Find Academic Supervisors

• Computer Graphics
• Human-Computer Interaction
• Geometric Modeling
• +5 more

Carlo H. Séquin is a Professor of Computer Science in the EECS Department at the University of California, Berkeley. He is affiliated with the Graphics (GR) and Human-Computer Interaction (HCI) research areas, and associated with the Berkeley Center for New Media (BCNM), Berkeley Institute of Design (BID), CITRIS, and the Visual Computing Lab (VCL). His research focuses on geometric modeling, artistic geometry, mathematical visualizations, and CAD tools. Education: Ph.D. in Experimental Physics (1969), University of Basel, Switzerland. Past Roles: Head of Computer Science Division (1980–1983), co-inventor of RISC architecture with David Patterson. His work spans computer graphics, VLSI design, and the intersection of art and mathematics. He has pioneered functional optimization for surface design and contributed to CCD technology at Bell Labs. Séquin's awards include the Berkeley Citation (2016), ACM Fellow (1997), and teaching excellence awards. He advises students in Ph.D. and M.S. programs, as seen in his Ph.D. alumni list . His research is supported through CITRIS and other institutional collaborations. Séquin's artistic projects, such as mathematical sculptures and architectural designs, bridge engineering and art, exemplified by his work on the Pillar of Engineering and Twisted Tori .

• Microelectronics
• Analog Filters
• Signal Processing
• +10 more

Nuno Miguel de Figueiredo Garrido is an Assistant Professor in the Department of Information Science and Technology at ISCTE – Instituto Universitário de Lisboa (ISCTE-IUL). He is also an Associate Researcher at the Institute of Telecommunications – IUL, affiliated with the Radio Systems Group. His academic work bridges microelectronics, signal processing, and smart city technologies. PhD in Information Sciences and Technologies, ISCTE-IUL (2012–2015) Bachelor's in Electrical and Computer Engineering, Higher Technical Institute – UTL (1994) His research interests include microelectronics, analog filters, CMOS technology, smart cities, IoT systems, machine learning, and low-power circuit design. He has contributed significantly to adaptive analog filter design for hard disk drives and more recently to smart parking and interactive systems using BLE, Arduino, and Raspberry Pi. The analysis of his recent publications (2018–2024) reveals a strong interdisciplinary focus. Early work centered on high-frequency CMOS transconductors and signal equalization in storage systems. Recent research expands into machine learning for healthcare, NLP for IT automation, and educational tools for programming. His work frequently appears in international conferences such as IEEE ISCAS, INTELEC, and ACM ITiCSE, indicating active engagement in both engineering and computer science communities. Although no formal scientific awards are listed, his work has accumulated 94 Google Scholar citations, with publications in Q2 and Q3 ranked venues, reflecting scholarly impact. Garrido advises students and collaborates on research projects involving port classification automation, kidney disease prediction, and smart urban systems. He has contributed to the development of tools like Jask (question generation for Java code) and Sprinter (a didactic linter), showing commitment to computing education. He is involved in multiple research initiatives related to IoT, smart cities, and embedded systems, particularly those utilizing open hardware and software. His lab and team affiliations include the Radio Systems Group at the Institute of Telecommunications – IUL, where he conducts research on wireless and embedded systems for smart environments.

Tim SherwoodView profile

Professor

• Computer Architecture
• Computer Security
• Hardware Security
• +7 more

Tim Sherwood is a Professor of Computer Science and Dean of the College of Creative Studies at UC Santa Barbara. He leads the UCSB Computer Architecture Lab (ArchLab) and co-founded Cycuity (formerly Tortuga Logic). His research focuses on secure and energy-efficient computing, superconducting architectures, and interdisciplinary projects like SEEDS. He holds a B.S. from UC Davis (1998) and M.S./Ph.D. from UC San Diego (2003) under Brad Calder. Awards include ACM Fellow (2023), IEEE Fellow (2022), and numerous best paper awards. Research interests span neuro-inspired temporal logic, hardware security, 3D integration, and accelerating machine learning. He emphasizes mentoring, having mentored over 20 students highlighted in awards. Teaching includes courses on computer organization, compiler design, and advanced architectures. Collaborations with industry and academia address challenges in trustworthy computing and future hardware paradigms. Notable achievements include the ASPLOS Most Influential Paper Award (2017) for SimPoint and leadership in securing hardware architectures. Current work explores superconducting computing, low-energy neural networks, and privacy-preserving systems.

Dustin RichmondView profile

Assistant Professor

• Computer Architecture
• FPGA
• RISC-V
• +4 more

Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.

• Quantum Information and Computation
• Quantum Many-Body Systems
• Tensor Networks
• +7 more

Professor Norbert Schuch is a full Professor of Physics and Mathematics at the University of Vienna, where he leads the Research Group "Quantum Information and Quantum Many-Body Physics" at both the Faculty of Physics and Faculty of Mathematics. He joined the University of Vienna in October 2020 after serving as a tenured Research Group Leader at the Max-Planck-Institute of Quantum Optics in Garching, Germany and as a Lecturer at the Technical University Munich. Prior to that, he held a Tenure-Track-Professor position at the Institute for Quantum Information at RWTH Aachen University. Professor Schuch's research focuses at the intersection of Quantum Information and Computation with the Physics of Complex Quantum Many-Body Systems. His work combines mathematical, physical, and computational approaches to understand quantum correlations in many-body systems. Key research areas include tensor networks (such as Matrix Product States and Projected Entangled Pair States), topological order, entanglement theory, quantum algorithms, and quantum complexity theory. His interdisciplinary approach integrates methods from physics, mathematics, and theoretical computer science to address fundamental questions about quantum systems. His recent publications show a continued focus on tensor network theory and applications, with particular emphasis on topological phases, entanglement structure, quantum algorithms, and computational aspects of quantum many-body systems. His work spans mathematical foundations, physical applications, and computational implementations, demonstrating the cross-disciplinary nature of his research program. As an educator, Professor Schuch teaches courses on Quantum Information, Quantum Computing, and Quantum Algorithms, as well as specialized topics like Entanglement in Quantum Many-Body Systems. He actively supervises PhD students, postdocs, and master's students in his research group, which maintains strong connections with the international quantum information community.

Juan Carlos Pichel CamposView profile

Professor

• parallel and distributed computing
• Big Data technologies
• programming models
• +7 more

Juan Carlos Pichel Campos is a Full Professor at the University of Santiago de Compostela (USC) specializing in high performance computing and language technologies. His research spans quantum computing, distributed systems, and Big Data technologies with a focus on practical applications in health informatics and computational physics. He received his B.Sc. and M.Sc. in Physics from University of Santiago de Compostela (Spain) and completed his Ph.D. there in 2006. He conducted postdoctoral research at University Carlos III de Madrid and University of Illinois at Urbana-Champaign, and worked as a researcher and project manager at Galicia Supercomputing Center. Professor Pichel's research interests include parallel and distributed computing, Big Data technologies, programming models, and software optimization techniques for emerging architectures. His recent work has focused on bridging quantum computing with classical high performance computing systems, developing efficient algorithms for processing massive biological datasets, and creating tools for health-related information retrieval and misinformation detection. His interdisciplinary approach combines techniques from computer science, physics, and biomedical informatics to solve complex computational problems. Analysis of his recent publications reveals a strong trend toward quantum computing applications and integration with classical HPC systems (accounting for approximately 40% of his recent work), followed by health informatics and natural language processing (about 30%), and bioinformatics and computational physics (about 30%). His research demonstrates a consistent focus on developing practical tools and frameworks that address real-world computational challenges across multiple domains. rePowerSiC: High-Efficiency High-Power Laser Beaming In-Space Systems Based On Sic (2024-2028) C3HS: Content curation for consumer health search - Search and misinformation detection (2023-2026) Big-eRisk: Early Prediction of Personal Risks on Massive Data (2021-2024) eRISK: Technologies for the early prediction of signs related with psychological disorders (2019-2021) BigNLP: Approaching High Performance Computing to Big Data Technologies: Natural Language Processing as Case Study (2015-2018) Professor Pichel has established strong collaborations with research groups across Europe and the United States, particularly in the fields of quantum computing and biomedical informatics. He is actively involved with CiTIUS (Centro singular de investigación en tecnoloxías da información e da comunicación de USC), contributing to its mission of advancing information and communication technologies through interdisciplinary research.

• Machine Learning
• Relational Databases
• Quantum Computing
• +3 more

R. Hai is a researcher active in the fields of Machine Learning , Relational Databases , and Quantum Computing . Their work bridges the integration of large language models (LLMs) with database systems, focusing on optimizing query processing and data management through linear algebraic methods. Hai's research emphasizes seamless data-ML workflows and innovative applications of relational databases in emerging domains. Key Research Themes : LLM compilation to SQL, quantum circuit simulation via RDBMS, and convergence of data integration with ML. Collaborations : Active in international academic networks, with contributions to conferences like SIGMOD and IEEE journals. Scientific Awards: Veni grant AES2022 (2023) Publications demonstrate expertise in overcoming data barriers, enhancing database performance for ML tasks, and simulating quantum computations using relational database management systems.

• Automating Design and Diagnosis of Information Systems
• Computer Graphics
• Web Technologies

Konstantin Nikolaevich Kasyan serves as Associate Professor at the Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies at Zaporizhzhia National Technical University, where he has maintained academic activity since 1998. He graduated with honors from Zaporizhzhia Machine-Building Institute's Faculty of Electronic Engineering in 1993, specializing in Radio Engineering with qualification as Radio Engineer. His Candidate of Sciences degree (defended 1998/1999) established his expertise in diagnostic methodologies for electronic systems. His research spans three core domains: automating design and diagnosis of information systems, computer graphics methodologies, and web technologies. This interdisciplinary focus manifests in practical applications ranging from hardware diagnostics to smart home systems. His work demonstrates consistent evolution from foundational electronics reliability research in the 1990s toward contemporary IoT and computer vision applications. His publication trajectory reveals distinct chronological phases: 1990s-2000s concentrated on electro-radio diagnostics and reliability engineering; 2000s-2010s expanded into computer graphics and text recognition; while 2010s-2021 shifted toward IoT integration, smart home technologies, and machine learning applications. This progression reflects both technological advancements and his adaptability across computing subfields. Kasyan teaches modern Internet technologies, computer graphics, computer systems design, and computational methods in scientific research, directly translating his research into pedagogical practice. His academic presence is maintained through Scopus, Web of Science, Google Scholar, and ORCID profiles, indicating active scholarly engagement despite the absence of formal awards or documented grants in available records.

• distributed and parallel computing
• blockchain technology
• decentralized platforms
• +3 more

Тетяна Сергіївна Дьячук є старшим викладачем кафедри комп'ютерних систем та мереж Факультету комп'ютерних наук і технологій Запорізької національної технічної політехніки, де працює з 2006 року після закінчення університету з відзнакою. Вона є активним членом академічної спільноти, зосереджуючись на сучасних напрямках комп'ютерних наук та технологій. Освіта: Запорізька національна технічна політехніка, 2006 рік, спеціальність "Комп'ютерні системи та мережі", кваліфікація "Магістр комп'ютерних систем та мереж" (з відзнакою) Запорізька національна технічна політехніка, 2006 рік, кваліфікація "Менеджер-економіст" Наукові інтереси Тетяни Сергіївни охоплюють ключові напрями сучасних комп'ютерних технологій, зокрема розподілені та паралельні обчислення, блокчейн-технології, децентралізовані платформи та оптимізацію обчислень. Вона також активно займається дослідженнями в галузі Android-програмування та розробки мобільних додатків. Її наукова робота характеризується практичною спрямованістю, що знаходить відображення в численних публікаціях та конференціях. Аналіз наукових публікацій Тетяни Сергіївни показує чітку еволюцію її наукових інтересів від фундаментальних досліджень розподілених систем та алгоритмів планування ресурсів до сучасних технологій блокчейну, штучного інтелекту та автоматизації процесів програмування. Особливо вражає її здатність поєднувати теоретичні дослідження з практичними застосуваннями в різних галузях, від медичної діагностики до розробки мов високого рівня. Наукові досягнення: Понад 15 наукових публікацій в провідних наукових виданнях Активна участь у міжнародних наукових конференціях Реєстрація в наукометричних базах: Scopus, Web of Science, Google Scholar, ORCID Тетяна Сергіївна активно бере участь у науково-педагогічній діяльності, викладаючи курси, що відповідають сучасним тенденціям в комп'ютерних науках. Вона також займається науковою роботою зі студентами, сприяючи їх інтеграції в наукову спільноту через участь у наукових конференціях та проєктах. Незважаючи на те, що конкретні науково-дослідні гранти не зазначені в доступних джерелах, її публікаційна активність та участь у конференціях свідчать про продуктивну наукову діяльність. Хоча конкретні лабораторії або наукові групи, якими керує Тетяна Сергіївна, не зазначені в доступних джерелах, її наукова робота тісно пов'язана з розвитком сучасних технологій розподілених систем та обчислень, що ймовірно відбувається в рамках кафедри комп'ютерних систем та мереж Запорізької політехніки.

Frank LeymannView profile

Professor

• Quantum Computing
• Cloud Computing
• Service-Oriented Architecture
• +7 more

Frank Leymann is a Professor at the Institute for Architecture of Application Systems, University of Stuttgart. His research spans quantum computing, cloud systems, middleware, and business process management. Affiliation: University of Stuttgart, Institute for Architecture of Application Systems Key Projects: PlanQK, EniQmA, OpenTOSCA, SeQuenC Academic Recognition: Over 30 years of publications in service computing and quantum technologies Research Interests: His work focuses on quantum software engineering , hybrid quantum-classical systems , and cloud application architectures . Notable contributions include TOSCA standardization for cloud deployment and systematic studies on quantum optimization. Recent Publications: 2025-2024 articles emphasize quantum algorithm expressivity , cross-chain blockchain transactions , and post-quantum security . Earlier works (2023-2021) address quantum workflow provenance , QAOA optimization , and IoT platform architectures . Technical Leadership: Director of a multidisciplinary team developing frameworks like OpenTOSCA and tools for quantum application deployment.

Anitha GollamudiView profile

Assistant Professor

• Language-based Security
• Trusted Execution Environments
• Formal Methods
• +4 more

Anitha Gollamudi is an Assistant Professor in the Department of Computer Science at the Miner School of Computer and Information Sciences, University of Massachusetts Lowell. She teaches core courses including Systems Security (COMP 5300), Compiler Construction (COMP 4060/5340), and Organization of Programming Languages (COMP 3010). Her research focuses on language-based security through hardware-assisted mechanisms, cryptography, and formal methods. Current projects include: Automatic compartmentalization of Trusted Execution Environment (TEE) programs Formal foundations of Fully Homomorphic Encryption (FHE) compilers Privacy-preserving machine learning with encrypted learning Analysis of her 8 recent publications (2016-2025) reveals dominant themes in TEE security and secure compilation. Key contributions address memory safety in WebAssembly, authorization logic for computation principals, and formal verification of cryptographic systems. Her work consistently bridges theoretical foundations with practical implementations for real-world security challenges. No scientific awards were mentioned in the available information. Professor Gollamudi actively mentors students across levels, currently advising PhD candidates Wesley B. Nuzzo and Samuel Dodson alongside undergraduate Benjamin Houle. Her former students include Nam Bui, James Chen, Yuka Akiyama (honors thesis), and Andrew Eggleston. She emphasizes collaborative research and encourages prospective students to contact her with research interests and academic background. She leads a research group focused on applying programming language techniques to security problems, with ongoing projects targeting enclave placement optimization, FHE correctness verification, and encrypted machine learning frameworks.

• Embedded Systems
• Real-Time Systems
• System-on-Chip Design
• +7 more

Adriano José Conceição Tavares is an Associate Professor at the School of Engineering, University of Minho, Portugal. He serves as a Senior Researcher at Centro ALGORITMI, where he is affiliated with both the IE R&D Group and the ESRG R&D Lab. His academic credentials include a PhD in Industrial Electronics from the University of Minho, a Master of Science in Information Technology from the University of Coimbra, and an undergraduate degree in Informatics from the University of Coimbra. Professor Tavares specializes in embedded systems with particular expertise in: Embedded systems modeling and design System software design System-on-chip design Real-time operating systems Hardware acceleration and FPGA design Virtualization for embedded systems IoT frameworks and protocols His publication record demonstrates a strong research trajectory in hardware-software co-design, with recent work showing an increasing integration of machine learning techniques into embedded systems. His publications span theoretical frameworks to practical implementations addressing real-time performance, resource constraints, and security challenges. Among his scholarly metrics: h-index of 18 126 publications with 1148 citations 20 publications in Q1/Q2 journals Author of a book on microcontroller programming Professor Tavares has supervised students including Miguel Ângelo Fernandes Silva and has established international collaborations through the Erasmus Program with institutions in China, Iran, Thailand, Jordan, and Cambodia. He teaches advanced courses on embedded and real-time systems modeling, compiler design, system-on-chip design, real-time operating system design, and advanced computer architectures at University of Minho.

Işıl DilligView profile

Associate Professor

• Program analysis
• Program synthesis
• Program verification
• +4 more

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.

• Artist film & video
• Video installation
• Networked narratives
• +3 more

Lecturer in Fine Art & Graphic Design at the University of Salford's School of Arts, Media and Creative Technologies , Gary Peploe is an artist, designer, and curator directing the Interval research collective since 2005. His academic practice integrates creative production with pedagogical innovation through platforms like Loosecollective. Master's Degree in Creative Technologies (1997-1998) Bachelor's Degree in Interactive Arts (1994-1997) Research explores artist film & video , video installation , and networked narratives through urban ecologies and dual-screen dialogues. His 2018 Research Archive & Legacy project extends this focus to preservation frameworks, while works like Houndstooth II demonstrate immersive spatial video environments interrogating viewer-perception relationships. Exhibition trends reveal consistent international engagement across London, Berlin, Manchester, and South Africa, with 15+ outputs between 2002-2015 spanning digital artifacts, performances, and conference contributions. His practice emphasizes temporal constraints (e.g., one-minute films) and cross-cultural exchange, notably through One Minute Volume series curation. ZKM Award for media art innovation As Interval Director, Peploe creates symbiotic knowledge exchange platforms between industry, educators, and students, evidenced by the Costa del Salford model. His 2014 'Fast forward' research identifies disruptive opportunities for micro-enterprises in creative sectors, reflecting active industry engagement beyond traditional academic boundaries. Leading Interval's non-gallery exhibitions like 'Illumination' in Manchester, Peploe develops research environments centered on blacked-out spatial experiences and alumni collaboration, distinct from conventional laboratory structures.

John WickersonView profile

Senior Lecturer

• concurrency semantics
• FPGAs
• GPUs
• +5 more

John Wickerson is a Senior Lecturer in the Department of Electrical and Electronic Engineering at Imperial College London. His research spans formal methods, concurrency, and hardware/software synthesis. Academic Rank: Senior Lecturer Affiliation: Imperial College London His research interests include concurrency semantics, weak memory models, transactional memory, GPU and FPGA programming, and high-level synthesis for hardware accelerators. These areas intersect formal verification, programming language design, and hardware-software interface optimization. The publications of John Wickerson reflect trends in formalizing memory models, improving hardware synthesis reliability, and testing concurrency frameworks. His work addresses challenges in quantum compiler validation, GPU workgroup progress, and weak memory persistency across Intel, ARM, and C++ architectures. He actively contributes to academic communities as a Publicity Co-Chair and Session Chair in conferences like POPL and as a Committee Member in SPLASH and PLDI. His GitHub repository activity and X (Twitter) presence further demonstrate his engagement in technical dissemination.