جست‌وجوی استاد و پژوهشگر

Benjamin Risseمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Prof. Dr. Benjamin Risse leads the Computer Vision and Machine Learning Systems (CVMLS) group at the Institute of Geoinformatics, University of Münster . His interdisciplinary research bridges biomedical image analysis , machine learning , and virtual reality (VR) applications for medical education. Develops FIMTrack for high-throughput analysis of animal locomotion Focuses on VR-based medical training systems (e.g., brain death diagnostics) Pioneers deep learning in acute myeloid leukemia (AML) diagnosis and neuroscience-inspired AI Research Interests: Biomedical image analysis, tracking algorithms, behavioral quantification, machine learning for biological systems, VR in clinical education, and interdisciplinary imaging technologies. His work addresses algorithm limitations in ecology , neuroscience , and medical diagnostics . Recent Publications (2025–2024) span coherent nanophotonic networks , VR-based medical training , and Gaussian splatting for occupancy estimation , reflecting trends in AI-driven biomedical systems and cross-disciplinary innovation . Scientific Awards: Teaching Prize of the University of Münster (2021) Lehrpreis des Fachbereichs Mathematik/Informatik (2021) AI Starter Grant on neuroscience-inspired deep learning (2022) Advising & Grants: Mentors PhD students in AI applications for 3D printing , insect monitoring , and medical education . Holds grants from BMBF , DFG , and Else Kröner-Fresenius Foundation for projects like medical tr.AI.ning and inFlame Medical Scientists College . Labs & Collaborations: Part of the Cells in Motion graduate program and Health-AI Network . Develops FIM imaging systems for Drosophila studies and insect camera traps with the Institute for Landscape Ecology . Collaborates with University Hospital Münster on AI diagnostics.

Philippe Bonnetمشاهده پروفایل

استاد

• Database Systems
• Storage Systems
• High Performance Computing
• +۶ مورد دیگر

Philippe Bonnet is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen since 2023, where he is affiliated with the Programming Languages and Theory of Computation section. Previously, he served as a Professor at the IT University of Copenhagen from 2009 to 2023 and as an Associate Professor at DIKU from 2001 to 2009. His academic journey began with a PhD from Universite Savoie Grenoble, France in 1999. Education: PhD from Universite Savoie Grenoble, France (1999) Philippe Bonnet is an experimental computer scientist with expertise in database systems and storage system software. His research focuses on the intersection of database systems and storage technologies, with significant contributions to the uFlip Benchmark, Linux multiqueue block layer, Linux framework for Open-Channel SSDs, OX architecture for computational storage, xNVMe library, and Delilah prototype for eBPF offload. His work spans database tuning, sensor networks (Cougar project at Cornell, Hogthrob and Mana projects at U.Copenhagen), and edge-based AI for predictive maintenance through the DAPHNE Project. His technical contributions bridge theoretical computer science with practical systems development. His recent publications demonstrate a strong trend toward integrating database systems with advanced storage technologies, particularly focusing on computational storage, CXL integration, and reliability mechanisms between databases and SSDs. His work bridges computer architecture, operating systems, and database systems to create more efficient data processing infrastructures, with increasing emphasis on edge-based applications and reproducibility in computer science research. Scientific Awards: ACM SIGMOD Contribution Award (2020) Professor Bonnet has served in numerous editorial and committee roles, including as Editor of Big Data Research Journal since 2021, Member of the VLDB Endowment (2020-2025), Member of ACM EIGREP, and long-standing involvement with ACM conferences. His work on the DAPHNE Project focuses on creating an open and extensible system infrastructure for integrated data analysis pipelines, particularly for edge-based AI applications in predictive maintenance. He co-authored a book on database tuning with Dennis Shasha and has been instrumental in advancing storage system software through multiple high-impact projects and collaborations.

• Machine Learning
• Natural Language Processing
• Sustainable Artificial Intelligence
• +۳ مورد دیگر

Casper Dorph-Jensen serves as a Lecturer in the Department of Computer Science at the University of Copenhagen, where he is an active member of the Machine Learning section. His academic work bridges theoretical machine learning foundations with practical applications across diverse domains, contributing to both research and educational initiatives within Denmark's premier computing institution. His research spans multiple critical frontiers in artificial intelligence. Key interests include: Natural Language Processing with emphasis on emotion-aware dialogue systems and cross-cultural adaptation frameworks Sustainable AI development addressing environmental impacts of large models Quantum machine learning applications for biomolecular simulations Medical image analysis techniques for clinical diagnostics Fairness-aware information retrieval systems and recommender algorithms Analysis of his 2024-2025 publications reveals strong interdisciplinary trends combining machine learning with quantum physics, healthcare informatics, and sustainability science. Notable patterns include the application of large language models to clinical contexts (particularly nursing values evaluation), energy efficiency concerns in AI infrastructure, and novel quantum-classical hybrid approaches for scientific computing. His work frequently addresses real-world implementation challenges in noisy environments and resource-constrained settings. No scientific awards were documented in available sources. Information regarding student supervision or specific research grants remains unavailable in current public records, though his Machine Learning section affiliation suggests participation in broader departmental initiatives like the SCIENCE AI Centre and TreeSense remote sensing project. He operates within the Department of Computer Science's Machine Learning section, which maintains dedicated high-performance computing resources and participates in the university-wide SCIENCE AI Centre. This section focuses on both theoretical ML foundations and applications in medical imaging, biological data modeling, and sustainability-focused computing, with recent projects including quantum computing initiatives and environmental monitoring systems.

• Human-Computer Interaction
• Extended Reality
• Computer Supported Cooperative Work
• +۳ مورد دیگر

Marcus Alexander Janum serves as an Instructor in the Human-Centred Computing section at the University of Copenhagen's Department of Computer Science (DIKU). His work focuses on advancing the relationship between computational technology and human activities within a collaborative research environment dedicated to innovation and well-being. His research spans Human-Computer Interaction, Extended Reality (XR/VR/AR), Computer Supported Cooperative Work, Health Informatics, and Digital Fabrication. Key emphases include designing novel interaction techniques, developing health-focused information systems, and creating inclusive computing technologies through initiatives like FemTech. The section prioritizes empirical studies with end-users to build solutions grounded in human capabilities. The Human-Centred Computing section operates modern laboratories supporting shape-changing interfaces, sensing technologies, and fabrication research. It fosters a collaborative culture through groups like the Confronting Data Co-lab, which examines ethical implications of data-driven societal trajectories, and the Fabrication Lab, which pioneers software/hardware tools for digital manufacturing.

Dan Grossmanمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Human-Centered Computing
• +۳ مورد دیگر

Dan Grossman is a Professor and Vice Director at the Paul G. Allen School of Computer Science & Engineering, University of Washington, where he has been a faculty member since 2003. His expertise spans programming languages, software engineering, and computing education research, with interdisciplinary collaborations in computer architecture and hardware/software interface studies. Education: Ph.D. from Cornell University, undergraduate from Rice University Service: ACM SIGPLAN Executive Committee, CRA Board (2014–2023), Program Chair for PLDI 2018 His research focuses on bridging theoretical and applied aspects of programming languages, contributing to high-impact publications and curriculum development. He leads a popular MOOC on programming languages and functional programming, which has been available since 2016. Scientific awards include the J. Ray Bowen Professorship for Innovation in Engineering Education. He has served on over 30 conference program committees and contributed to ACM/IEEE-CS curriculum guidelines.

Taha Khanمشاهده پروفایل

استادیار

• Computer Security
• Privacy
• Human-Computer Interaction
• +۳ مورد دیگر

Dr. Taha Khan is an Assistant Professor of Computer Science at Washington and Lee University's The College, specializing in computer security, privacy, and human-computer interaction. He holds a BS in Electrical Engineering from Lahore University of Management Sciences (Pakistan) and a Ph.D. from the University of Illinois at Chicago. His research explores cybercrime, commercial VPN privacy, and longitudinal data management in cloud storage. Key research interests include analyzing cybersecurity threats, developing privacy-centric solutions for cloud systems, and improving user interfaces for privacy management. He teaches courses on computer hardware design, internet networking, and security, emphasizing real-world problem-solving in his pedagogy. His work bridges technical security mechanisms with human behavioral aspects, focusing on vulnerabilities in modern digital ecosystems. Notable contributions include empirical studies of commercial VPN services and frameworks for retrospective cloud data management. Khan advocates integrating ethics into cybersecurity education to prepare future professionals for complex societal challenges.

Yu Liuمشاهده پروفایل

استاد

• Sustainable Computing
• Energy-Efficient Software
• Programming Languages
• +۳ مورد دیگر

Yu Liu is a Professor at the School of Computing, Binghamton University, where he has been a faculty member since 2008. His research focuses on sustainable computing, energy efficiency, and security in emerging software systems, with significant contributions to programming languages, robotics, and software-hardware interfaces. Education: MSE, Johns Hopkins University PhD, Johns Hopkins University Professor Liu's research centers on sustainable computing and energy-aware software systems. He investigates programming language designs for energy prediction, develops reliable robotics software through managed languages, and creates secure software-hardware interfaces. His work bridges theoretical foundations with practical applications in data centers, UAV systems, and multi-threaded environments, emphasizing verifiable sustainability metrics and energy-efficient resource management. His publication trends reveal a consistent focus on sustainable computing evolution, with recent work advancing verifiable sustainability frameworks in data centers (2023-2024), energy accounting for multi-threaded applications (2020), and secure cache management techniques (2022). The research spans programming language theory, robotics safety, and hardware security, demonstrating interdisciplinary integration across computer science subfields. Scientific Awards: NSF CAREER Award Google Faculty Research Award Fulbright Scholarship Professor Liu has secured significant research funding through his NSF CAREER Award and Google Faculty Research Award, supporting innovations in sustainable computing infrastructure. His Fulbright Scholarship enabled international collaboration in Slovenia, advancing global research in energy-efficient software systems. He regularly teaches core courses including Programming Languages (CS471/571) and Sustainable Computing (CS680G), mentoring the next generation of computer scientists. While specific lab affiliations aren't detailed in the source text, his research on UAV software (Jcopter) and cache security (Composable cachelets) suggests active involvement in robotics and systems security research groups at Binghamton University.

James Mickensمشاهده پروفایل

استاد

• Computer Security
• Cloud Computing
• Systems Architecture
• +۳ مورد دیگر

James Mickens is the Gordon McKay Professor of Computer Science at Harvard University's School of Engineering and Applied Sciences (SEAS). He specializes in systems security, cloud computing, and web technologies. His research focuses on fundamental advancements in secure systems design, including isolation mechanisms for AI, privacy-preserving protocols, and fault-tolerant storage solutions. Notable contributions include groundbreaking work on hypervisor security (Guillotine), TinyML vulnerability analysis, and resilient cloud storage systems (Carbink). He has been recognized with the Harvard College Professorship (2022) and tenure (2019). His work spans theoretical breakthroughs and practical implementations, often addressing critical gaps in system reliability and user privacy. Mickens' research trends emphasize proactive security measures, efficient resource management, and balancing performance with safety in distributed environments. His articles reflect a focus on real-world applicability, from browser optimization (Crom, Vesper) to cloud infrastructure resilience (Blizzard, Oort). Awards include the Harvard College Professor title, signaling exceptional teaching and scholarly impact. While specific grant details are not provided, his prolific publication record suggests sustained funding in systems research. Mickens' work often critiques conventional approaches, exemplified by his humorous yet incisive keynote critique of 'security as an afterthought.'

Peter Arsenaultمشاهده پروفایل

عضو هیئت علمی

• Computer Science
• Operating Systems
• Virtualization Technologies
• +۳ مورد دیگر

Peter Arsenault is an Adjunct Lecturer in the Computer Information Systems department at Bentley University. His professional activities include teaching and maintaining a technical blog Peter Arsenault Industries , focusing on macOS development, system administration, and virtualization technologies. His technical writing emphasizes practical implementations like objective-C programming for legacy macOS systems, QEMU virtualization automation, and network configuration strategies. He frequently explores topics such as responsive web design with Hugo/SCSS, SSH key management, and macOS-specific development workflows. Recent work includes in-depth tutorials on virtual machine automation using QEMU with socket_vmnet, Hyper-V scripting with PowerShell, and maintaining legacy macOS features like the Touch Bar through custom applications.

• Computing Architectures
• System Design and Co-Design
• Hardware-Software Systems
• +۶ مورد دیگر

Crișan Strugaru was a Professor at the Politehnica University of Timisoara, serving as Head of the Department of Computers from 1983 to 1992. He held academic positions from 1961 until his retirement in 2003, contributing significantly to the development of Romania's first School of Computers. His roles included researcher, educator, and administrator, with international grants and leadership in academic organizations such as the Romanian Academy. Education: B.S. in Electromechanics, Faculty of Electrical Engineering, Politehnica University of Timisoara (1960) Ph.D. in Computer Science, defended in 1973 with a thesis on microprogrammed control units Research Interests: Professor Strugaru specialized in computing architectures, embedded systems, hardware-software co-design, robotics, and network protocols. His work included pioneering contributions to microprocessor-based systems, industrial robot control, and digital communication systems. Awards and Recognition: Recipient of the Traian Vuia Prize (1983) for robotics innovations Honorary Member of the Academy of Technical Sciences of Romania (2005) President of the Romanian Academy’s 'General Systems and Cybernetics' sub-commission (1992) Advising and Grants: Supervised numerous B.S. and Ph.D. students, coordinated 20 research contracts, and authored 11 patents. His research teams developed the experimental TIM-S microcomputer and advanced industrial testers. Labs and Teams: Research conducted in the Department’s laboratories led to innovations in microprocessor applications and digital communication systems, with practical industrial implementations.

Newton Armstrongمشاهده پروفایل

استاد

• Instrumental and Electronic Composition
• Electronic and Digital Performance
• Sound Art
• +۵ مورد دیگر

Professor Newton Armstrong at City St George's, University of London is a composer, performer, and electronic musical instrument designer whose work bridges instrumental and electronic music with focus on human-technology-environment interactions. Ph.D., Princeton University (2006) M.F.A., Princeton University (2003) M.Mus., University of Melbourne (1996) B.Mus. (Hons), University of Melbourne (1991) His research explores: Instrumental and Electronic Composition through hybrid acoustic-electronic systems Digital Performance via custom software/hardware development Sound Art with environmental acoustics and psychoacoustic phenomena Machine Learning applications in rhythm perception and generation Experimental Music Aesthetics in 20th/21st century contexts From his 15 most recent works, key trends emerge in: Neural network models for expressive timing Spatialized sound installation design Instrument development for enactive performance Contemporary chamber music with extended techniques Temporal structure analysis through mathematical frameworks Urban acoustic ecology applications

Silvia Zorzettiمشاهده پروفایل

دانشیار مدعو

• Quantum Information Science
• Quantum Computing
• Quantum Sensing
• +۴ مورد دیگر

Silvia Zorzetti is an Adjunct Associate Professor at Northwestern University and leads the Quantum Computing Co-Design and Communication Department at Fermilab. She also heads the Quantum Information Science (QIS) Ecosystem Thrust within the Superconducting Quantum Materials and Systems (SQMS) Research Center. Her roles include leadership in workforce development and software/middleware for quantum computing. Dr. Zorzetti holds a PhD from the University of Pisa and completed a Marie Curie Fellowship at CERN. She joined Fermilab as a Bardeen Fellow in 2017 and received the DOE Early Career Award in 2023 for quantum transduction research. Research interests focus on quantum information science, including superconducting cavities, quantum computing/sensing devices, and software-hardware interfaces. She actively mentors students and interns at SQMS. Notable contributions include advancements in cryogenic material characterization, quantum transduction systems, and instrumentation control kits for qubit applications. Awards: DOE Early Career Award (2023), Marie Curie Fellowship (CERN) Leadership Roles: QIS Ecosystem Thrust Lead, 3D Software/Middleware Lead, QPU Connectivity Co-Lead Key Projects: SQMS Center, Fermilab Quantum Computing Department

Yngve Haftingمشاهده پروفایل

مدرس

• Robotics
• Digital Design
• 3D Printing
• +۳ مورد دیگر

Yngve Hafting is a Lecturer at the Department of Informatics, University of Oslo, affiliated with the Robotics and Intelligent Systems (ROBIN) research group. He holds a Master's degree in Measurement and Instrumentation from the University of Oslo (2000) and has extensive experience in engineering and education. His roles include Program Leader for the Robotics and Intelligent Systems bachelor and master programs (2019-2025). Research interests span Mechatronics, Digital Design, 3D-printing, and safety engineering. He has developed hardware/software systems for robotics labs and contributed to projects like additive manufacturing for biomedical applications. Courses taught include Digital Design and Computer Architecture (IN2060) and Digital System Design (IN3160). Publications highlight work in 3D-printed microfluidics, gait recognition systems, and wireless sensor platforms. Safety roles include Deputy Senior Safety Delegate for UiO (2014-2018) and involvement in campus safety committees and infrastructure projects like the New Life-Science Building.

Michael Franzمشاهده پروفایل

استاد

• Software Systems
• Compiler Design
• Virtual Machine
• +۹ مورد دیگر

Professor Michael Franz is a Distinguished Professor and ICS Alumni Professor in the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. He also holds a courtesy appointment in the Department of Electrical Engineering and Computer Science in the Henry Samueli School of Engineering. Franz directs UCI's Secure Systems and Software Laboratory and is a Fellow of AAAS, ACM, IEEE, and an Inaugural Fellow of IFIP. His educational background includes: Doctor of Technical Sciences in Computer Science from ETH Zurich (advisor: Niklaus Wirth) Dipl. Informatik-Ingenieur ETH degree from ETH Zurich Professor Franz pioneered mobile code and dynamic compilation research, creating early just-in-time compilation systems and co-inventing trace compilation technology that became Firefox's JavaScript engine. His current research focuses on Software Systems, particularly compiler and virtual machine techniques for making software safer, faster, or both. His work spans Computer Security, Trustworthy Computing, and Software Engineering, with recent emphasis on multivariant execution, automated software diversity, and probabilistic memory safety. Franz's research bridges theoretical foundations with practical applications, resulting in technologies deployed in major software systems used by hundreds of millions. His publication record demonstrates consistent leadership in security and systems research, with recent work focusing on survivable systems, binary analysis, and cross-platform security solutions. The publications reveal an evolution from foundational compiler techniques to sophisticated security mechanisms addressing real-world vulnerabilities, with strong emphasis on practical implementation and measurable impact. Professor Franz has received numerous prestigious awards: ACM Charles P. 'Chuck' Thacker Breakthrough in Computing Award (2020) Humboldt Research Award (2019) Distinguished Professor at UCI (2022) UCI's 'Innovator of the Year Award' (2018) Fellowships from all four major computing professional organizations Multiple Best Paper Awards at top-tier conferences As an advisor, Franz has graduated over 40 Ph.D. students, with recent graduates including Mitchel Dickerson and André Rösti. His research group has secured over $24 million in competitive grants (more than $16 million as sole PI) and received over $1 million in unrestricted industry gifts. Franz maintains strong industry connections, with many former students now at Google, Apple, and Meta, and his research directly influences commercial technologies. Leading the Secure Systems and Software Laboratory, Franz fosters a collaborative environment focused on developing innovative security solutions. The lab maintains global research partnerships and continues to advance areas like multivariant execution systems, automated software diversity, and practical security mechanisms. Current projects emphasize developing systems that maintain functionality even when compromised, addressing the evolving landscape of cyber threats with scientifically rigorous approaches.

• Artificial Intelligence
• Machine Learning
• Affective Computing
• +۳ مورد دیگر

Fahad Ahmed is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. He specializes in teaching modules such as Database Systems, Interaction Design, and Semi-structured Data Modelling. His research focuses on Artificial Intelligence, Machine Learning, Affective Computing, and Big Data Analytics with applications in healthcare, education, and environmental monitoring. Education background and prior roles are not explicitly detailed in the provided text. His recent publications (2017-2023) emphasize interdisciplinary work including serious games for emotion analysis in autism research, IoT-based environmental sensors, and machine learning applications in agriculture and sports analytics. He has contributed to both theoretical advancements (e.g., computational models, affective interaction design) and practical solutions (e.g., tangible user interfaces, data warehouse systems). His work spans multiple subfields such as emotion recognition via games, socio-economic decision-making simulations, and hardware-software integration for environmental sensing. While no specific awards are listed, his research demonstrates innovation in bridging computer science with healthcare and social sciences.