HPC applications for smart grids and material sciences . Recent work extends SPIRAL to quantum computing . The scientific awards Franchetti has received include the Gordon Bell Prize (2006) , HPC Challenge Class II Award (2010) , and the CIT Dean's Early Career Fellowship (2013) . He and his students have won multiple Best Paper Awards at HPEC, DAC, and ISPA ACM TODAES Best Paper (2014) Student Research Competition wins (PACT 2024, CGO 2023) Franchetti has advised students like Richard Veras and Thom Popovici . He has secured significant grants from agencies such as DARPA, DOE, NSF, and industry partners (Intel, NVIDIA, Mercury). He co-founded SpiralGen, Inc. and holds leadership roles in organizations like ASciNA Western Pennsylvania and as Honorary Consul of Austria in Pittsburgh.

Fernando De la Torreمشاهده پروفایل

استاد مدعو

• Machine Learning
• Computer Vision
• Augmented Reality
• +۴ مورد دیگر

Fernando De la Torre is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with an affiliation to the Robotics Institute where he has been a research faculty member since 2005. He holds a Ph.D. in Electronic Engineering from Ramon Llull University (2002). His research focuses on machine learning and computer vision, with applications in human health, augmented/virtual reality, generative models, and data-centric methodologies. He directs the Human Sensing Laboratory, which explores technologies for human behavior analysis and health monitoring. Notable contributions include founding FacioMetrics LLC (acquired by Meta), advancing facial recognition and 3D human digitization, and developing frameworks for robust visual models. His work bridges theory and practice, with over 225 peer-reviewed publications and editorial roles, including Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence. Recent research trends emphasize generative AI applications in satellite imagery analysis, VR/AR rendering optimizations (e.g., Gaussian splatting), and clinical motion recognition for healthcare. His projects often intersect with industry, addressing challenges in wearable health monitoring and immersive technologies. His lab collaborations span academia and industry, focusing on scalable solutions for 3D human modeling, adversarial robustness, and multimodal data fusion. Key achievements include pioneering work on 3D face animation from speech and garment reconstruction from single images.

Thomas Sullivanمشاهده پروفایل

استاد آموزشی

• Signal Processing
• Audio Engineering
• Music Technology
• +۴ مورد دیگر

Dr. Thomas Sullivan is a Teaching Professor in the Department of Electrical and Computer Engineering (ECE) at Carnegie Mellon University, with a courtesy Lecturer appointment in the School of Music. He holds a PhD (ECE '96) and BS (EE '85) from Carnegie Mellon and an MS in Computer Music from MIT's Media Lab (MAS '88). His research interests focus on signal processing for music and audio applications, including audio recording advancements, music synthesis, and controller design for synthesizers. He teaches core ECE courses such as Introduction to ECE, Senior Capstone Design, and Electro-acoustics, while also emphasizing STEM outreach for under-represented K-12 students. Education: PhD in Electrical and Computer Engineering, Carnegie Mellon University (1996) MS in Computer Music, MIT Media Lab (1988) BS in Electrical Engineering, Carnegie Mellon University (1985) His work bridges engineering and music technology, contributing to both academic and industry applications. Sullivan actively promotes STEM engagement through outreach programs and is involved in interdisciplinary initiatives like the Music Technology BS/MS programs. Outside academia, he enjoys music performance as an amateur guitarist/bassist, ice hockey, and distance running.

Mayank Goelمشاهده پروفایل

استادیار

• Mobile Computing
• Sensing
• Signal Processing
• +۷ مورد دیگر

Mayank Goel serves as an Assistant Professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University's School of Computer Science. His research bridges computer science and societal impact through practical sensing systems that leverage existing environmental devices for health monitoring and human-computer interaction without requiring hardware modifications. Dr. Goel specializes in mobile computing, signal processing, and machine learning to develop unobtrusive health technologies applicable to real-world scenarios. His core research areas include passive activity recognition for chronic disease management (particularly multiple sclerosis), privacy-preserving acoustic sensing, smartwatch-based clinical interventions for post-operative care, and equitable healthcare systems for global development contexts. He emphasizes end-to-end solutions through close collaboration with medical professionals and designers to ensure immediate deployability outside laboratory environments. Analysis of his 2024-2025 publications reveals a strong interdisciplinary focus spanning computer science, biomedical engineering, and clinical practice. Key trends include longitudinal digital phenotyping for neurological conditions, on-device privacy preservation in activity recognition, and multimodal procedural assistance systems. His work consistently addresses real-world challenges in sensor placement flexibility, user adoption barriers, and equitable access to medical technologies. No scientific awards were mentioned in the available documentation. Information regarding student advising, research grants, or laboratory affiliations was not specified in the provided materials, though his publication record indicates active collaboration with medical professionals and bio-engineers for clinical validation of health technologies.

• Audio Signal Processing
• Music Technology
• Digital Audio Recording
• +۲ مورد دیگر

Tom Sullivan is Teaching Professor in Electrical and Computer Engineering and Lecturer in Music at Carnegie Mellon University. His research interests center on signal processing applications for music and audio systems, including digital audio recording technologies, musical instrument synthesis, and controller interfaces for performance systems. Teaches foundational courses including Introduction to Electrical and Computer Engineering, Electro-acoustics, Signals and Systems, and core components of the Music Technology program. Actively involved in STEM outreach initiatives targeting K-12 students from underrepresented communities, demonstrating engineering applications in music and media contexts.

Yiqun Panمشاهده پروفایل

استاد مهمان

• Building Performance Simulation
• Energy Efficiency
• Sustainable Building Design
• +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.

Kevin Zollmanمشاهده پروفایل

استاد

• Game Theory
• Agent-Based Modeling
• Philosophy of Science
• +۵ مورد دیگر

Kevin Zollman is the Herbert A. Simon Professor of Philosophy and Social and Decision Sciences at Carnegie Mellon University, with affiliations as an associate fellow at the University of Pittsburgh's Center for Philosophy of Science and a visiting professor at the Munich Center for Mathematical Philosophy. His work bridges game theory, agent-based modeling, and the philosophy of science. Education: Ph.D. and M.A. in Philosophy, University of California, Irvine B.S. in Philosophy, Kansas State University His research focuses on the intersection of strategic reasoning and social epistemology, including evolutionary dynamics in scientific communities, signaling theory in biological and academic contexts, and computational methods in philosophy. Recent publications examine hybrid equilibria in signaling games, incentives in peer review, and the epistemic consequences of stochasticity. Kevin actively engages in public outreach, co-authoring the popular science book The Game Theorist's Guide to Parenting and contributing to discussions about applying game theory to real-world challenges. Leadership: Director, Institute for Complex Social Dynamics

Haohan Wangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Computational Biology
• Healthcare Applications
• +۵ مورد دیگر

Haohan Wang is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, with affiliations to the Carl R. Woese Institute for Genomic Biology and the National Center for Supercomputing Applications. His research focuses on developing trustworthy machine learning methods for computational biology and healthcare applications , emphasizing robustness , causality , and interpretability in vision-based models. Recent research trends in his work include: Large Language Model interactions with biomedical challenges (GenoAgent, GenoTex) Adversarial security in language and vision models (Guard, Jailbreakzoo) Genomic data analysis through robust machine learning frameworks (Precision Lasso, Kernel Mixed Models) Interactive toolkits like Robustar for data annotation and model training Scientific awards include recognition as Baidu's Top 50 AI+X Rising Young Scholars (2022), Best Paper Honorable Mention at WSDM 2023, and Broad Institute's Next Generation status (2019). Current projects explore AI-made scientists for biomedical discovery and Robustar development for GUI-based robust vision learning.

Douglas Weberمشاهده پروفایل

استاد

• Neural Engineering
• Neuroprosthetics
• Sensory Feedback
• +۱۲ مورد دیگر

Douglas Weber is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), where he leads research at the intersection of neuroscience and engineering. He is a founding member of DARPA’s Biological Technologies Office and has led major neurotechnology programs, including HAPTIX, ElectRx, and TNT. His research is centered at the NeuroMechatronics Lab, with collaborations at the University of Pittsburgh and industry partners like Meta. He is actively engaged in developing neuroprosthetics, spinal cord stimulation, and wearable devices for sensory and motor restoration. Ph.D., Bioengineering, Arizona State University (2001) MS, Bioengineering, Arizona State University (2000) BS, Biomedical Engineering, Milwaukee School of Engineering (1994) Post-doctoral training, Centre for Neuroscience, University of Alberta Douglas Weber's research focuses on understanding sensory feedback in motor control, neuroplasticity, and the development of neurotechnologies for individuals with stroke, spinal cord injury, or limb loss. His work spans neural engineering , biomechanics , neuromodulation , and bioelectronic medicine . He aims to translate academic research into real-world applications, such as brain-computer interfaces and sensory-restoring prosthetics. His lab explores high-density electromyography (HD-sEMG), spinal cord stimulation, and closed-loop systems to enhance human-machine interaction. The recent articles reflect a strong emphasis on spinal cord and peripheral nerve stimulation , brain-computer interfaces , and sensory feedback restoration . Many studies investigate neuromodulation for motor recovery , endovascular BCIs , and non-invasive stimulation techniques . There is a recurring theme of clinical translation , with multiple early feasibility trials and human studies. The work integrates electrophysiology , signal processing , and rehabilitation engineering to improve outcomes for patients with neurological impairments. Douglas Weber has mentored over 100 undergraduate, graduate, and medical students, as well as several postdoctoral fellows. He holds eight issued U.S. patents and has secured significant research funding, including awards from ARPA-H and collaborations with the Pitt CTSI. His work has led to practical technologies aimed at improving independence for individuals with paralysis or limb loss. He is actively involved in several research teams and labs, most notably the NeuroMechatronics Lab at CMU. His team collaborates with institutions like the University of Pittsburgh and industry partners such as Meta to develop wearable interfaces and implantable devices. Projects include wristband-based sEMG control systems, spinal cord stimulation for stroke recovery, and bioelectronic implants for chronic disease management.

Tae Wan Kimمشاهده پروفایل

دانشیار

• Business Ethics
• AI Ethics
• Cross-Cultural Ethics
• +۴ مورد دیگر

Tae Wan Kim is an Associate Professor of Business Ethics at the Tepper School of Business , Carnegie Mellon University, with affiliate roles at CyLab (School of Computer Science) and the Block Center for Technology and Society (Heinz College). His work bridges ethical theory, AI governance, and cross-cultural analysis. Education : PhD in Ethics & Legal Studies (University of Pennsylvania, 2012), BA in Philosophy (Sungkyunkwan University, 2007) Research focuses on AI ethics , data privacy , technological unemployment , and cross-cultural business ethics . He explores the moral implications of automation, algorithmic transparency, and corporate responsibility in AI deployment. His recent publications examine explainable AI, human-AI dialectics, and ethical frameworks for emerging technologies. Key article trends span AI ethics , computational morality , workplace automation , and data governance . Subfields include algorithmic fairness, ethical stakeholder theory, digital labor rights, and human-AI coexistence. Scientific Awards : Fellow, World Economic Forum; Xerox Junior Faculty Chair Editorial leadership includes Editor-in-Chief and Associate Editor roles at Business Ethics Quarterly and multiple editorial board memberships. Professional activities highlight involvement in the IEEE Global Initiative for Ethical Considerations in AI, AAAI/ACM Conference on AI Ethics, and CMU's Responsible AI Initiative.

Alex Hillsمشاهده پروفایل

استاد

• Telecommunications
• Wireless Networking
• Digital Signal Processing
• +۷ مورد دیگر

Alex Hills is a Professor of Engineering and Public Policy at Carnegie Mellon University (CMU), where he has held multiple leadership roles including Vice Provost, Chief Information Officer, and Founding Director of the Information Networking Institute. He led the development of 'Wireless Andrew,' the world's first large-scale Wi-Fi network, pioneering modern wireless campus infrastructure. His research interests include telecommunications, wireless networking, digital signal processing, and technology deployment in remote and developing regions. He focuses on error detection in wireless systems, policy implications of engineering solutions, and using technology for global development. The available article highlights his expertise in how digital networks handle voice data, particularly the causes of robotic distortion in phone calls due to packet corruption and error correction mechanisms. His work bridges engineering and public understanding of digital infrastructure. Distinguished Service Professor at CMU Author of books on Wi-Fi development and connecting remote Alaskan villages Senior advisor to 'Technology Consulting in the Global Community' program Expert quoted in Consumer Reports on telecom issues Alex Hills has advised numerous students through university programs and initiatives, particularly those focused on applying technology in developing nations. He has secured institutional support for global outreach projects and continues to mentor students in interdisciplinary tech-policy work. His career spans academia, government service (including as Alaska’s Deputy Commissioner of Administration), and military leadership. He leads or contributes to teams working on resilient communication networks, especially in underserved areas. His past and ongoing work involves building robust, low-infrastructure telecommunications systems suitable for remote communities and disaster response scenarios.

L. Richard Carleyمشاهده پروفایل

استاد

• Analog Circuit Design
• RF Circuit Design
• MEMS and NEMS Systems
• +۷ مورد دیگر

L. Richard Carley is a Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the Data Storage Systems Center (DSSC). He has been a faculty member since 1984, following his S.B., S.M., and Ph.D. in Electrical Engineering and Computer Science from MIT (1976–1984). His research focuses on analog circuit design, CAD tools for analog synthesis, MEMS systems, and RF circuit design. He co-authored two textbooks and over 200 papers, earning multiple awards including an IEEE Fellowship (1997). Education: Ph.D., Electrical Engineering and Computer Science, MIT, 1984 M.S., Electrical Engineering and Computer Science, MIT, 1978 B.S., Electrical Engineering and Computer Science, MIT, 1976 Research Interests: Development of CAD tools for analog IC design, mixed-signal ICs, RF front-end circuits, and MEMS/NEMS systems. His work emphasizes low-power digital logic, data converters, and signal conditioning for SOC applications. Awards & Professional Contributions: IEEE Fellow (1997) Co-founder of Neolinear (acquired by Cadence in 2004) Editorial board member of Analog Integrated Circuits and Signal Processing Advising & Industry Impact: Advised over 70 graduate students (30+ Ph.D., 40+ M.S.). His patents and industry collaborations, including Neolinear’s analog CAD tools, reflect his translational research impact. Labs & Affiliations: Key contributor to the Center for Circuits and Systems Solutions (C2S2) and DSSC, where he led electronic subsystems as associate director.

Ken Maiمشاهده پروفایل

استاد پژوهش

• High-Performance Circuit Design
• Secure IC Design
• Radiation Hardening
• +۴ مورد دیگر

Ken Mai is a Principal Systems Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.S., M.S., and Ph.D. in Electrical Engineering from Stanford University. His research focuses on high-performance circuit design, secure IC design, radiation hardening, reconfigurable computing, and computer architecture. He has received prestigious awards including the NSF CAREER Award and the George Tallman Ladd Research Award. Education: Ph.D., Electrical Engineering, Stanford University, 2005 M.S., Electrical Engineering, Stanford University, 1997 B.S., Electrical Engineering, Stanford University, 1993 Research Interests: Dr. Mai’s work addresses challenges in nanometer-scale CMOS technology, including interconnect delay, leakage, and soft errors. His projects include secure IC design against hardware attacks, robust memory techniques using digital communications, 100GHz logic via cryogenic cooling, and bio-implantable computing platforms. He collaborates with neurosurgeons at the University of Pittsburgh for medical applications. Key Projects: Secure IC Design: Countermeasures against invasive/non-invasive attacks Robust Memory Design: Error correction codes for resilience 100GHz Logic: Cryogenically cooled CMOS for high-speed applications Bio-Implantable Systems: Low-power, high-density computing for medical devices Awards: NSF CAREER Award George Tallman Ladd Research Award Eta Kappa Nu Excellence in Teaching Award Teaching and Advising: He teaches courses like 18-322 (Digital Circuits), 18-617 (Memory Systems), and advises students including Mudit Bhargava and Mark McCartney. His lab, the VLSI Design Group, develops tools and methodologies linking circuit design to architectural design. Contact: Email: kenmai@ece.cmu.edu Website: Carnegie Mellon VLSI Design Group