جست‌وجوی استاد و پژوهشگر

John Preskillمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information Theory
• Theoretical Physics
• +۳ مورد دیگر

John Preskill is the Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology (Caltech). He is a leading figure in quantum information science, focusing on quantum computing, quantum error correction, and the theoretical foundations of quantum mechanics. His work bridges fundamental research and practical quantum technologies, including contributions to the NISQ (Noisy Intermediate-Scale Quantum) era framework and quantum machine learning. In 2024, he was awarded the prestigious John Stewart Bell Prize for his advancements in quantum information processing and machine learning applications in quantum experiments. Preskill's research emphasizes leveraging quantum principles for novel computational paradigms, such as quantum advantage in learning from experimental data and scalable quantum error correction. His articles explore topics like quantum field theory simulations, entanglement dynamics, and fault-tolerant quantum architectures. He collaborates across disciplines, contributing to both theoretical breakthroughs and experimental implementations of quantum technologies. Notably, his 2018 paper Quantum Computing in the NISQ era and beyond outlines near-term quantum computing challenges and opportunities. His work on Bell Prize-winning research highlights foundational links between quantum learning and efficient information processing. Preskill is affiliated with Caltech's Institute for Quantum Information and Matter, driving interdisciplinary quantum science initiatives.

• Generative AI
• Dance Improvisation
• Decolonial Thought
• +۵ مورد دیگر

Marlon Barrios Solano is an interdisciplinary artist, creative technologist, and researcher at the University of Florida's Center for Arts, Migration and Entrepreneurship (CAME) since 2024. With an MFA in Dance and Technology from Ohio State University and software engineering training, he merges generative AI, machine learning, and queer theory to create epistemic infrastructures. Current roles: Maker-in-Residence at CAME, Lake Studios Berlin co-founder Education: MFA in Dance and Technology (2004), General Assembly Software Engineering Immersive (2021) His work interrogates latent space as a metaphor for diasporic memory and synthetic cognition. Through live AI collaborations , he constructs knowledge labs that challenge Silicon Valley's extractive AI paradigms, focusing on Decolonial AI frameworks Queer techno-intimacy Embodied computational ethics Somatic machine learning Scientific achievements include 2017 Hombroich Fellowship Residencies at Radiona (Croatia), ICK Amsterdam (Netherlands) fal.ai Research Grant for real-time AI development He has published in Transmission in Motion and Dance in the Head , while pioneering open-source platforms like dance-tech.net (2007) and movimiento.org (2011). Currently developing the Born in Latent Space five-year research arc (2024-2029).

Selçuk Köseمشاهده پروفایل

استاد

• Hardware Security
• On-Chip Power Delivery
• Cryogenic Electronics
• +۳ مورد دیگر

Selçuk Köse is a Full Professor in the Department of Electrical and Computer Engineering at the University of Rochester. Previously, he held positions at the University of South Florida as an Assistant Professor (2012-2018) and Associate Professor (2018-2019). He earned his B.Sc. from Bilkent University (2006), M.S. and Ph.D. from the University of Rochester (2008 and 2012, respectively). His research focuses on hardware security (side-channel attacks, fault injection, PUFs), on-chip power delivery, cryogenic electronics, graphene nanoribbon transistors, and nature-inspired computing (e.g., Ising machines). He has received prestigious awards including the NSF CAREER Award (2014) and Cisco Research Awards (2015–2017). His recent work emphasizes security in quantum computing interfaces, power delivery networks, and covert channel mitigation. Research funding comes from NSF, DARPA, DoE, and industry partners. He serves as an associate editor for IEEE and Springer journals.

• Quantum Information Systems
• Quantum Simulators
• Quantum Error Correction
• +۴ مورد دیگر

Michael Gullans is an Adjunct Assistant Professor in the Department of Physics, Department of Computer Science, and the Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is also a physicist in the Nanoscale Device Characterization Division at NIST. His research focuses on quantum information systems, quantum simulators, and fault-tolerant computing, emphasizing error correction, noise mitigation, and statistical physics applications in many-body quantum dynamics. Gullans holds a PhD from Harvard University (2013) and has held postdoctoral positions at QuICS and Princeton University. His work bridges theoretical quantum computing and experimental implementations, with contributions to quantum error correction protocols, analog quantum simulation, and the interplay of disorder and noise in quantum systems. Recent publications address scalable quantum architectures, low-depth random circuits, and hybrid fermion-qubit systems. He teaches advanced courses on quantum technology and quantum error correction. Key collaborations include NIST, QuICS, and institutions exploring silicon spin qubits and reconfigurable atom arrays. His research aims to advance fault-tolerant quantum computation and reliable quantum simulators for studying complex systems.

Filipa Caladoمشاهده پروفایل

استادیار

• Digital Humanities
• Queer Studies
• Natural Language Processing
• +۱۲ مورد دیگر

Filipa Calado is an Assistant Professor in the School of Information at Pratt Institute, where she teaches courses in programming, data science, and critical approaches to technology. Her research lies at the intersection of digital humanities, queer theory, and computational linguistics, focusing on how AI and machine learning encode and reproduce biases related to gender, sexuality, and identity. PhD in English Literature and Certificate in Interactive Technology and Pedagogy, CUNY Graduate Center (2019) MA in English, University of Maryland BA in English with minor in Art History, Catholic University of America Her research critically examines the transformation of linguistic expressions of sex, gender, and sexuality into computable data, with a recent focus on using Large Language Models to analyze transphobic discourse in the U.S. She combines digital methods like text analysis and machine learning with critical frameworks from queer and feminist theory to challenge dominant narratives in technology. Her recent publications explore gender bias in NLP, queer approaches to text encoding (TEI), and the erasure of queer identities in literary texts. Her teaching emphasizes ethical coding practices, algorithmic bias, and feminist data science, equipping students with both technical and critical skills. She has presented her work at major conferences including ADHO, MLA, and ASAP, and delivered keynotes on topics such as impostor syndrome and open knowledge in AI. Most Distinguished Dissertation of the Year, CUNY Graduate Center, 2024 She has secured grants from Pratt Institute, CUNY, and the Digital Ethnic Futures Consortium, and is actively involved in service, including diversity and faculty search committees at Pratt. Her coding projects and teaching materials are openly available on GitHub under gofilipa , reflecting her commitment to open knowledge and digital pedagogy.

Nan Xieمشاهده پروفایل

پژوهشگر

• Network Design
• Performance Optimization
• Communication Networks
• +۳ مورد دیگر

Nan Xie is a Researcher in the Department of Electrical and Electronic Engineering at Imperial College London, affiliated with the Information Processing and Communications Lab. He holds a Ph.D. in Electrical Engineering from Drexel University (2014), following M.S. (2006) and B.S. (2003) degrees in Communication Engineering from Wuhan University, China. His research focuses on network design and optimization, particularly analyzing metrics like delay, stability, throughput, and fairness in communication networks. Education: B.S., Communication Engineering, Wuhan University (2003) M.S., Circuits and Systems, Wuhan University (2006) Ph.D., Electrical Engineering, Drexel University (2014) His work emphasizes understanding and improving network performance through theoretical frameworks, with contributions to Aloha protocols, network coding, and erasure channel analysis. Recent publications explore trade-offs between throughput and fairness in wireless networks, stability region approximations, and delay optimization in broadcast systems. He has collaborated on projects extending his doctoral research into broader network optimization contexts. His expertise is reflected in peer-reviewed journals and conferences such as IEEE Transactions on Information Theory and the IEEE International Symposium on Information Theory. Currently part of Imperial's Information Processing and Communications Lab, his research continues to bridge theoretical insights with practical network design challenges.

Annemarie Toeboschمشاهده پروفایل

استاد آموزشی

• Linguistics
• Dutch Studies
• Decoloniality
• +۴ مورد دیگر

Annemarie Toebosch is a Teaching Professor and Director of Dutch Studies in the Department of Germanic Languages and Literatures at the University of Michigan's College of Literature, Science, and the Arts. She also serves as affiliate faculty in Judaic Studies and the Michigan Community Scholars Program. Her educational background includes: Ph.D. in Linguistics, University of Michigan M.A. in English Literature and Linguistics, Radboud Universiteit Nijmegen M.A. in TESOL College Preparatory Education, Radboud Universiteit Nijmegen As a Chomskyan linguist, Toebosch teaches and writes within a framework of political and academic activism that challenges colonial power structures in the Dutch-speaking world and beyond. Her work centers on developing decolonial approaches to language education, making the Dutch Studies program at the University of Michigan the first of its kind on campus and a model for other language programs. Her teaching focuses on comparative Holocaust studies and decoloniality, connecting linguistic analysis with critical examinations of historical and contemporary power structures. Toebosch's research bridges linguistic theory with social justice activism, examining how language programs can confront colonial legacies while preparing students for global citizenship. Her scholarly output demonstrates consistent engagement with decolonial theory, postcolonial studies, and Holocaust education. Recent work includes critical analyses of Dutch colonial narratives, development of decolonial pedagogical approaches, and examinations of linguistic phenomena through critical theoretical lenses. She has produced significant scholarship on Dutch colonial history, multilingualism, and the intersection of language with power structures. Dutch Studies: A Decolonial Revision (2022) - an exhibit at the University of Michigan Harlan Hatcher Graduate Library Dutch King's Apology for Colonial Slavery Is an Erasure of History (2023) Yom HaShoah address on Holocaust education (2021) Translating Anti-Racism research working group (2019-2020) Dr. Toebosch leads the 'Translating Anti-Racism' research working group through the Humanities Collaboratory at the University of Michigan, collaborating with interdisciplinary scholars to address issues of race and language. As Director of Dutch Studies, she has reimagined the program to center decolonial approaches, moving beyond traditional language instruction to engage critically with the historical and political contexts of the Dutch-speaking world. Her work bridges linguistics, cultural studies, and political activism, creating innovative approaches to language education that address historical injustices while preparing students to engage critically with contemporary global issues.

James Davisمشاهده پروفایل

استاد

• Algebra
• Combinatorics
• Number Theory
• +۴ مورد دیگر

James Davis is a Professor in the Department of Mathematics at the University of Richmond, School of Arts and Sciences. He is actively engaged in research and teaching, with office located in Jepson Hall and contactable via email jdavis@richmond.edu and phone (804) 289-8094. Ph.D. in Mathematics, University of Virginia, 1987 M.S. in Mathematics, University of Virginia, 1985 B.S. in Mathematics, Lafayette College, 1983 His research focuses on algebraic combinatorics, particularly difference sets, bent functions, and error-correcting codes, with a goal of discovering new constructions with optimal or near-optimal structures. His work bridges theoretical mathematics and practical applications in coding and information theory. Although no explicit publications are listed in the provided text, his research interests suggest a strong output in combinatorial design theory and algebraic coding. His patents and industrial experience at Hewlett-Packard reflect applied impact. Dr. Davis has served as a testifying expert in patent litigation between Apple and Samsung and holds 15 U.S. patents in coding and memory systems. K.K. Smith, J. Jedwab, J.A. Davis, D. Banks and S.R. Wyatt, System for error correction coding and decoding, U.S. Patent No. 7418644, 26 Aug 2008. D. Banks, J. Davis, and J. Jedwab, Identifying uncorrectable codewords in a Reed-Solomon decoder for errors and erasures, US Patent No. 7278086, 2 October 2007. J. Davis, K. Eldredge, J. Jedwab, G. Seroussi, and K. Smith, MRAM with controller, US Patent No. 7266732, 4 September 2007. He advises students indirectly through academic materials and summer research programs, as suggested by files like krantz_phd_advice.pdf and directories such as summerwork/ and problemoftheweek/ . He is involved in institutional service, including the General Education Committee. His research has been supported through academic and industrial grants, though specific grant names are not listed. Dr. Davis maintains a personal academic website with teaching materials, research notes, and committee work, indicating active participation in both pedagogy and academic leadership.

• Computer Engineering
• Embedded Systems
• Image Processing
• +۳ مورد دیگر

Kranitis Nektarios is a Lecturer at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on FPGA-based hardware architectures, space-grade computing, and image compression standards like CCSDS, with applications in satellite systems and reliable data processing. Primary affiliation: National and Kapodistrian University of Athens Department: Informatics and Telecommunications Research interests center on space-grade SRAM FPGAs , LDPC encoding , hyperspectral image compression , and software-based self-test methodologies for embedded systems. His work addresses high-speed data processing and fault tolerance in satellite communications. Key trends in his publications include CCSDS standard implementations , hardware accelerators for image compression, resilience to SEUs , and energy-efficient testing techniques for microprocessors. Topics span space systems , parallel computing , and digital circuit design .

• Information Theory
• Machine Learning
• Fairness in AI
• +۶ مورد دیگر

Changho Suh is a Professor in the Department of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST), College of Engineering. His research spans information theory, machine learning, and data science with significant contributions to matrix completion, fairness in AI, and network communications. Dr. Suh's research interests focus on the theoretical foundations of information processing and machine learning. He has pioneered work in matrix completion with graph side information, developing efficient algorithms that leverage hierarchical structures and similarity graphs. His recent work emphasizes fairness in machine learning systems, addressing correlation shifts and developing methods for fair training and generative modeling. He has also made significant contributions to information theory, particularly in interference channels, network coding, and quantum key distribution. Analysis of his recent publications reveals a strong trend toward addressing fairness challenges in AI systems while maintaining theoretical rigor. His work bridges information theory with practical machine learning applications, particularly in recommender systems and community detection. Suh's research demonstrates how graph structures can enhance data recovery and how theoretical insights from information theory can improve modern machine learning systems. Dr. Suh has received recognition for his scholarly contributions through numerous publications in top-tier venues including IEEE Transactions on Information Theory, NeurIPS, ICML, and AAAI. His work has influenced both theoretical understanding and practical implementations in data science. As an academic advisor, Suh has mentored numerous graduate students who have gone on to publish significant research in their own right. His collaborative approach is evident in the diverse range of co-authors across his publications, indicating strong research partnerships both within KAIST and internationally. His laboratory work appears to focus on information-theoretic approaches to machine learning problems, with particular emphasis on structured data analysis, fairness considerations, and efficient algorithm design for large-scale data processing tasks.

• Communication Networks
• Decentralized Algorithms
• Large Deviations
• +۵ مورد دیگر

Ayalvadi Ganesh is a Lecturer in the Department of Mathematics at the University of Bristol's School of Mathematics, where he teaches advanced courses including Complex Networks, Stochastic Optimisation, and Queueing Networks. His academic work bridges theoretical mathematics with practical network applications. His research spans communication networks , decentralized algorithms , and stochastic modeling , with core expertise in large deviations theory , random graphs , queueing systems , and information theory . Recent work demonstrates strong focus on multi-agent bandit problems, epidemic modeling on networks, and latency optimization in distributed systems, reflecting interdisciplinary applications from cybersecurity to biological networks. Analysis of his 15 most recent publications reveals dominant trends in decentralized decision-making (38% of works), network epidemics/rumor spreading (27%), and stochastic optimization (20%), with increasing crossover into machine learning and biological applications since 2020. Best Paper award at ACM SIGMETRICS 2010 for 'Load balancing via random local search in closed and open systems' His teaching portfolio includes graduate-level courses on Complex Networks, Stochastic Optimisation, and Queueing Theory, with documented emphasis on connecting theoretical foundations to real-world network challenges. While specific grant details aren't provided in source materials, his publication pattern suggests sustained research funding in network science and stochastic systems.

• Anglo-Irish Literature
• Drama Studies
• Body and Image Studies
• +۴ مورد دیگر

Futoshi Sakauchi is a full-time Professor at Waseda University's School of Culture, Media and Society and Graduate School of Letters, Arts and Sciences. Holding a PhD from University College Dublin, his career spans over two decades of research and teaching in Anglo-Irish literature and performance studies. Current affiliations: Faculty of Letters, Arts and Sciences Secondary affiliation: Global Education Center Research focus examines: Body and image representations in Irish modernism Transformative public space in Joyce/Beckett Confession as secular/spiritual narrative Gendered corporeality in postcolonial contexts Cultural regeneration through performance Publisher trends show consistent engagement with James Joyce's works, Irish nationalist theatre, and body-centric methodologies. His 2018 project on confession in Irish drama reveals institutional authority's decline in contemporary contexts. Scientific recognition includes five consecutive Japan Society for the Promotion of Science grants (2007-2023) funding analyses of: Modernist body transfiguration Confession-as-secular-sacrament Technology's impact on bodily representations As educator , he teaches graduate seminars on body/media studies and performance theory while supervising master's research projects.

William J. Bowmanمشاهده پروفایل

استادیار

• Secure and Verified Compilation
• Dependently Typed Programming
• Verification
• +۴ مورد دیگر

William J. Bowman is an Assistant Professor in the Department of Computer Science at the University of British Columbia. He focuses on secure and verified compilation, dependently typed programming, and meta-programming systems. His work bridges high-level language design with low-level code generation to maintain correctness and security invariants throughout compilation. Education: PhD in Computer Science from Northeastern University Research spans type-preserving compilation, including: Typed closure conversion for dependently typed languages Allocation-aware type universes Hybrid embedding techniques Secure interoperability via multi-language semantics Recent publications examine: Heap allocation modeling through type universes Flat closure representations WebAssembly extensions with indexed types Control-effect semantics

Weina Wangمشاهده پروفایل

استادیار

• Applied Probability
• Stochastic Systems
• Reinforcement Learning
• +۷ مورد دیگر

Weina Wang is an Assistant Professor in the Computer Science Department at Carnegie Mellon University, joining in Fall 2018. Her research lies at the intersection of applied probability , stochastic systems , and reinforcement learning , focusing on decision-making in large-scale systems with applications to computing resource orchestration, data privacy, and graph statistics. She has received prestigious awards including the NSF CAREER Award (2022) , ACM MobiHoc Best Paper (2022) , and ACM SIGMETRICS Rising Star Research Award (2023) . PhD in Electrical Engineering, Arizona State University (2016) Bachelor’s in Electronic Engineering, Tsinghua University (2009) Her recent publications span restless bandits , queueing theory , and attributed graph alignment , reflecting her dual focus on fundamental limits and algorithmic solutions. Notable collaborations include work on privacy-preserving data routing , phase-aware scheduling , and erasure-coded servers for heterogeneous traffic. She has advised PhD students Jalani Williams , Tuhinangshu Choudhury , and Yige Hong . Her research has been recognized with best paper awards and grants like the NSF CAREER . She also contributes to professional societies, recently joining the INFORMS Applied Probability Society council . Her teaching includes courses like Probability and Computing and Fundamentals of MDPs and Reinforcement Learning .

• Cryptography
• Blockchains for embedded systems
• Secure satellite communications
• +۷ مورد دیگر

Jerome Lacan is a Professor at the Higher Institute of Aeronautics and Space (ISAE), where he serves as Head of the Department of Complex Systems Engineering (DISC) and is a member of the Sysco research team. He holds a PhD in Computer Science from Paul Sabatier University, Toulouse, France, and has accreditation to supervise research since December 2008. His research interests focus on security and cryptography with several specific areas of contribution: Blockchains for embedded systems through the BLEND group (BLockchains for aEronautical and space systems), addressing blockchain implementation in resource-constrained networks (drones, satellites, vehicles) including oracles, zero-knowledge proofs, and smart contracts Specialized cryptographic mechanisms including threshold cryptography and post-quantum cryptography Secure satellite communications, particularly implementation of cryptographic mechanisms on nano-satellites Erasure codes and network integration, notably the TETRYS protocol which combines coding and networking Professor Lacan has supervised numerous PhD students across various topics related to satellite communications, network coding, and security. His teaching spans multiple levels of the engineering program, from first-year courses on Information Theory to advanced Master's level courses in algorithms and video compression. He has taught across the Engineering program, including first-year elective modules on Information Theory, second-year Cryptography modules, third-year error-correcting coding and satellite communications standards, and Master's courses including Algorithm and Computing and video compression. Professor Lacan plays a significant role in both research and education at ISAE, contributing to the advancement of secure communications technologies for aerospace applications while mentoring the next generation of engineers and researchers.