جستجوی استاد راهنمای دانشگاهی

Jason Congمشاهده پروفایل

استاد

• Electronic Design Automation
• VLSI CAD
• FPGA Synthesis
• +۶ مورد دیگر

Jason Cong is the Volgenau Chair for Engineering Excellence and Distinguished Chancellor's Professor in the Computer Science Department at UCLA's Samueli School of Engineering. He directs the Center for Domain-Specific Computing (CDSC) and the VLSI Architecture, Synthesis, and Technology (VAST) Laboratory, and serves as Associate Vice Provost for Internationalization and Co-Director of UCLA/PKU Student and Scholar Program. Dr. Cong's research spans electronic design automation, customizable computing for machine learning and big-data applications, quantum computing, and highly scalable algorithms. His work has produced over 500 publications with more than 41,000 citations and an H-index of 106. His recent work focuses on quantum computing compilation, domain-specific acceleration for AI workloads, and high-level synthesis optimization techniques that leverage machine learning. His publication trend shows a strong emphasis on quantum computing and machine learning acceleration in recent years, with numerous papers on quantum layout synthesis, LLM acceleration, and high-performance FPGA implementations. His team has developed frameworks like TAPA for task-parallel dataflow programming and RapidStream for automated parallel implementation of FPGA designs. Member of National Academy of Engineering (2017) IEEE Robert N. Noyce Medal recipient (2022) Phil Kaufman Award recipient (2024) ACM Chuck Thacker Breakthrough Award recipient (2024) 18 Best Paper Awards across major conferences Multiple 10-Year Retrospective Most Influential Paper Awards Dr. Cong has graduated 50 PhD students, many of whom are now faculty at major research universities or hold key positions at leading tech companies. He has led over 100 research projects funded by DARPA, NSF, SRC, and industry sponsors. His entrepreneurial activities include founding three successful companies (Aplus Design Technologies, AutoESL, and Falcon Computing Solutions), all acquired by major EDA players. His VAST Laboratory continues to push boundaries in domain-specific computing, with active research in quantum computing, AI acceleration, and high-performance FPGA implementations.

W. Hong Yeoمشاهده پروفایل

استاد

• Flexible Electronics
• Human Augmentation
• Micro and Nano Device Engineering
• +۶ مورد دیگر

W. Hong Yeo is a Professor in the Woodruff School of Mechanical Engineering and Program Faculty in Bioengineering at the Georgia Institute of Technology, where he also directs the WISH Center. He holds adjunct appointments in the Wallace H. Coulter Department of Biomedical Engineering. Previously, he was an Assistant Professor at Virginia Commonwealth University (2014-2016) and a postdoctoral fellow at the University of Illinois Urbana-Champaign's Beckman Institute. Dr. Yeo's research integrates nanomechanics, soft materials, and nano-microfabrication to develop bio-interfaced systems. Key areas include: Flexible Bioelectronics : Wearable/implantable sensors for health monitoring Human-Machine Interfaces : Neural prosthetics and soft robotics Translational Nanoengineering : Nanoparticle biosensing and diagnostics His publications (2023-2025) demonstrate strong focus on wireless health technologies, including multi-modal wearable systems, implantable sensors for cardiovascular/neurological monitoring, and AI-integrated diagnostics. Trends show increasing emphasis on closed-loop therapeutic systems and scalable manufacturing. Awards & Recognition : BMES Innovation and Career Development Award Virginia Commercialization Award Blavatnik Award Nominee NSF Summer Institute Fellowship Research funding sources include MEDARVA Foundation, NIH, DARPA, and industry partners like CooperVision. He leads the Center for Human-Centric Interfaces & Engineering , developing next-generation bio-interfaced systems.

Timothy Oleksiakمشاهده پروفایل

دانشیار

• Rhetorical theory
• Queer feminist rhetorics
• Rhetoric and composition pedagogy
• +۳ مورد دیگر

Timothy Oleksiak is an Associate Professor in the Department of English at UMass Boston, specializing in rhetorical theory , queer feminist rhetorics , and rhetoric and composition pedagogy . His research explores intersections of queer theory, writing pedagogy, and digital communication, with a focus on peer review practices and power dynamics in educational settings. Education: PhD, University of Minnesota MA, The University of West Florida BS, Eastern Michigan University Research Trends: His recent publications examine themes of consent , queer generativity , and slow scholarship in writing studies. He integrates critical discourses on LGBTQ+ representation, digital culture, and affect theory into pedagogical frameworks. Scientific Awards & Service: Co-Chair, CFSHRC Taskforce on Share Values (2022-2023) Chair, Lavender Rhetoric Award Committee (2020, 2023) RSA Proposal Mentor Program (2022) CCCC Executive Committee (2021-2024) Teaching & Professional Contributions: He teaches graduate courses on queer rhetorics, peer review theory, and digital writing, alongside undergraduate courses in composition and professional writing. His editorial service spans journals like Peitho and QED , emphasizing feminist and LGBTQ+ scholarship.

• Control Theory
• Machine Learning
• Nonlinear Estimation
• +۶ مورد دیگر

Prashant Mehta is a Professor of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign , affiliated with the Coordinated Science Laboratory . His research focuses on controlled interacting particle systems and machine learning applications , particularly in human activity recognition using motion sensors. Education: Ph.D. in Mathematics, Cornell University (2004) M.S. in Electrical & Computer Engineering, University of Massachusetts Amherst (1996) B.E. in Electrical & Electronics Engineering, Birla Institute of Technology & Sciences (1993) Mehta's work has pioneered the feedback particle filter (FPF) algorithm for nonlinear estimation, applied in robotic systems and gesture recognition. His research spans control of combustion instabilities in jet engines, mean-field games , and dynamical systems in aerospace engineering. His publications emphasize nonlinear control theory and stochastic filtering , with recent trends in sensor data pattern recognition and cyber-physical systems . He has received multiple scientific awards , including the MURI award for the Cyberoctopus project and Excellence in Undergraduate Advising Awards . Scientific Honors: MURI Award (2019) for Cyberoctopus Excellence in Undergraduate Advising (2010, 2008) Outstanding Teaching Assistant Award (1994) Senior Member, IEEE Control Systems Society Member, ASME Energy Systems Subcommittee Member, SIAM Dynamical Systems Group Mehta has supervised students like Jin Kim (IEEE CDC Best Student Paper, 2019) and co-founded the startup Rithmio , acquired by Bosch Sensortec . His laboratory develops gesture-detection filters for applications in soft robotics and human-machine interfaces .

Miroslav Pajicمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Embedded Systems
• Artificial Intelligence
• +۶ مورد دیگر

Miroslav Pajic serves as a Professor in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. He also holds joint appointments as Associate Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science and Associate Professor of Computer Science. As Director of Master's Studies, he oversees the graduate program in Electrical and Computer Engineering and teaches numerous courses spanning embedded systems, cyber-physical systems design, and robotics. Education: Ph.D. in Electrical and Computer Engineering from University of Pennsylvania (2012) Miroslav Pajic's research focuses on the design and analysis of cyber-physical systems (CPS) with varying levels of autonomy and human interaction. His work spans the intersection of embedded systems, artificial intelligence, machine learning, control theory, formal methods, and robotics. He specializes in developing high-assurance autonomous systems with applications in robotics, automotive systems, and medical devices, with particular emphasis on CPS security and resilient autonomy. His research addresses fundamental challenges in creating systems that can operate reliably in uncertain environments while maintaining security against potential cyber attacks. Analysis of Pajic's recent publications reveals a strong interdisciplinary research program bridging theoretical foundations with practical applications. His work spans secure sensor fusion for distributed autonomy, medical applications of CPS (particularly deep brain stimulation for neurological disorders), and innovative sensing technologies for autonomous vehicles. A significant portion of his research addresses security challenges in cyber-physical systems, including stealthy GPS attacks on UAVs and methods for attack-resilient state estimation. His publications increasingly integrate machine learning techniques with traditional control theory to create more adaptive and robust autonomous systems. Pajic actively mentors graduate students and leads research groups focused on cyber-physical systems security and high-assurance autonomy. His research is supported by multiple grants, including the NSF AI Institute for Edge Computing (Athena), which he co-leads. He has received funding from various sources to support his work on secure and resilient cyber-physical systems, medical device security, and autonomous vehicle technologies. Pajic collaborates extensively with medical researchers on applications of cyber-physical systems in healthcare, particularly in deep brain stimulation for neurological disorders. His work bridges the gap between theoretical control systems and practical implementations in safety-critical domains, with a growing emphasis on translating research into real-world applications that improve system security and reliability.

• statistical machine learning
• optimization
• sparse methods
• +۵ مورد دیگر

Francis Bach is a Professor and researcher at INRIA, leading the SIERRA project-team since 2011, which is part of the Computer Science Department at Ecole Normale Supérieure (ENS) within PSL Research University. His work bridges CNRS, ENS, and INRIA as a joint research effort. Elected to the French Academy of Sciences in 2020, he currently runs the ERC project SEQUOIA following his previous ERC project SIERRA (2009-2014). His research spans statistical machine learning with focus on optimization, sparse methods, kernel-based learning, neural networks, graphical models, and signal processing. Bach completed his Ph.D. in Computer Science at U.C. Berkeley under Professor Michael Jordan, followed by work at Ecole des Mines de Paris and the WILLOW project-team at INRIA/ENS/CNRS (2007-2010). His recent book "Learning Theory from First Principles" was published by MIT Press in December 2024. Bach's publication record shows consistent high-impact contributions across machine learning theory and applications, with recent work focusing on conformal prediction, diffusion models, optimization theory, and learning theory foundations. His research demonstrates strong connections between theoretical guarantees and practical algorithms, with applications spanning generative modeling, robust optimization, and statistical inference. Elected to French Academy of Sciences (2020) ERC project SIERRA (2009-2014) ERC project SEQUOIA (current) Author of "Learning Theory from First Principles" (MIT Press, 2024) Bach actively mentors numerous PhD students and postdocs, with many alumni now holding faculty positions at institutions like EPFL, Ecole Polytechnique, University of Washington, and University of Montreal. His teaching includes advanced courses on learning theory at ENS's Master's programs. He regularly presents tutorials at major conferences including COLT, NeurIPS, and ICML, demonstrating his leadership in the theoretical machine learning community.

• Econometric Theory
• Machine Learning/Nonparametrics
• Robust Inference for Clustered & Network Data
• +۶ مورد دیگر

Harold D. Chiang is an Assistant Professor in the Department of Economics at the University of Wisconsin-Madison. His research focuses on econometric theory and methods, particularly robust inference techniques for clustered and network data, machine learning applications, and causal inference frameworks like regression discontinuity/kink designs. He employs computational statistics and asymptotic theory to address methodological challenges in high-dimensional and complex datasets.

Rahul Sarpeshkarمشاهده پروفایل

استاد

• Analog synthetic biology
• Quantum circuit design
• Feedback control systems
• +۶ مورد دیگر

Rahul Sarpeshkar is a Professor of Engineering, Microbiology & Immunology, Physics, and Molecular & Systems Biology at Dartmouth College, holding the Thomas E. Kurtz Professorship and chairing the Neukom Computational Science Cluster. His research bridges analog circuits with quantum physics, synthetic biology, and ultra-low-power systems. BS in Electrical Engineering and Physics from MIT (1995) PhD in Computation and Neural Systems from Caltech (1998) His research focuses on analog synthetic biology , quantum circuit design , and bio-inspired supercomputing , emphasizing noise, thermodynamics, and energy efficiency. He develops cytomorphic chips to model biochemical networks and quantum-inspired circuits for spectrum analysis. Recent work integrates quantum and classical computation for biological simulations, drug cocktail formulation , and ATP energy measurement in living cells. Patents highlight innovations in quantum emulation and medical devices. Scientific awards include: Fellow, National Academy of Inventors (2018) IEEE Fellow (2018) NSF CAREER Award ONR Young Investigator Award Packard Fellow Award Junior Bose Teaching Award, MIT He leads a wet lab for synthetic microbial circuit implementation and a dry lab for quantum and nanoelectronics, mentoring a multidisciplinary team of physicists, bioengineers, and computer scientists.

Pekka Marttinenمشاهده پروفایل

دانشیار

• Machine Learning
• Large Language Models
• Reinforcement Learning
• +۸ مورد دیگر

Pekka Marttinen is a tenured Associate Professor of Machine Learning at Aalto University, Department of Computer Science, and leads the Machine Learning for Health (Aalto-ML4H) group within the Helsinki Institute for Information Technology HIIT. Education: M.Sc. in Applied Mathematics, University of Helsinki (2004) Ph.D. in Statistics, University of Helsinki (2008) Title of Docent in Information and Computer Science, Aalto University (2015) Research Focus: His methodological work spans large language models, reinforcement learning, deep learning, probabilistic machine learning, and causal inference . These techniques are applied to critical domains of healthcare, bioinformatics, statistical genetics, epidemiology, and personalized medicine . The group develops novel algorithms, theoretical guarantees, and open-source software that enable data-driven discovery and decision-making in medicine and biology. Publication Trends: Across 2022-2024 the lab has concentrated on (i) rigorous causal reasoning over temporal clinical data, (ii) principled uncertainty quantification in LLMs, (iii) representation learning for neural network comparison, and (iv) translational projects that turn raw EHRs into actionable clinical insights. Earlier work integrated high-dimensional genomics with metabolomics and mapped evolutionary forces in bacterial pathogens. Scientific Awards & Recognition: While no specific awards are listed, his sustained publication record in top-tier venues (NeurIPS, ICML, AISTATS, Nature Genetics, PLOS CB) and his role as responsible professor of the Machine-Learning, Data-Science and AI major signify significant peer recognition. Advising & Grants: Prof. Marttinen currently mentors 8 PhD students as primary supervisor and an additional 7 PhD students as co-supervisor. He has already graduated 8 PhDs since 2014. The group is supported through competitive funding including the Finnish Center for Artificial Intelligence (FCAI) doctoral program. Labs & Teams: He directs the Machine Learning for Health (Aalto-ML4H) research group, comprising postdocs Hans Moen, Ti John, Alexander Nikitin, Negar Safinianaini, Linli Zhang, Zhiyuan Li, and the above-mentioned PhD cohort.

Kamil Glinkaمشاهده پروفایل

دانشیار

• public governance
• local development
• urban policy
• +۵ مورد دیگر

Kamil Glinka is an Associate Professor and Deputy Director of the Institute of Political Science for Science and Development at the University of Wrocław, specializing in public governance, urban policy, and political marketing. His work focuses on municipal self-governments in Visegrad Group countries and their responses to crises like the COVID-19 pandemic. His research interests span public governance , theory and practice of local development , urban policy , public communication , and political and territorial marketing . Glinka examines how cities navigate crises, implement strategic planning, and develop effective communication strategies with citizens. His recent publications reveal a strong focus on urban responses to the pandemic across Visegrad countries, with particular attention to municipal governance models, post-pandemic recovery strategies, and the impact of crises on urban democracy. His work bridges theoretical frameworks with practical policy applications in Central and Eastern Europe. Scientific Awards: Visegrad Fellowship Program (2024) laureate Multiple Rector's Awards from University of Wrocław (2020-2024) for scientific, teaching, and organizational achievements Bernard Steinacher Fellowship 2022-2023 from METREX Network IDUB program awards for academic excellence Glinka leads numerous international research projects including 'Urban Post-COVID Recovery in the V4 Countries' (2022-2025), 'Urban energy transition in Czechia' (2025), and 'Urban policy under ten pressure of the crisis' (2024). His work involves substantial collaboration with institutions across Visegrad countries and beyond. As a member of the Steering Committee of the European Consortium for Political Research's Standing Group on Central and East European Politics and active participant in METREX and IPSA, Glinka contributes significantly to international academic networks focused on urban governance and political science.

Raphael Franziniمشاهده پروفایل

دانشیار

• Drug Discovery
• Medicinal Chemistry
• Bioorthogonal Chemistry
• +۳ مورد دیگر

Raphael Franzini serves as Associate Professor of Medicinal Chemistry at the University of Utah, actively contributing to the Biological Chemistry PhD Program. His research pioneers innovative chemical approaches for therapeutic development, with dual focus on DNA-encoded library technologies and bioorthogonal drug delivery systems. His educational foundation includes an M.S. from the Swiss Federal Institute of Technology (Lausanne) and a Ph.D. from Stanford University. This training underpins his group's multidisciplinary methodology combining organic synthesis, bioconjugation, computational modeling, and advanced imaging techniques. Dr. Franzini's research program centers on two transformative areas: First, advancing DNA-encoded library screening through computational integration to identify leads for challenging targets like Tankyrase and Sirtuin 6, with recent work addressing false negatives in machine learning prediction. Second, developing novel bioorthogonal release chemistry using isonitrile-tetrazine reactions for spatiotemporally controlled drug activation, validated in zebrafish models. His group emphasizes both technological innovation and therapeutic translation, with chemistry designed to minimize off-target effects in solid tumors. Analysis of his 15 most recent publications reveals escalating integration of computational methods with experimental library screening, alongside refinement of bioorthogonal release kinetics. The work spans chemical biology, medicinal chemistry, and pharmaceutical sciences, with growing emphasis on machine learning for library data interpretation and in vivo validation of drug-release systems. Dr. Franzini maintains an active research laboratory that provides comprehensive training in cutting-edge drug discovery methodologies. His group culture prioritizes both scientific innovation and researcher development, with projects spanning from fundamental reaction kinetics to therapeutic applications. The lab's infrastructure supports organic synthesis, molecular imaging, and computational analysis for advancing precision therapeutics.

Brett Sandersمشاهده پروفایل

استاد

• Flood modeling and prediction
• Coastal and urban flooding
• Hydrological modeling
• +۷ مورد دیگر

Brett Sanders is a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on developing innovative algorithms for flow and transport in river and coastal systems and integrating information technologies to create more accurate and efficient simulation tools for flood hazard assessment. His primary research interests include: Flooding and erosion hazards, particularly coastal flooding and urban flooding Surface water quality Low impact development impacts on hydrology Dam-break flooding Aerial and terrestrial lidar scanning Geographical information systems High performance computing for simulation tools Social dimensions of flood risk and adaptation behaviors Dr. Sanders' recent publications (2024-2025) reveal a comprehensive research program addressing both technical and social aspects of flood risk. His work spans computational hydrodynamics, flood hazard mapping, infrastructure vulnerability assessment, and the socioeconomic dimensions of flood risk. He has made significant contributions to understanding multi-grid modeling of urban flooding, post-fire flood hazards, satellite-based monitoring of land motion, and social inequalities in flood exposure. His research demonstrates how flood dynamics are more complex than simple bath-tub filling models suggest, with important implications for urban planning and climate adaptation. Dr. Sanders has received recognition as a Chancellor's Professor at UC Irvine, indicating distinguished scholarly achievement. His educational background includes: Ph.D. in Civil Engineering from the University of Michigan (1997) M.S. in Civil Engineering from the University of Michigan (1994) B.S. in Civil Engineering from the University of California, Berkeley (1993)

Cora Schmidt-Ottمشاهده پروفایل

پژوهشگر

• Intellectual History
• Political History
• 20th Century History
• +۳ مورد دیگر

Cora Schmidt-Ott is a Postdoctoral Researcher at the Chair of Modern and Contemporary History (Prof. Dr. Jan Eckel) at the University of Freiburg . Her work focuses on the intellectual biography of Samuel P. Huntington and the broader intellectual history of the 20th century, particularly in relation to political stability, globalization, and the American Century. She collaborates with institutions like the German Historical Institute, Washington DC , and has led DFG-funded projects. Education: MA in Comparative Modern History (University of Freiburg & University of Bologna); BA in History and American Studies (University of Freiburg & Connecticut College) Her research explores the intersections of political theory, Cold War liberalism, and transnational historical processes, with a particular emphasis on Huntington's influence on postcolonial state-building and global order. She has contributed to debates on migration, museum narratives, and post-war societal transformations. Recent publications and lectures highlight her expertise in political history, American studies, and Cold War-era intellectual networks. She has received scholarships from the Bavaria Graduation Scholarship , Max Weber Fellowship , and Erasmus Program , among others. Scientific Awards: Bavaria Graduation Scholarship (2016) Max Weber Fellowship (2015) Erasmus Scholarship (2013) Baden-Württemberg Scholarship (2011) Cora Schmidt-Ott contributes to academic discourse through her leadership in workshops, teaching roles in seminars on decolonization and 20th-century history, and her ongoing project funded by the German Research Foundation on Samuel Huntington's intellectual legacy.

Hedvig Kjellströmمشاهده پروفایل

استاد

• Computer Vision
• Artificial Intelligence
• Human-Computer Interaction
• +۶ مورد دیگر

Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.

• Artificial Intelligence
• Marketing Analytics
• Digital Marketing
• +۴ مورد دیگر

Natasha Zhang Foutz is a Research Associate Professor of Commerce at the McIntire School of Commerce, University of Virginia . Her work bridges Artificial Intelligence , Marketing Analytics , and Consumer Behavior , with a focus on Digital Content and Location-Based Services . She teaches Marketing Analytics , Entertainment Marketing , and Marketing Models across undergraduate to PhD programs. Ph.D. in Marketing, Cornell University M.S. in Statistics & Marketing, Cornell University B.S. in Economics, Fudan University Her research investigates: AI-Powered Entertainment Marketing : Using machine learning to analyze consumer behavior in digital content. Privacy and Ethical Data Use : Studying consumer trade-offs between privacy and public good, especially during crises like the COVID-19 pandemic . Location Analytics : Leveraging mobile data for urban economics, real estate, and emergency response modeling (e.g., MobiRescue for disaster logistics). Prosocial Consumer Behavior : Exploring how social capital and diversity drive innovation and policy compliance. Recent publications highlight trends in Reinforcement Learning for crisis management, Privacy-Preserving AI , and Freemium Pricing Models in digital markets. Her awards include the 2025 UVA Outstanding Researcher Award and the 2018 Mallen Award for motion picture studies. Natasha serves as an Area Editor for multiple journals, emphasizing Data Science in marketing. She has advised numerous PhD students and collaborated on projects analyzing Big Data in consumer mobility and platform economics.