Emmett Witchel is a Professor of Computer Science at the University of Texas at Austin , with research spanning computer architecture, systems, networking, security, and privacy . His work focuses on low-level systems optimization and secure concurrent execution. Research Interests: Concurrent systems, secure execution environments, GPU integration, distributed systems. Teaching: CS 380L (Advanced Operating Systems), CS 371M (Mobile Computing). Scientific Awards: Runner-up Best Paper, ASPLOS 2013 Runner-up Award for Outstanding Research, USENIX Symposium 2012 IEEE Micro Top Pick Award 2007 ACM Honorable Mention 2004 George M. Sprowls Award, MIT EECS 2004 Recent Publications demonstrate leadership in CXL pod databases ( Tigon ), stateful serverless computing ( Boki ), SmartNIC-accelerated file systems ( LineFS ), and GPU security ( Telekine ). His work bridges hardware-software co-design and practical systems implementation.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۹۱-۱۰۵ از ۵٬۲۳۲ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Brett Laursen is a Professor of Psychology at Florida Atlantic University's Charles E. Schmidt College of Science, with additional Docent Professor appointments in Educational Psychology at the University of Helsinki and in Social Developmental Psychology at the University of Jyväskylä in Finland. His research focuses on developmental psychology, particularly adolescent development, peer relationships, and social dynamics. Dr. Laursen earned his Ph.D. and M.A. in Child Psychology from the Institute of Child Development at the University of Minnesota and his B.A. in Psychology from Nebraska Wesleyan University. He also holds an Honorary Ph.D. from Örebro University in Sweden. His research program examines influence within close relationships, with particular focus on peer relationships during childhood and adolescence. Current projects include longitudinal studies of elementary and middle school children in Florida, Lithuanian youth transitioning from middle to secondary school, and child characteristics affecting parent engagement in literacy activities. His work consistently explores how social dynamics shape development, with special attention to friendship formation, dissolution, and influence processes. Analysis of his recent publications reveals a strong focus on peer relationships, social status, and developmental transitions. His research employs sophisticated longitudinal and genetically informed designs to examine how social contexts shape development across childhood and adolescence, with particular emphasis on the mechanisms through which peer influence operates. Fellow, American Psychological Association (Division 7, Developmental; Division 8, Social) Fellow and Charter Member, Association for Psychological Science Fellow, International Society for the Study of Behavioural Development Distinguished Alumnus, College of Education and Human Development, University of Minnesota Florida Atlantic University Scholar of the Year (2023-24 and 2016-17) Dr. Laursen has mentored numerous doctoral and master's students who have gone on to successful careers in academia and research. His research has been supported by major funding sources including the US National Institute of Child Health and Human Development, the US National Institute of Mental Health, the US National Science Foundation, Trygfonden, the Jacobs Foundation, and the European Social Fund. As Editor-in-Chief of Merrill Palmer Quarterly and Founding Editor of Cambridge Elements in Research Methods for Developmental Science, he plays a significant role in shaping the field's scholarly discourse. The Laursen Lab operates as a collaborative research team involving current students, alumni, and international collaborators including Professors Goda Kaniušonytė and Rita Žukauskienė of Mykolas Romeris University in Lithuania. The lab regularly presents research at major conferences including the Society for Research on Child Development.
Alan Zaoxing Liuمشاهده پروفایل
استادیار
- Systems
- Networking
- Applied Algorithms
- +۹ مورد دیگر
Alan Zaoxing Liu is an Assistant Professor of Computer Science at the University of Maryland, College Park , with appointments at the University of Maryland Institute for Advanced Computer Studies (UMIACS) and Maryland Cybersecurity Center (MC2) . His research bridges systems, networking, and cybersecurity to design scalable, trustworthy approximate computing systems. Ph.D. in Computer Science from Johns Hopkins University (2018) Postdoctoral research at Carnegie Mellon CyLab (2018–2020) Research Interests : Networked and data-intensive systems Telemetry/analytics for heterogeneous networks Machine learning for network optimization Security in programmable networks Recent Publications include work on future-proof telemetry (PromSketch, VLDB’25), scalable caching (OctoCache, ASPLOS’25), and secure network analytics (TrustSketch, NDSS’24). His NSF-funded projects focus on optics-enabled DDoS defense and data-driven network management. Scientific Awards : USENIX FAST Best Paper (2019) USENIX ATC 'Best of Rest' (2021) Red Hat Collaboratory Research Awards (2022, 2023) Teaching : Leads Cloud Computing at Boston University , emphasizing agile development, open-source collaboration, and cloud infrastructure.
Zsolt Kiraمشاهده پروفایل
استادیار
- Robotics
- Machine Learning
- Artificial Intelligence
- +۶ مورد دیگر
Zsolt Kira serves as an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing, with additional affiliations at the Georgia Tech Research Institute and as Associate Director of ML@GT. He leads the Robotics Perception and Learning (RIPL) Lab, driving research at the intersection of machine learning and robotics. Dr. Kira earned his Ph.D. in 2010 under Professor Ron Arkin, establishing foundational expertise in robotics and AI before transitioning to his current academic role after industry experience at SRI International Sarnoff. His research pioneers beyond supervised learning through unsupervised, semi-supervised, self-supervised, and continual/lifelong learning frameworks, while advancing distributed perception via multi-modal fusion and cross-robot information integration. This dual focus addresses core challenges in robotic autonomy and sensor processing. Analysis of his 15 most recent publications reveals dominant trends in embodied AI systems, robust foundation model adaptation, and multimodal learning architectures. Key themes include neural radiance field applications, reinforcement learning for locomotion, and novel benchmarks for memory evaluation in agents. While specific advisees and grants aren't documented in the source material, his RIPL Lab leadership implies active graduate mentorship and research funding acquisition. The lab's work directly enables next-generation robotic systems through algorithmic innovation in perception and learning. The RIPL Lab operates as a hub for developing machine learning techniques that solve difficult perception problems in robotics, with particular emphasis on unsupervised learning paradigms and distributed multi-robot systems that push the boundaries of autonomous operation.
Feras Dayoubمشاهده پروفایل
مدرس ارشد
- Computer Vision
- Machine Learning
- Robotics
- +۶ مورد دیگر
Dr. Feras Dayoub is a Senior Lecturer at the School of Computer and Mathematical Sciences (Faculty of Sciences, Engineering and Technology) at the University of Adelaide , specializing in Embodied AI and Robotic Vision within the Australian Institute for Machine Learning (AIML) . He co-directs the CROSSING French-Australian laboratory for human-autonomous agent teaming and holds an Adjunct position at the Queensland University of Technology (QUT) , serving as an Associate Investigator at its Centre for Robotics . Previously, he was a Chief Investigator at the ARC Centre of Excellence for Robotic Vision . His research focuses on advancing reliable deployment of computer vision and machine learning on mobile robots in real-world environments. Applied projects include agricultural automation , environmental conservation , and autonomous infrastructure monitoring . He has published extensively on topics like object detection , domain adaptation , 3D representation learning , and vision-language navigation , with a particular emphasis on robustness in dynamic and partially observed environments. Dr. Dayoub is also an educator specializing in programming , computer vision , and robotic perception . He contributes to open-source robotics research through tools like AARK (Autonomous Racing Toolkit) and has led teams developing solutions for precision agriculture (e.g., Deepfruits fruit detection system) and environmental monitoring (e.g., Crown-Of-Thorns starfish detection ). Key Collaborations : CROSSING Lab, QUT Centre for Robotics Research Themes : Embodied AI, Robust Perception, Domain Adaptation
- Nanotechnology
- Nanoelectronics
- Spintronics
- +۵ مورد دیگر
Azad J Naeemi is a Professor holding the Dean's Professorship in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He serves as Editor-in-Chief of the IEEE Journal on Exploratory Computational Devices and Circuits and Associate Director for Computation of the NSF-supported National Nanotechnology Coordinated Infrastructure (NNCI). His educational background includes a B.S. in Electrical Engineering from Sharif University (1994) and M.S./Ph.D. in Electrical and Computer Engineering from Georgia Tech (2001/2003). Prior to academia, he worked as a design engineer in Tehran (1994-1999) and as a research engineer at Georgia Tech's Microelectronics Research Center (2004-2008). Professor Naeemi's research spans nanotechnology with focus on emerging nanoelectronic devices, spintronics, ferroelectric devices, and design technology co-optimization for CMOS/beyond-CMOS technologies. His work bridges materials, devices, circuits, and systems, particularly investigating integrated circuits based on nanoscale devices and interconnects. Educational research includes experiential learning environments for engineering education. Recent publications (2024-2025) demonstrate strong emphasis on spin-orbit torque MRAM, ternary content addressable memories, ferroelectric/antiferroelectric devices, and plasmonic circuits. Key trends include energy-efficient hardware accelerators, neuromorphic computing applications, and compact modeling for advanced technology nodes. His scientific honors include: IEEE Solid-State Circuits Society James Meindl Innovators Award (2022) IEEE Electron Devices Society Paul Rappaport Award (2008) NSF CAREER Award (2013) SRC Inventor Recognition Award (2010) Multiple Georgia Tech teaching awards Professor Naeemi leads research supported by NSF (including NNCI infrastructure) and SRC. His editorial role with IEEE JXCDC positions him at the forefront of exploratory computational devices. He previously served as General Co-Chair for the IEEE International Interconnect Technology Conference (2013). His work connects with Georgia Tech's Microelectronics Research Center and national nanotechnology initiatives through the NNCI network, focusing on computational infrastructure for nanoscale device characterization and design.
Tianzheng Wangمشاهده پروفایل
دانشیار
Tianzheng Wang is an Associate Professor and Director of the Dual-Degree and Partnerships Programs at the School of Computing Science, Simon Fraser University. His research focuses on database systems, transaction processing, parallel and distributed computing, and embedded systems. He holds a PhD in Computer Science from the University of Toronto (2017) and a BSc in Computing from Hong Kong Polytechnic University (2012). Research Interests: Database systems optimized for modern hardware, parallel programming, synchronization, and distributed architectures. His work emphasizes high-performance transaction processing and efficient indexing techniques, with applications in cloud and embedded systems. Awards: ACM SIGMOD Best Paper Award (2025), IEEE TCSC Early Career Award (2019), and multiple distinguished reviewing recognitions (SIGMOD/VLDB 2021-2024). His research has been integrated into systems like Amazon Redshift and DragonflyDB. Teaching: Leads courses such as CMPT 454 (Database Systems II), CMPT 300 (Operating Systems), and special topics in databases. Actively mentors graduate and undergraduate students in research projects. Labs & Collaborations: Heads the Data-Intensive Systems Lab, part of SFU's Data Science and Systems groups. Collaborates on tools like PiBench for persistent memory benchmarking and contributes to open-source projects like CoroBase and Tabular.
- Women, Gender and Sexuality History
- 19th and 20th Century United States History
- Suffrage and Enfranchisement History
- +۲ مورد دیگر
Jessica Brannon-Wranosky is a Professor in the Department of History within the College of Humanities, Social Sciences and Arts at East Texas A&M University. She specializes in women, gender and sexuality history and digital humanities applications, and currently serves as Project Director for the Handbook of Texas Women, a statewide public education initiative of the Texas State Historical Association. Her educational background includes: Ph.D. in History from the University of North Texas M.S. in History from Texas A&M University-Corpus Christi B.S. in Political Science from Texas A&M University-Corpus Christi Dr. Brannon-Wranosky's research centers on 19th-20th century U.S. women's history with regional focus on Texas and the South, examining suffrage movements, gender dynamics, and digital historical methodologies. Her work bridges academic scholarship with public engagement through digital platforms and educational outreach. Her publication portfolio reveals consistent thematic focus on Texan women's historical agency, with recent works emphasizing digital curation of primary sources and intersectional analysis of suffrage activism. The Handbook of Texas Women project exemplifies her commitment to transforming archival materials into accessible public resources. Her scholarly contributions have been recognized with: John H. Jenkins Award (Texas State Historical Association, 2015) Best Article Award (Texas Oral History Association, 2016) Liz Carpenter Award (2016) for co-edited volume Texas Women/American Women As lead investigator for the Handbook of Texas Women project, she directs a multidisciplinary team developing digital infrastructure for statewide historical content, collaborating with museums and educational institutions to produce exhibits like the Bob Bullock Texas History Museum's 2019-2020 suffrage exhibition.
Noga Alon is a Professor at Princeton University (previously at Tel Aviv University since 1985), renowned for transformative contributions to Combinatorics and Theoretical Computer Science. His work bridges deep mathematical theory with computational applications, earning him the 2024 Wolf Prize and 2022 Shaw Prize in Mathematical Sciences. Education Ph.D. in Mathematics, Hebrew University of Jerusalem, Israel (1983) Research Interests Alon pioneers combinatorial methods with profound impacts across mathematics and computer science. His expertise spans Graph Theory, Combinatorial Algorithms (including Streaming Algorithms), Circuit Complexity, and Combinatorial Geometry/Number Theory. He innovatively applies Algebraic and Probabilistic Methods to solve fundamental problems, such as necklace splitting and signrank applications, driving advancements in both pure and applied domains. Scientific Awards 1989 Erdos Prize, Israel 1991 Feher Prize, Israel 1997 Member of the Israel National Academy of Sciences 2000 Polya Prize, SIAM, USA 2001 Bruno Memorial Award, Israel 2005 Landau Prize, Israel 2005 EATCS-ACM Goedel Prize 2008 Israel Prize in Mathematics 2008 Member of the Academia Europaea 2011 EMET Prize 2015 Fellow of the American Mathematical Society 2015 Łojasiewicz Lecture at Jagiellonian University 2017 Fellow of the Association for Computing Machinery 2021 Leroy P. Steele Prize for Mathematical Exposition (with Joel Spencer) 2022 Shaw Prize in Mathematical Sciences 2024 Wolf Prize in Mathematics Advising and Grants While Alon has undoubtedly mentored numerous students during his tenure at Tel Aviv University and MIT, specific advisee names are not documented in the source material. Similarly, grant funding details remain unspecified despite his extensive research output.
Ruomeng Huangمشاهده پروفایل
دانشیار
Ruomeng Huang is an Associate Professor in the Sustainable Electronics Technologies group within the School of Electronics and Computer Science at the University of Southampton. He holds a PhD in nanoscale memristors (2015) and has been a faculty member since 2018, advancing to his current rank in 2023. His research focuses on neuromorphic computing using memristive materials, machine learning-driven nanophotonics, and energy harvesting devices. Huang has published over 100 peer-reviewed articles and leads six UKRI-funded projects, including the EPSRC-funded ADEPT initiative. Education: BSc Physics (2008), MEd (2009) in China; MSc Nanoelectronics & Nanotechnology (2010), PhD in nanoscale memristors (2015) at the University of Southampton. Research Interests : - Neuromorphic computing via novel memristor devices (SiC, mesoporous silica, chalcogenides) - Thermoelectric materials (SnSe, Bi₂Te₃) and AI-optimized generators - Deep learning for structural color design Teaching : Leads MSc programs in Electronic Engineering and Micro/Nanotechnology. Teaches undergraduate/graduate modules including semiconductor devices, nanoelectronics, and industrial studies. Grants & Projects : - EPSRC Doctoral Prize Fellowship (2015) - Co-Investigator on £6.33M EPSRC ADEPT grant (electrodeposition innovations) - PI on multiple thermoelectric and neuromorphic computing projects Students : Currently supervising 7 PhD students. Notable advisees include Aiden Graham, Jiale Zeng, and Dongkai Guo. Labs/Teams : Heads the Sustainable Electronics Technologies group, collaborating with interdisciplinary teams in nanomaterials and energy systems.
Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).
David I. August is a Professor of Computer Science at Princeton University, affiliated with the Department of Electrical Engineering. He earned his Ph.D. from the University of Illinois at Urbana-Champaign in 2000. His research focuses on compilers and computer architecture, emphasizing synergistic design between compilers and microarchitecture. He leads the Liberty Research Group, which explores topics such as automatic parallelization, memory profiling, and speculative execution. August joined Princeton in 1999 as a lecturer, advancing to full professor in 2012. He has served as program chair for MICRO 2009 and on committees for ISCA, PLDI, and ASPLOS. His notable accolades include the IEEE Fellow designation, Best Paper Awards at PLDI and CGO, and teaching awards from Princeton's School of Engineering. His work spans compiler optimizations, hardware-software co-design, and security architectures like TrustGuard. Recent research includes GPU scheduling (GhOST), memory profiling frameworks (PROMPT), and instruction prefetching (PDIP). He advises over 20 graduate students, many now leading roles at tech companies and academia. August teaches courses such as COS-126 (Intro to CS), COS-375 (Computer Architecture), and graduate seminars. His projects often bridge theory and practice, with tools like NOELLE and Liberty Research Group initiatives advancing compiler infrastructure and parallelism extraction.
- Constructions of gender and sexuality in Islamic traditions
- Feminist exegesis of the Qur'an
- The body in Islamic ritual practices
- +۳ مورد دیگر
Aysha Hidayatullah is an Associate Professor in the Department of Theology and Religious Studies at the University of San Francisco's College of Arts & Sciences. She teaches undergraduate courses focusing on gender, sexuality, race, ethics, and religious studies within Islamic traditions. PhD, Religious Studies, University of California, Santa Barbara, 2009 MA, Religious Studies, University of California, Santa Barbara, 2005 BA, Women's Studies and English, Emory University, 2001 Her research explores feminist exegesis of the Qur'an , constructions of gender and sexuality in Islamic traditions , and the body in Islamic ritual practices . She also examines literary representations of Muslims, particularly through feminist theological frameworks and methodologies in Islamic studies. Key themes in her publications include interfaith collaboration , Qur'anic hermeneutics , and gendered narratives in Islamic history . Her work addresses intersections of religion, gender, and race in both historical and contemporary contexts. 2023, Collective Achievement Award, University of San Francisco 2019, James Catiggay Changemaker Award, University of San Francisco 2017, Distinguished Teaching Award, University of San Francisco & Faculty Association 2016-2017, Dean's Scholar Award, College of Arts and Sciences 2015, Ignatian Service Award, University of San Francisco
- Market Design
- Game Theory
- Microeconomic Theory
- +۳ مورد دیگر
Jacob D. Leshno is an Associate Professor of Economics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research employs game theory, applied mathematics, and microeconomic theory to study allocation mechanisms and marketplace design, with applications spanning school choice systems, patient assignments to nursing homes, and decentralized cryptocurrency protocols. Professor Leshno's academic background includes: PhD in Economics from Harvard University, completed under Nobel laureate Alvin Roth M.Sc. in Pure Mathematics from Tel Aviv University B.Sc. in Pure Mathematics from Tel Aviv University His research program centers on market design theory with two primary strands. The first focuses on matching markets, where he developed tractable cutoff characterizations that clarify market structures for college admissions and medical residency matching (NRMP). His work demonstrates how price discovery mechanisms can streamline inefficient processes like college applications and subsidized housing allocation. The second strand examines cryptocurrencies and blockchain technology, investigating how open-source computer code functions as market rules in decentralized systems. This research explores both the economic security of permissionless consensus and fundamental limitations of proof-of-work protocols. Professor Leshno's publications reveal a cohesive research trajectory applying economic theory to increasingly complex market structures. His work consistently bridges theoretical rigor with practical implementation, evolving from traditional matching markets to the frontier of decentralized digital systems. Publications in top journals like American Economic Review and Journal of Political Economy demonstrate both analytical depth and real-world relevance across education, healthcare, and financial technology sectors. Professor Leshno has received significant recognition for his contributions: ACM SIGecom Test of Time Award for foundational work in matching markets INFORMS Frederick W. Lanchester Prize for outstanding contributions to operations research Prior to Chicago Booth, Professor Leshno served as Assistant Professor at Columbia Business School and completed a postdoctoral fellowship at Microsoft Research New England, following industry experience at Yahoo! and IBM. He teaches MBA courses in Competitive Strategy and Market Design, and developed a PhD seminar bridging computer science theory with economic principles for distributed systems. His research continues to influence both academic theory and practical implementations of market mechanisms across multiple sectors. Professor Leshno maintains active collaborations with leading researchers including Itai Ashlagi, Irene Lo, and Gur Huberman, advancing the theoretical foundations of market design while addressing contemporary challenges in digital marketplaces and allocation systems.
Alin Coman is a Professor at Princeton University 's School of Public and International Affairs, leading the Cognition in Collectives Lab . His research explores how cognition emerges and evolves within social contexts, focusing on collective memory, belief dynamics, and emotion regulation through interactions. Education: Ph.D. from the New School for Social Research Research Focus: Integrating laboratory experiments, field studies, social network analysis, and agent-based simulations, his work demonstrates how macro-level phenomena like collective memories and synchronized beliefs arise from micro-level cognitive processes. Key themes include memory convergence, belief propagation in networks, and socially triggered prediction errors. Article Trends: His recent publications address vicarious memory frameworks, emotion regulation contagion, moral narratives, political belief change, pandemic-related belief dynamics, and the role of social norms in cognitive processes. Methodologies often involve network science and experimental paradigms. Advising: Mentors graduate researchers including Ari Dyckovsky, Gracielle Li, and Naomi Vaida. Lab: The Cognition in Collectives Lab employs a social-interactionist approach to study emergent psychological phenomena across groups and networks.
فقط ۷۵۰ نتیجه اول نمایش داده میشود. برای رسیدن به نتایج دقیقتر، جستوجو را با فیلترها محدودتر کنید.