Toyosi Oyinloye is the Deputy Head of the School of Computer and Engineering Sciences at the University of Chester, and Programme Leader of the NCSC-certified MSc Cybersecurity programme. She holds a PhD in Cybersecurity from the University of Chester and has over 20 years of experience in software development, database management, and cybersecurity. Her academic roles include teaching final-year computer programming (Swift for iOS Development) and postgraduate cybersecurity modules like Software Exploitation and Research Methods. Education: PhD in Cybersecurity, University of Chester (2024) MSc in Cybersecurity, University of Chester BSc in Computer Science, University of Ilorin, Nigeria PGCert in Learning and Teaching in Higher Education, University of Chester Research Interests: Toyosi focuses on enhancing software protection mechanisms, particularly through Inter-Process Control Flow Integrity to mitigate control flow hijacks. She also investigates mitigating social engineering attacks and applying data visualization for incident response. Her work spans cybersecurity domains such as mobile application security, exploit development, and firmware forensics. Professional Recognition: Fellow of the Higher Education Academy (FHEA) Fellowship (2023) British Computer Society Membership (2022) Teaching & Leadership: Toyosi supervises undergraduate programming projects and postgraduate cybersecurity research. She leads initiatives to elevate programme quality across the School and serves as an Internal Examiner for PhD candidates. Her leadership extends to mentoring and collaborative projects. Labs & Teams: Her research is affiliated with the University of Chester's Culture and Society Research and Knowledge Exchange Institute, where she contributes to interdisciplinary cybersecurity advancements.
Konrad Witaszczyk is a Research Associate and PhD student at the University of Cambridge's Department of Computer Science and Technology, affiliated with the Computer Laboratory. His work focuses on the CHERI project, exploring kernel compartmentalization in CheriBSD and advancing memory-safe systems. He has contributed to QEMU emulation for CHERI-RISC-V, CheriBSD ports, and Poudriere infrastructure for package management. Education: BSc in Theoretical Computer Science (Jagiellonian University) and MSc in Computer Science (University of Copenhagen). His MSc thesis, 'Capability-aware memory copying between address spaces,' was supervised by Ken Friis Larsen and David Chisnall. Teaching includes Advanced Operating Systems (Part II L341/ACS L41) and supervision of student projects like the PCuABI Linuxulator for CheriBSD. Committed to EDI initiatives, he serves on the Equality, Diversity, and Inclusion Committee and Postgraduate Students' Forum. Professional activities include mentoring interns on Morello systems and contributing to open-source projects like FreeBSD and QEMU. Contact: GE10 office, konrad.witaszczyk@cl.cam.ac.uk.
Frans Kaashoek is the Charles Piper Professor in MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Parallel and Distributed Operating Systems (PDOS) group, focusing on secure systems, formal verification, and distributed computing. His work emphasizes crash-safe systems, concurrent programming, and cryptographic security. Education: PhD in Computer Science from Vrije Universiteit Amsterdam (1992), thesis on group communication in distributed systems under Andy Tanenbaum. Research interests include operating systems, networking, programming languages, and computer architecture. Notable projects: FSCQ (verified crash-safe file system), Perennial (framework for verifying concurrent systems), and Noria (high-performance web backend). Awards: ACM SIGOPS Mark Weiser Award (2001), ACM Prize in Computing (2010), National Academy of Engineering membership (2006), and American Academy of Arts and Sciences membership (2012). Publications: Over 150 papers on systems software, verification, and security. Authored textbooks like Principles of Computer System Design: An Introduction and xv6 commentary.
Darshana Jayasinghe is a Postdoctoral Research Associate at the School of Electrical and Information Engineering (EIE) , University of Sydney. He holds a PhD from the University of New South Wales (UNSW), completed in 2017, and worked as a Research Associate there until December 2022. His research focuses on hardware security, particularly side-channel analysis attacks and countermeasures. Education: PhD, University of New South Wales (2017) Research Interests include: Side-channel analysis attacks (Power Analysis, EM Attacks, Fault Injection) Countermeasures (Balancing, Random Execution, Masking) On-chip sensors for FPGA monitoring FPGA reliability under power fluctuations Publication Trends reveal expertise in: Hardware Security (15/15 articles) FPGA Vulnerabilities (10/15 articles) Cryptographic Countermeasures (12/15 articles) Sensor Development (5/15 articles)
Dr. Holger Eichelberger is part of the Academic Staff in the Software Systems Engineering (SSE) department at the University of Hildesheim's Institute of Computer Science. He is affiliated with Faculty 4: Mathematics, Natural Sciences, Economics and Computer Science. His roles include membership in the Managing Committee of the Institute of Computer Science and the Committee for Student Scholarships. He has extensive experience in model-based software development, Industry 4.0 platforms, and performance engineering. Research Interests: Software Engineering for adaptive systems, Asset Administration Shells (AAS), IIoT platforms, MLOps, container orchestration, and open-source tools like EASy-Producer and SPASS-meter. His work focuses on bridging research and industrial needs, particularly in smart manufacturing and edge computing. Publications highlight contributions to IIoT platform analysis, AI integration in Industry 4.0, and performance benchmarking of communication protocols. He has organized conferences like ICPE and SSP and reviewed for top journals such as IEEE Transactions on Software Engineering. Key projects include the IIP-Ecosphere platform and contributions to standards like AAS. Collaborations involve institutions like the University of the West Indies and industry partners through funded projects like BMBF AI-Lab HAISEM. His research emphasizes reproducibility, interoperability, and scalable solutions for industrial challenges.
Dr. Asieh Salehi Fathabadi is a Lecturer (Assistant Professor) in the Cyber-Physical Systems (CPS) group at the University of Southampton, UK. She specializes in formal methods for software engineering, with a focus on Event-B methodology for designing safe and secure systems. Her research addresses challenges in autonomous systems, responsible AI, and human-AI trust dynamics. She leads the Verifiably Safe and Trusted Human-AI Systems (VESTAS) and HANA-HAIP projects as Principal Investigator and contributes to initiatives like HD-Sec and HICLASS . Her work integrates formal verification into critical system development, emphasizing security and safety. Recent publications explore exception handling in secure hardware (CHERI), socio-technical trust frameworks for defense systems, and human intervention in self-driving vehicles. She supervises two PhD students in Computer Science and actively participates in the Rodin formal methods community. Dr. Salehi Fathabadi has over 13 years of research experience, applying formal methods to aerospace systems, embedded software, and cybersecurity. Her interdisciplinary approach bridges theoretical rigor with practical engineering solutions for modern complex systems.
Jens-Peter Kaps is an Associate Professor at George Mason University's Volgenau School of Engineering, jointly affiliated with the Department of Electrical and Computer Engineering and the Department of Cyber Security Engineering. He holds a PhD in Electrical and Computer Engineering from Worcester Polytechnic Institute (2006), an MS from the same institution, and a BS from Munich University of Applied Sciences. As a co-director of the Cryptographic Engineering Research Group (CERG), his research focuses on cryptographic hardware design, side-channel analysis, post-quantum cryptography, and IoT security. Dr. Kaps has led numerous research projects funded by agencies like the National Science Foundation (NSF) and NIST, including initiatives on countermeasures for post-quantum cryptographic algorithms and lightweight cryptography in embedded systems. He has organized major conferences such as CHES 2008 and SHARCS 2012, and is actively involved in standardization efforts for cryptographic algorithms. His teaching responsibilities include courses on computer organization and side-channel security. He has advised over 50 senior design projects, focusing on cryptographic hardware implementations, IoT devices, and security tools. His lab work emphasizes practical applications of cryptographic engineering, with a strong emphasis on hardware-software co-design and vulnerability assessment. Dr. Kaps collaborates with industry partners like McQ Inc. and Riscure, and his research outputs include open-source platforms like FOBOS for side-channel analysis. His work bridges theoretical cryptography with real-world hardware implementations, addressing critical challenges in secure embedded systems and post-quantum security.
Dr. Dimitrios Bakalis is an Assistant Professor at the Department of Physics, University of Patras, specializing in Digital Electronic Circuits and Systems. He joined the faculty in 2004 and focuses on the design and control of digital circuits, emphasizing low-power testing and built-in self-test (BIST) methodologies. His academic roles include teaching courses such as Computer Programming I, Digital Electronics, and Microcomputer Architecture at both undergraduate and postgraduate levels. Education: Diploma in Computer Engineering and Informatics (University of Patras) Master’s Degree in Computer Science and Technology (University of Patras) PhD in Computer Engineering and Informatics (University of Patras) Research Interests: His work revolves around VLSI design, arithmetic circuits, and low-power techniques. Key areas include modulo arithmetic circuits, fault-tolerant systems, and reconfigurable computing architectures. He has published over 50 papers in top-tier journals and conferences, contributing to advancements in digital circuit efficiency and reliability. Teaching: He instructs core courses in digital electronics and computer architecture, integrating cutting-edge research into his pedagogy. His MSc courses focus on FPGA-based digital system design, emphasizing practical applications. Labs/Teams: His research aligns with the Electronics & Computers sector within the Department of Physics, collaborating on projects involving arithmetic core optimization and low-power testing strategies.
Lukasz Ziarek is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and serves as the Associate Dean for Academic Affairs in the School of Engineering and Applied Sciences. His research focuses on concurrency, real-time systems, distributed systems, and formal verification. He holds a PhD from Purdue University (2011) and a BS from the University of Chicago (2003). His research explores topics such as real-time Java implementations, session types for distributed protocols, and visual debugging techniques. Recent work includes formal models for secure multiparty computation, IoT device validation, and optimizing visual SLAM systems for robotics applications. He has contributed to frameworks like Juav (a Java-based UAV autopilot) and RTDroid (a real-time Android extension). Ziarek has received notable awards including the 2023 IEEE Technological Innovation Award, 2022 Meyerson Teaching Award, and 2018 NSF CAREER Award. His grants include collaborative research on UAV software infrastructure and real-time communication protocols. He actively develops tools like PTDETECTOR for JavaScript library analysis and Anodize for mixed-criticality systems. His work integrates formal methods with practical systems, addressing challenges in embedded systems security, compiler optimization, and real-time programming language design. He maintains a lab focused on advancing reliable software for autonomous systems and distributed computing environments.
Professor Bradley Evans is a distinguished Earth observation and remote sensing specialist at the University of New England, where he holds a position in the Faculty of Science, Agriculture, Business and Law within the School of Environmental and Rural Science. His expertise spans environmental science, biodiversity conservation, and the application of hyperspectral imaging spectroscopy to solve real-world environmental challenges. Previously, he has held significant positions including Director of Australia's Terrestrial Ecosystem Research Network and Director of Sydney Informatics Hub at The University of Sydney. PhD in Environmental Science, Murdoch University, Western Australia, 2013 Bachelor of Science with Honours in Environmental Science, Murdoch University, Western Australia, 2009 Bachelor of Science in Energy Studies, Murdoch University, Western Australia, 2009 Advanced Diploma in Marketing Management, TAFE NSW, Bradfield College, 1999 CASA RPAS sub 25kg (Multirotor Drone) certification Professor Evans's research focuses on applying advanced remote sensing techniques to environmental monitoring and conservation. His work integrates hyperspectral imaging with ecological modeling to address critical issues such as koala habitat mapping, forest health assessment, and water quality monitoring. He has pioneered approaches using plant fluorescence to model growth patterns and has contributed significantly to NASA's OCO2 mission. His recent work emphasizes the development of open-source tools for hyperspectral imaging, making advanced remote sensing more accessible to researchers worldwide. Analysis of Professor Evans's recent publications reveals a strong trend toward practical applications of hyperspectral imaging across diverse environmental contexts. His work spans from precision agriculture applications for cotton farming to koala habitat conservation, demonstrating the versatility of remote sensing technologies. The research shows increasing integration of machine learning techniques with hyperspectral data, enhancing the accuracy and efficiency of environmental monitoring systems. There's also a notable emphasis on open-source solutions, reflecting his commitment to democratizing access to advanced remote sensing technologies. 2016 – Terrestrial Ecosystem Research Network NSW – NSW Chief Scientist Award Multiple travel scholarships from NCCARF, EUFAR, and Australian Research Council 2010 Centre of Excellence for Climate Change PhD top-up Scholarship 2008 Master class Scholarship from Wentworth Group of Concerned Scientists Professor Evans has successfully supervised numerous PhD and Master's students across multiple institutions, demonstrating strong mentorship capabilities. His research is supported by substantial grants including the $198K NSW Department of Environment Koala's in the Landscape project (2023), the University of Sydney's Koala's in the Air project ($70K), and significant funding for the OpenHSI initiative. He has been a Chief Investigator for the Australian Research Council Training Centre on CubeSats, UAVs and Their Applications, securing funding for innovative remote sensing projects. His work with NASA JPL's Surface Biology and Geology Study and collaborations with international space agencies demonstrates the global impact of his research. At the University of New England since 2023, Professor Evans has established the Earth Observation Laboratory with a special focus on water and wildlife habitat (particularly koalas) and riverine water quality. He serves as Vice President of Earth Observation Australia and participates in the AquaWatch Steering Committee for the Commonwealth Department of Defence. His laboratory actively collaborates with industry partners like HyVista Corporation and academic institutions including The University of Sydney. The lab emphasizes open-source approaches to remote sensing technology, exemplified by the OpenHSI project, which has created accessible hyperspectral imaging solutions for researchers worldwide.
Fuyuan Zhang is a Postdoctoral Researcher at the Max Planck Institute for Software Systems, specializing in advanced software testing methodologies and formal verification techniques. His research focuses on improving the reliability and security of AI systems, quantum computing frameworks, and concurrent systems through innovative testing criteria, adversarial attacks, and compositional reasoning. Key areas of expertise include: Large Language Model (LLM) testing and validation Quantum program analysis and security Adversarial machine learning and neural network robustness Formal verification of concurrent and cyber-physical systems Automated bug detection in complex software systems His work bridges theoretical foundations with practical applications, addressing critical challenges in AI safety, quantum software reliability, and system-wide security certification.
Chengming Zhang is a tenure-track assistant professor in the Computer Science Department at the University of Houston. He recently completed his Ph.D. in Computer Engineering from Indiana University in May 2024, where he was a member of the HiPDAC group working on building efficient and scalable deep learning systems under the advisement of Prof. Dingwen Tao. He has extensive industry research experience with multiple projects at Microsoft Research, Meta Reality Labs, and Argonne National Laboratory. His educational background includes: Ph.D. in Computer Engineering, Indiana University (May 2024) Dr. Zhang's research focuses on creating efficient machine learning systems that can operate effectively across diverse hardware platforms. His work bridges the gap between theoretical algorithms and practical implementation with particular emphasis on efficient machine learning systems for training and inference on parallel, distributed, and heterogeneous hardware; AI algorithm-hardware co-design, particularly for GPU architectures; effective efficiency algorithms including model compression, data efficiency, and parameter-efficient tuning; and large-scale deep learning applications such as Large Language Models, Agents, and Image/Video Generation systems. His publication record demonstrates a consistent focus on optimizing deep learning systems through hardware-aware approaches. The majority of his work centers around making deep learning more efficient through techniques like model compression, hardware-algorithm co-design, and memory optimization. His research spans both theoretical algorithm development and practical system implementation, with publications in top-tier conferences including the International Conference on Supercomputing, PPoPP, and AAAI. A notable trend in his work is the emphasis on practical efficiency - not just theoretical improvements but solutions that deliver real-world performance gains on actual hardware. Dr. Zhang is actively building his research group at the University of Houston and has secured significant computational resources for his lab, including multiple high-performance computing servers worth a total of $130K (two 8-Ada6000 servers and one dual-4090 servers).
Nikol Rummel is a Professor at Ruhr-Universität Bochum , specializing in Computer-Supported Collaborative Learning (CSCL) , Artificial Intelligence in Education , and Human-Computer Interaction . Her work bridges educational technology with hardware reverse engineering , focusing on AI-orchestrated learning environments and adaptive tools for collaboration. Her research spans AI-orchestration tools ( Pair-Up , Co-Designing Orchestration Support ), collaborative problem-solving ( Learning Alone or Together ), and hardware reverse engineering education ( Promoting Skill Acquisition ). She investigates how multimodal data and adaptive feedback enhance learning outcomes, teacher practices, and emotional regulation. Her publications highlight trends in generative AI for academic writing , collaboration scripts , and cognitive obfuscation in cybersecurity education. Collaborations with researchers like Vincent Aleven, Christof Paar, and Steffen Becker underscore her interdisciplinary approach. Nikol Rummel’s work emphasizes teacher dashboards ( What Information Should CSCL Dashboards Provide? ), dynamic student pairing ( Combining Dialog Acts and Skill Modeling ), and emotional engagement in learning ( How to Enjoy Writing Papers ).
Iyán Méndez Veiga is a Research Associate and Doctoral Student at the Lucerne School of Computer Science and Information Technology, part of the Lucerne University of Applied Sciences and Arts (HSLU). Their research focuses on quantum cryptography, post-quantum security protocols, and privacy amplification. They have conducted studies on adversarial wiretap channels and reproducible builds in open-source systems like Arch Linux. Education includes a BSc in Physics from the University of Oviedo, Spain, and an MSc in Physics from Ulm University, Germany. Their work bridges theoretical cryptography with practical implementations, such as developing the randextract library for validating privacy amplification algorithms. Key projects include quantum-safe hardware security modules, implications of post-quantum cryptography on certificate management, and quantum cryptography in practice. Presentations emphasize topics like quantum hardware verification and secure communication protocols. Collaborations with institutions like the University of Applied Sciences and Arts Northwestern Switzerland highlight their applied research focus.
Yang Li is an Assistant Professor of Computer Science at Iowa State University, specializing in computer architecture, machine learning, and their intersection. He holds a Ph.D. and M.S. from Carnegie Mellon University (2020), an M.S.E. from the University of Texas at Austin (2013), and a B.E. from Tsinghua University (2011). Prior to academia, he worked as a Senior Research Scientist at Meta, a Research Scientist at Meta, and a Researcher at Microsoft. His research focuses on large language models (LLM) acceleration, on-device AI, cloud infrastructure optimization, and spatiotemporal forecasting. He has contributed to over 20 peer-reviewed publications at top venues like ASPLOS, EMNLP, and ICASSP. Research Interests: Algorithmic and systems-level acceleration of LLMs On-device AI co-design and privacy Cloud memory/power management Graph-based spatiotemporal forecasting Teaching: Taught COMS 6730 (Advanced Topics in ML), COM S 321 (Computer Architecture), and guest-lectured on graph signal processing. Recent teaching scores include 4.75/5.0 (Fall 2024) and 4.67/5.0 (Spring 2025). Awards: IBM Patent Application Award (2021) and multiple patents on power management systems for data centers. Service: Program committee member for DAC 2024, NeurIPS 2024, and ICLR 2025. Reviewer for ACM TACO, IEEE TPAMI, TPDS, and others.
