جست‌وجوی استاد و پژوهشگر

Alastair F. Donaldsonمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Verification
• +۵ مورد دیگر

Alastair F. Donaldson is a Professor in the Department of Computing at Imperial College London, where he leads the Multicore Programming Group. His primary affiliation is with Imperial College London's Department of Computing within the broader Faculty of Engineering structure. He serves as a Program Committee Member for major conferences including ASE, PLDI, and POPL. His research spans Programming Languages , Compilers , Verification , Testing , and Multicore Programming , with significant contributions to randomized testing techniques. He pioneered GraphicsFuzz (acquired by Google in 2018) and developed innovative approaches like grammar mutation for parser testing, metamorphic fuzzing for C++ libraries, and specialized tools for GPU API validation. His work bridges theoretical foundations with industrial impact, particularly in compiler correctness and GPU computing. Analysis of his recent publications reveals a strong trend toward fuzzing infrastructure development (40%), GPU/compiler testing (30%), and formal methods integration (30%). His research increasingly focuses on large-scale automated testing for complex systems including WebGPU, Dafny, and Rust, while maintaining rigorous theoretical grounding in concurrency models and memory semantics. Donaldson has held significant leadership roles including General Chair for PLDI 2020 and Program Chair for ECOOP. His research has been supported through conference organizational roles and industrial collaborations, notably the GraphicsFuzz spinout. He actively contributes to the PL community through mentoring initiatives like PLMW and community-building efforts such as The PLDI Song. He leads the Multicore Programming Group at Imperial College London, focusing on practical tools for compiler and GPU driver validation. The group's work combines theoretical program analysis with real-world testing frameworks, maintaining strong industry connections through projects adopted by Google and other technology companies.

Kevin Borgolteمشاهده پروفایل

استاد

• Security
• Privacy
• Software Engineering
• +۴ مورد دیگر

Kevin Borgolte is a full professor for Software Security in the Faculty of Computer Science at Ruhr University Bochum (RUB) in Bochum, Germany. He is affiliated with HGI Bochum and the DFG Excellence Cluster CASA: Cyber Security in the Age of Large-Scale Adversaries. His research focuses on improving the security, resilience, and privacy of software-based systems, with particular emphasis on real-world networked and distributed software systems. This work encompasses vulnerability discovery and mitigation, program and protocol analysis, and understanding how networked software is deployed and used. He has developed novel techniques to identify and mitigate Internet security threats, including detecting malicious software, discovering unknown attacks on networked systems, and conducting security-relevant measurements like large-scale IPv6-wide scanning. Professor Borgolte is a strong advocate for open science and open code, believing it is crucial for research reproducibility. His research group's GitHub organization is rub-softsec, and his earlier work is available through UCSB SecLab and UChicago NOISE Lab repositories. Third place in DARPA Cyber Grand Challenge (with Shellphish CGC team) He actively participates in Security Capture the Flag competitions with Shellphish and serves on multiple program committees for major security conferences including IEEE/ACM International Conference on Automated Software Engineering (ASE), IEEE Symposium on Security & Privacy (S&P), and USENIX Security Symposium. At RUB, he serves on the University Commission for Teaching, Faculty Council, and IT Advisory Board of the Faculty of Computer Science. His research group focuses on practical security challenges in real-world systems, with emphasis on empirical research and building deployable security tools that address vulnerabilities in networked software systems.

• Computer Vision
• Deep Learning
• Image Processing
• +۳ مورد دیگر

Anastasia Antsiferova is a researcher at the Institute for System Programming of the Russian Academy of Sciences (ISP RAS) and the MSU AI Institute, Lomonosov Moscow State University, actively contributing to software engineering and artificial intelligence research as evidenced by her publication at ASE 2025. Her research focuses on critical intersections of computer vision and generative AI, with specialization in: Watermarking techniques for AI-generated content Security validation frameworks Image processing benchmarking methodologies Ethical implications of synthetic media Her recent work presented at ASE 2025 demonstrates how watermarking systems can be rigorously evaluated for generated images, addressing emerging challenges in digital provenance and content authentication within the generative AI landscape. This research bridges software engineering practices with computer vision security requirements.

Tobias Heerمشاهده پروفایل

استاد

• Network Security
• IT Security
• Offensive Security
• +۵ مورد دیگر

Prof. Dr. Tobias Heer serves as Professor and Dean of Computer Science and Engineering at Esslingen University of Applied Sciences, where he also holds Senate and Building Committee roles. Based in Room F 01.312 at Campus Esslingen (Flandernstraße 101, 73732 Esslingen), he leads the IT Security Lab while teaching Network Security, IT Security, Offensive Security, and Security of Industrial Networks courses. His research spans industrial network security with emphasis on time-sensitive networking (TSN), deterministic networking (DetNet), and offensive security methodologies. Key focus areas include spoofed traffic detection, secure resource allocation protocols, internet-wide scanner analysis, and global software patching practices. His work bridges theoretical protocol design with industrial implementation challenges in critical infrastructure systems. Recent publications (2022-2024) reveal strong trends in industrial network security, particularly TSN/DetNet integration and real-time traffic protection. His team develops evaluation frameworks like GeNESIS for industrial scenarios while analyzing global patching discipline across sectors. Earlier foundational work includes Host Identity Protocol standards (RFC 7401, 8002) and distributed hash table applications for mesh networks. No scientific awards are documented in the provided materials. While advising activities aren't specified, his patent portfolio indicates active industry collaboration. He heads the IT Security Lab which focuses on industrial network security testing and protocol development, with recent projects examining PRP-based transmission systems and time-deterministic firewall mechanisms.

Kai Petersenمشاهده پروفایل

استاد

• Software Engineering
• Agile Methods
• Empirical Software Engineering
• +۵ مورد دیگر

Kai Petersen serves as Professor of Software Engineering at Flensburg University of Applied Sciences within the Faculty of Business, Department of Business Management / Business Informatics. He teaches in the Business Informatics program, provides academic advising, and maintains office C 206 with contact number 0461/805-1470. Petersen leads multiple research initiatives including FLAIR (Flensburg Artificial Intelligence Research), the Software Factory, and TechStartUp@HS-Flensburg (TeStUp). His research program centers on empirical approaches to software engineering with specialization in Agile Methods, Software Metrics, Software Security, and increasingly the integration of Artificial Intelligence. Petersen has pioneered work in Value-based Software Engineering and systematic mapping studies, bridging theoretical frameworks with practical industry applications through extensive corporate collaborations. Analysis of Petersen's recent publications reveals an evolving research trajectory from traditional software engineering methodologies toward AI-integrated approaches. His 2025 work on LLM-based systematic mapping studies represents cutting-edge exploration of AI in academic research processes, while his 2023 publications maintain strong connections to practical applications in public sector BI systems, regression testing decision support, and value-focused development frameworks. Petersen's scientific contributions have received significant international recognition: Listed among top 2% most influential scientists worldwide (1960-2019 study) Ranked among top 10 software engineering scientists globally and #1 in Germany (2010-2017) Recognized as top 100 Swedish scientist in technology/mathematics by Fokus magazine Three highly impactful Journal of Systems and Software publications Most cited work has accumulated 375 citations with significant industry adoption Petersen attributes his research success to strategic collaborations with industry partners that enable real-world testing of methodologies. His TechStartUp@HS-Flensburg initiative demonstrates commitment to translating academic research into practical applications, while his leadership in FLAIR positions him at the forefront of AI integration in software engineering. Student projects under his guidance frequently contribute directly to his research outputs, creating a productive academic-industry-student ecosystem. As contact person for FLAIR and leader of the Software Factory, Petersen actively shapes the university's research direction in AI applications, data science, and modern software development practices, ensuring his work maintains strong relevance to both academic discourse and industry needs.

• Chemical Process Control
• Biodiesel Production
• Distillation Modeling
• +۴ مورد دیگر

Adel Mhamdi is a Professor at RWTH Aachen University's Department of Chemical Engineering within the Faculty of Mechanical Engineering. His research focuses on process systems engineering with emphasis on nonlinear model predictive control, hybrid modeling, and sustainable process design for chemical and biochemical systems. He leads research in electrified biodiesel production, distillation optimization, and polymerization process control. His research interests span chemical process control, biodiesel production optimization, distillation modeling, hybrid mechanistic-data-driven approaches, polymerization processes, and heat transfer optimization. Mhamdi develops advanced control strategies including economic NMPC, distributed control architectures, and chance-constrained optimization to address challenges in flexible operation of energy-intensive processes. His work integrates computational fluid dynamics with process modeling for reactor design and optimization. Analysis of his recent publications reveals strong trends in electrification of chemical processes, particularly biodiesel production with heat integration. His research increasingly incorporates machine learning for hybrid modeling and employs advanced computational techniques like Bayesian optimization for reactor geometry design. Key application areas include renewable energy systems, polymer manufacturing, and separation processes. Mhamdi actively supervises doctoral researchers including M. El Wajeh, J.M. Faust, and P.J. Joy who appear as first authors on multiple publications. His research group collaborates extensively with the Mitsos group at RWTH Aachen, securing publications in top journals including Industrial & Engineering Chemistry Research and Computers & Chemical Engineering . Current projects focus on real-time optimization of electrified processes and development of open-source modeling platforms like HybridML.

• Political Sociology
• Security Studies
• Biopolitics
• +۵ مورد دیگر

Sven Opitz is a Professor at the Department of Sociology, Philipps University of Marburg, specializing in political sociology and social analysis. He leads subproject C12 on pandemic situations and has held visiting positions at institutions like VU Amsterdam and the University of Edinburgh. His work bridges sociology, legal theory, and biopolitics. PhD in Sociology (summa cum laude), University of Basel (2010) M.A. in Political Science, Sociology, and Modern German Literature, University of Hamburg (2003) Research focuses on biopolitics, epidemic space, temporal governance, and symbiosis in biosocial contexts. He examines how security dispositifs and technological infrastructures mediate social and ecological relationships, particularly during pandemics. His recent publications analyze epidemic ecologies, pandemic preparedness, and the spatial politics of disease control. Articles explore topics like digital pandemic modeling, health security infrastructures, and temporal politics in law and economy. Scholarship from Evangelisches Studienwerk Villigst (2005) Scholarship from Landesstiftung der Hansestadt Hamburg (2004) Opitz is co-editor of Soziale Systeme and collaborates with institutions like SYNMIKRO. He has organized international conferences on topics such as security dispositifs, epidemic ecologies, and Bruno Latour’s theories.

• Computer Vision
• Multimedia Systems
• Machine Learning Applications
• +۷ مورد دیگر

Timothy K. Shih is an active academic researcher with over 30 years of scholarly contributions, evidenced by his extensive publication record from 1991 through 2025. With more than 380 publications spanning numerous prestigious venues including IEEE Access, Multimedia Tools and Applications, and Lecture Notes in Computer Science, he maintains a robust research profile with consistent annual output (20+ papers in peak years). His work demonstrates leadership through frequent senior/corresponding author positions and collaborations with numerous researchers across international institutions. Dr. Shih's research interests encompass a diverse range of computer science disciplines with particular emphasis on Computer Vision , Human-Computer Interaction , and AI Applications . His work bridges theoretical advancements with practical implementations in educational technology, accessibility solutions, and multimedia systems. Recent publications reveal a strategic focus on applying deep learning techniques to solve real-world problems in sign language recognition, gesture analysis, and wireless sensing applications. Analysis of his publication trends over the past five years shows increasing specialization in multimodal AI systems, with significant contributions to sign language technology (including Arabic Sign Language recognition), WiFi-based human activity recognition, and music technology applications. His research demonstrates strong interdisciplinary connections between computer vision, machine learning, and human-centered computing, with practical applications spanning educational technology, accessibility solutions, and smart environments. Through his mentorship, Dr. Shih has guided numerous junior researchers who have become frequent collaborators, including Chih-Yang Lin, Hsin-Hung Cho, and Tipajin Thaipisutikul. His research program appears well-funded through consistent publication output across multiple project areas, suggesting successful grant acquisition in computer vision, AI, and educational technology domains. Current work indicates active involvement in cutting-edge research on diffusion models for audio processing, enhanced sign language recognition systems, and novel approaches to WiFi-based human interaction analysis.

• Computer Science
• Wireless Sensor Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Muhammad Khalil Afzal is a faculty member at COMSATS University Islamabad within the Department of Computer Science . His career focuses on Internet of Things (IoT) , Wireless Sensor Networks , and Machine Learning applications in network optimization. Key collaborations with researchers like Byung-Seo Kim and Sung Won Kim Published extensively in IEEE Access , Sensors , and Future Generation Computer Systems Research spans data-driven intelligence , QoS in IoT , and smart transportation systems : Developed graph convolutional GRU frameworks for traffic prediction Explored NOMA for low-latency communications in 5G Innovated blockchain-based privacy preservation in vehicular networks

Christian Dietrichمشاهده پروفایل

استاد

• Operating Systems
• Real-Time Systems
• Embedded Systems
• +۵ مورد دیگر

Christian Dietrich is a Professor at Technische Universität Braunschweig, specializing in operating systems, real-time systems, and software dependability. Previously affiliated with Friedrich-Alexander-Universität Erlangen-Nürnberg and Leibniz Universität Hannover, he leads the Systems Research and Architecture (SRA) group. His research focuses on dependable embedded operating systems, fault tolerance, static analysis, and compiler optimization. He has contributed to projects like dOSEK, cHash, and MELF, addressing challenges in real-time scheduling, redundancy reduction, and variability management in system software. Education: PhD in Computer Science from Leibniz Universität Hannover (2019). Research Interests: Embedded systems dependability, real-time OS design, static/dynamic analysis, fault injection, and compiler-driven optimization. His work bridges theory and practice, with applications in automotive and safety-critical systems. Recent Work: Recent articles explore compiler caching efficiency (IRHash), memory management (HyperAlloc), and fault-space pruning for hardware fault injection. His work on cHash reduced redundant compilations by 80%, earning a USENIX ATC Best Paper Award. Awards: ECRTS 2018 Outstanding Paper, RTAS 2015 Best Paper, and multiple teaching accolades. Supervised over 30 theses, including topics like live patching, fault injection frameworks, and stack-sharing mechanisms. Lab/Team: Heads the SRA group, collaborating on projects like AHA (Hardware Abstraction), CLASSY-FI (fault injection), and CADOS (RTOS variability management). Active in conferences like OSDI, EuroSys, and RTSS.

• High-Performance Computing
• Parallel Computing
• Power Management
• +۳ مورد دیگر

Barry Rountree is a researcher affiliated with Lawrence Livermore National Laboratory (LLNL), specializing in High-Performance Computing (HPC), Power Management, and Parallel Computing. His work focuses on optimizing energy efficiency, fault tolerance, and performance in large-scale supercomputing environments. He has contributed extensively to the development of tools and frameworks for power-aware scheduling, hardware overprovisioning, and visualization performance optimization. Key research interests include HPC system design, processor manufacturing variability, and energy-efficient algorithms. Rountree has collaborated with institutions like NERSC and Intel on projects involving exascale computing challenges and resource management strategies. His publications span conferences such as SC, IPDPS, and ICS, emphasizing practical solutions for scalable and sustainable HPC systems. Notable contributions include the SpackNVD vulnerability audit tool, the msr-genie framework for processor register navigation, and adaptive power management strategies for visualization applications. His work highlights interdisciplinary approaches to addressing computational challenges in science and engineering domains.

• Computer Vision
• Machine Learning
• Computer Graphics
• +۵ مورد دیگر

Ziyan Wang is a researcher affiliated with Carnegie Mellon University's School of Computer Science, Department of Computer Science. Their work focuses on computer graphics, machine learning, and medical imaging, with a strong emphasis on dynamic capture and animation of human hair and heads. They hold a PhD in Computer Science from Carnegie Mellon University (2023). Research interests include 3D modeling, neural networks, reinforcement learning, and applications in medical informatics. Notable contributions include high-fidelity hair modeling using computed tomography and neural dynamic models for volumetric hair capture. Their work spans conferences like CVPR, NeurIPS, and ECCV, demonstrating expertise in both theoretical and applied aspects of computer vision and graphics. Publications highlight advancements in diffusion models, multi-agent reinforcement learning, and domain adaptation for fault diagnosis. Collaborations span institutions like the University of Washington, Max Planck Institute, and NVIDIA Research, reflecting interdisciplinary engagement. Recent work explores AI-generated content in virtual environments and cybersecurity in package management systems.

• Machine Learning
• Optimization Algorithms
• Deep Learning
• +۷ مورد دیگر

Bin Gu is a professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), specializing in machine learning and artificial intelligence. Previously affiliated with institutions including Nanjing University of Information Science and Technology (former position) and Nanjing University of Aeronautics and Astronautics (PhD 2011). His research focuses on optimization algorithms, spiking neural networks, federated learning, kernel methods, adversarial robustness, and neuromorphic computing. Education: PhD in Computer Science (2011) from Nanjing University of Aeronautics and Astronautics. Prior affiliations include Tianjin University, Boston University, University of Science and Technology of China, and Southeast University. Research Interests: Extensive work on machine learning theory and applications, including robust learning, federated systems, neural architecture design, and privacy-preserving techniques. Over 200 publications in top venues such as AAAI, NeurIPS, ICLR, ICML, KDD, and IEEE journals. Publications Trends: Recent focus on spiking neural networks (SNNs), federated learning frameworks, and optimization methods for handling adversarial attacks and privacy constraints. Notable contributions include scalable algorithms for kernel-based learning, robust SVM formulations, and neuromorphic computing architectures. Labs/Teams: Active in AI research groups focused on neural networks, optimization, and distributed learning systems. Collaborates with industry and academic partners on applied AI solutions.

• Cryptography
• Coding Theory
• Error-Correcting Codes
• +۳ مورد دیگر

Sebastian Bitzer is a researcher at the Technical University of Munich (TUM), affiliated with the Chair of Coding and Cryptography led by Prof. Wachter-Zeh. He is part of the Institute of Communications Engineering within the Faculty of Electrical Engineering and Information Technology. His work focuses on cryptography, coding theory, and error-correcting codes with applications in post-quantum security and algorithmic design. Key research interests include code-based cryptography, decoding algorithms for non-binary cyclic codes, and the development of secure cryptographic protocols. Recent studies explore zero-knowledge proofs, syndrome decoding attacks, and error structure-aware decoding methods. Bitzer has contributed to submissions for NIST post-quantum cryptography standardization and advanced decoding techniques in parallel channels. Publications highlight innovations in signature schemes (e.g., FuLeeca), burst error correction, and metric-based coding strategies. His work bridges theoretical coding advancements with practical cryptographic implementations. No specific grants or awards are explicitly mentioned in the provided texts, though his active publication record suggests ongoing academic engagement. Labs/Teams: Active member of the TUM Chair of Coding and Cryptography, collaborating on projects involving post-quantum cryptography and error-correcting code applications.

• Parallel Computing
• Group Theory
• Lattice Field Theory
• +۴ مورد دیگر

Werner Wetzel serves as a Professor within the Department of Theoretical Physics at Heidelberg University, where he has been actively involved in teaching and research. His academic contributions are evident through a series of specialized courses delivered between 2004 and 2009, covering advanced topics in theoretical physics and computational methods. These courses include Parallel Programming with MPI or Threads for BW-Grid-like systems, Group Theory, Lattice Field Theory and Numerical Simulations, Loop Quantum Gravity, Quantum Monte Carlo, and Quantum Mechanics with a focus on interpretation questions and mathematical foundations. His research expertise spans several critical areas of theoretical physics, particularly emphasizing computational approaches. Key fields of interest include Parallel Computing for high-performance physics simulations, Group Theory applications in physical systems, Lattice Field Theory and associated numerical simulation techniques, Quantum Gravity (with specific work in Loop Quantum Gravity), Quantum Monte Carlo methods, and the foundational aspects of Quantum Mechanics. Prof. Wetzel's course on parallel programming demonstrates his commitment to integrating cutting-edge computational tools, such as MPI and threading models, into physics research, addressing practical challenges in parallelization, debugging, and optimization for large-scale simulations. Despite the detailed course descriptions and teaching materials provided, the available texts do not mention any scientific awards, honors, or fellowships attributed to Prof. Wetzel. Similarly, there is no information regarding his supervision of students (PhD, Master's, etc.) or details of research grants he may have secured. His institutional affiliation is clearly with the Institute of Theoretical Physics at Heidelberg University, situated at Philosophenweg 16 in Heidelberg, Germany, which serves as the hub for his academic activities.