جست‌وجوی استاد و پژوهشگر

Ibrahim Khalilمشاهده پروفایل

استاد

• Security
• Privacy
• Federated Learning
• +۴ مورد دیگر

Professor Ibrahim Khalil is a faculty member in the School of Computing Technologies at RMIT University, Melbourne, Australia. He holds a PhD in Computer Science from the University of Bern (2003) and has extensive industry experience in Silicon Valley focusing on secure network protocols. His research spans Security, Privacy, Federated Learning, Blockchain, Quantum Computing, and Distributed Systems. He leads high-impact projects funded by ARC grants (DP250100582, DP220100215, etc.) and international initiatives like the EU’s SELFY project. His work addresses challenges in secure AI data analytics, privacy-preserving systems, and critical infrastructure protection. Khalil supervises PhD/Masters students on topics ranging from federated learning security to quantum-enhanced machine learning. Education: PhD in Computer Science (University of Bern, 2003); prior roles at EPFL, Osaka University, and industry tech hubs. Research Interests: Privacy-Preserving Technologies Blockchain Applications in Healthcare and Supply Chains Quantum Computing for Machine Learning Secure Edge Computing and Federated Learning IoT Security and Critical Infrastructure Protection Grants & Collaborations: Over 10 major grants since 2017, including ARC Discovery/Linkage Projects and international partnerships (QNRF, EU). Notable projects include Privacy-Aware Digital Twins for Critical Infrastructure and Federated Learning frameworks for GenAI models. Advising & Labs: Active supervisor of 25+ research projects since 2013, focusing on anomaly detection, secure data analytics, and blockchain-based systems. Collaborates with industry partners on defense and healthcare tech.

Shahid Razaمشاهده پروفایل

استاد

• Cybersecurity
• Internet of Things (IoT) Security
• AI/Machine Learning & IoT Security
• +۳ مورد دیگر

Shahid Raza is a Professor of Cybersecurity at the University of Glasgow's School of Computing Science. He previously led the RISE Cybersecurity Unit in Sweden, establishing it as a leading research group. His expertise spans IoT Security, PKI, AI-driven cybersecurity solutions, and hardware/data security. Raza holds a PhD and Docentship from Uppsala University, alongside a Bachelor's with a Gold Medal for academic excellence. Education: B.Sc. (Computer Science, 3.99/4.0 CGPA, Gold Medal), Licentiate, PhD, and Docentship in Cybersecurity from Sweden. He leads EU-funded projects like H2020 CONCORDIA and Horizon Europe CUSTODES, coordinating initiatives such as the Cyber Node and Cyber Range. Active in cybersecurity policy, he serves on the EU SCCG, ECSO, and EARTO Security & Defence Research working groups. Research Interests Public Key Infrastructure (PKI) for IoT AIAgent-Driven Cybersecurity Solutions IoT Certification Standards Hardware Security for Low-Power Devices Grants & Projects Coordinator: Horizon Europe CUSTODES Technical Leader: H2020 Arcadian-IoT Founder: RISE Cyber Range (Sweden's largest cybersecurity test facility) Awards & Memberships IEEE Senior Member Gold Medal for Academic Excellence (Bachelor's)

Michael Pradelمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Program Analysis
• +۹ مورد دیگر

Michael Pradel is a full professor at the University of Stuttgart, specializing in software engineering, programming languages, and machine learning. He will join CISPA as a faculty member from September 2025 while retaining his Stuttgart position. His research focuses on: Neuro-symbolic software analysis Web application analysis Dynamic analysis and test generation Quantum software testing Machine learning for code Recent publications address: LLM-based program repair (RepairAgent, Treefix) WebAssembly analysis (Wasm-R3, LintQ) Python security and analysis (DyLin, DyPyBench) Quantum program analysis (LintQ) Scientific awards: Ernst-Denert Software Engineering Award Emmy Noether grant (1.3M Euro) ERC Starting Grant (1.5M Euro) 3x ACM SIGSOFT Distinguished Paper Award at FSE ACM Distinguished Member Best Paper/Distinguished Paper Awards at ISSTA, ASE, ASPLOS, MSR Key contributions include: DeepBugs for name-based bug detection Getafix for automated bug fixing LintQ for quantum program analysis DyLin for Python dynamic analysis Neuro-symbolic developer tools

Julian Adamekمشاهده پروفایل

پژوهشگر

• Computational Cosmology
• Theoretical Cosmology
• Large-scale structure of the Universe
• +۳ مورد دیگر

Julian Adamek is a computational cosmologist and lead developer of gevolution , a general-relativistic N-body code for cosmological simulations. His work focuses on modeling relativistic effects in cosmic structure formation to better understand gravity’s role on large scales and dark energy. Research Interests: Computational Cosmology, Theoretical Cosmology, Large-scale structure of the Universe, Relativistic N-body simulations. Technical Leadership: Lead developer of gevolution , a public cosmological simulation code available via GitHub. Recent publications span diverse applications of deep learning in geospatial analytics, environmental monitoring, and computer vision, including phenology modeling, biomass mapping, conflict assessment, and 3D reconstruction from point clouds. Key Trends: Integration of AI/ML for environmental tasks, cross-domain applications (cosmology, ecology, forestry), and satellite data processing. Technical Focus: Transformer networks, diffusion models, super-resolution imaging, and ensemble learning for uncertainty quantification. Julian collaborates with researchers in cosmology and geospatial science, though specific students or awards are not mentioned in the provided texts.

Yiorgos Makrisمشاهده پروفایل

استاد

• Hardware Security
• Trusted Systems
• Machine Learning in Semiconductor Manufacturing
• +۹ مورد دیگر

Yiorgos Makris is a Professor in the Department of Electrical and Computer Engineering at the Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas, since July 2011. Previously, he was a faculty member at Yale University for over a decade. He holds a Ph.D. in Computer Engineering from the University of California, San Diego, and a Diploma in Computer Engineering from the University of Patras, Greece. Education: Ph.D. in Computer Engineering, University of California, San Diego (2001) M.S. in Computer Engineering, University of California, San Diego (1997) Diploma in Computer Engineering and Informatics, University of Patras, Greece (1995) Research Interests: Hardware Security and Trustworthiness Statistical Side-Channel Fingerprinting Machine Learning in Semiconductor Manufacturing Trusted and Reliable Integrated Circuits Hardware Trojans in Wireless Cryptographic ICs On-Die Learning and Emergent Technologies His work focuses on enhancing hardware security through statistical methods, machine learning, and formal verification, with applications in analog/RF ICs, post-production calibration, and secure IC design. Key Contributions: Co-Founder and Site-PI of NSF CHEST I/UCRC (Hardware and Embedded System Security and Trust) Leader of the Safety, Security, and Healthcare Thrust at TxACE (Texas Analog Center of Excellence) Director of the Trusted and RELiable Architectures (TRELA) Lab Grants and Funding: NSF, NIH, SRC, ARO, AFRL, AFWERX, DARPA, DOE, and industry partnerships with Boeing, Northrop Grumman, IBM, Intel, Qualcomm, etc. Recent grants include projects on DNA storage security, analog neural networks, and malicious hardware detection. Awards and Recognition: IEEE Fellow (2025) Best Paper Awards at DATE'13, VTS'15, DCAS'22 Best Hardware Demonstration Awards at HOST'16 and HOST'18 Erik Jonsson School Faculty Research Award (2020) Labs and Teams: TRELA Lab (Focus: Secure Hardware Design, Trusted Architectures) CHEST I/UCRC (Industry-University Collaboration)

Shahram Rahimiمشاهده پروفایل

استاد

• Computational Intelligence
• Machine Learning
• Artificial Intelligence
• +۱۰ مورد دیگر

Shahram Rahimi is a Professor and Department Head in the Department of Computer Science at the University of Alabama, College of Engineering. He concurrently holds an Adjunct Professor position at Mississippi State University. His research spans computational intelligence, machine learning, healthcare AI, cybersecurity, and quantum computing. He leads the PATENT Lab, focusing on predictive analytics, decision support systems, and AI-driven healthcare solutions. His educational background includes a Ph.D. in Computer Science. Key research areas include multi-agent systems, generative models, and predictive maintenance. He has served as an editor for journals like Scalable Computing: Practice and Experience and Informatica . Rahimi’s recent work emphasizes secure MLOps, quantum algorithms, and patient-centric medical systems. His publications address challenges in explainable AI, anomaly detection, and healthcare informatics. He actively contributes to conferences and journals in AI, cybersecurity, and computational intelligence. Editorial Roles: Scalable Computing, Engineering Letters, Informatica Labs: Predictive Analytics & Technology Integration (PATENT) Lab Key Focus Areas: Healthcare AI, Quantum Computing, Cybersecurity, Explainable Machine Learning

• Theoretical Chemistry
• Electrochemistry
• Catalysis
• +۶ مورد دیگر

Christopher J. Stein is an Associate Professor of Theoretical Chemistry at the Technical University of Munich (TUM), part of the TUM School of Natural Sciences. His research focuses on theoretical (electro-)catalysis, developing electronic-structure models and solvation/embedding methods to understand and optimize catalytic processes. He leads the Stein Group, which integrates computational chemistry with high-throughput simulations to advance energy materials and battery technologies. His work emphasizes realistic modeling of catalyst behavior under operational conditions and has contributed to advancements in quantum embedding and automated reaction mechanism exploration. Education and Career: Earned his PhD in Theoretical Chemistry, with postdoctoral research at Caltech (2017-2020). Became an Associate Professor at TU Munich in 2023. He previously held roles at Karlsruhe Institute of Technology and contributed to projects like the BIG-MAP Materials Acceleration Platform. Research Interests: Theoretical chemistry, electrochemical interfaces, battery materials, high-throughput computational methods, and machine learning integration. His group explores topics like solid electrolyte interphases, charge transfer mechanisms, and automated workflows for materials discovery. Awards: While no explicit awards are listed, his contributions to materials acceleration platforms and theoretical catalysis have been widely recognized in the field. His work has been featured in journals like Journal of Chemical Physics , Chemical Science , and Angewandte Chemie . Labs/Teams: Leads the Stein Group at TUM, collaborating with institutions like the Munich Data Science Institute and MIRMI. His lab focuses on computational tools for accelerating energy material development, including quantum embedding and cloud-based simulations.

Pradip Sharmaمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Blockchain
• +۵ مورد دیگر

Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.

• Cybersecurity
• Data Security and Privacy
• GRC (Governance, Risk, Compliance)
• +۶ مورد دیگر

Dr. Gowri Sankar Ramachandran is a Senior Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in cybersecurity and distributed systems. She holds a PhD from KU Leuven (Belgium) and a postdoctoral position at the University of Southern California (USC). Her research focuses on open-source software security, runtime threat detection, blockchain applications, and IoT vulnerabilities. Notable contributions include the FUSE tool for detecting malicious packages and the discovery of hyperlink hijacking vulnerabilities affecting millions of domains. Research interests span software supply chain security, metadata-based risk analysis, and generative AI for cyber risk modeling. Awards include Best Paper Awards at ACM CBSE (2016), Mobiquitous (2017), and BigMM (2019). Collaborations include projects with CSIRO, the City of Los Angeles, and the University of São Paulo. She teaches courses on cybersecurity, database management, and network security, and actively supervises PhD students in cybersecurity and blockchain domains. Recent publications address blockchain-based data governance, quantum-resilient IoT protocols, and decentralized identity systems. Her work bridges academic research with real-world impact, addressing critical challenges in digital systems security and privacy.

Joseph Alejandro Gallego Mejiaمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۱۲ مورد دیگر

Joseph Alejandro Gallego Mejia is an Assistant Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He holds a PhD with meritorious distinction in Systems and Computing Engineering from the National University of Colombia, along with a Master’s and dual Bachelor’s degrees in Systems and Computing Engineering and Industrial Engineering. PhD in Systems and Computing Engineering, National University of Colombia (Meritorious Distinction) Master of Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Industrial Engineering, National University of Colombia His research focuses on artificial intelligence, machine learning, computer vision, quantum machine learning, natural language processing, and cybersecurity. He explores robustness estimation, anomaly detection, incremental learning, and scalable software architectures for AI systems. His work bridges theoretical foundations and practical applications in health, remote sensing, and edge computing. The recent publications reflect a strong trend in interdisciplinary AI research, combining machine learning with quantum computing, cybersecurity, and natural language understanding. His work spans domains such as satellite imagery analysis, medical diagnostics, IoT security, and conversational AI, demonstrating a commitment to scalable and robust intelligent systems. Keywords across publications include Computer Science, Machine Learning, Quantum Computing, and Cybersecurity, with subfields ranging from adversarial robustness to hybrid quantum-classical models. Scientific distinctions include: PhD with meritorious distinction, National University of Colombia Postdoctoral fellow, Frontier Development Lab (Trillium), supported by NASA and ESA He has served as a reviewer for top-tier journals and conferences including Neurocomputing, IEEE Access, Radioscience, NeurIPS, and NLDL. Though no formal grants are listed, his postdoc was funded by NASA and ESA, indicating significant external support. He teaches courses in programming, data science, machine learning, deep learning, NLP, and software engineering. He founded the tech company Sammu and mentors students through instruction and research supervision. He is actively involved in research and teaching, contributing to innovative programs in AI and computing education. His lab and team affiliations are not explicitly stated, but his work suggests collaboration with AI, quantum computing, and cybersecurity research groups.

Yongshan Dingمشاهده پروفایل

استادیار

• Quantum Computing
• Computer Architecture
• Quantum Algorithms
• +۴ مورد دیگر

Yongshan Ding is an Assistant Professor of Computer Science and Applied Physics at Yale University. He leads the Quantum Systems Lab (QSL) and directs Yale's Quantum Science and Engineering Certificate program. Affiliated with the Yale Quantum Institute (YQI) and Computer Systems Lab (CSL), his research focuses on quantum computing systems spanning algorithms, architecture, and hardware/software co-design. Dr. Ding earned his Ph.D. from the University of Chicago and a B.Sc. from Carnegie Mellon University. He has received prestigious awards including the Siebel Scholarship (2020) and William Rainey Harper Dissertation Fellowship (2020). Research Interests: Quantum computing architectures, noise-resilient quantum algorithms, error correction methods, quantum compilation, hardware-software co-design, and NISQ system optimization. Editorial Roles: Editor at Quantum journal and Associate Editor at ACM Transactions on Quantum Computing . Labs: Founder of Yale's Quantum Systems Lab (QSL) and contributor to the Computer Systems Lab (CSL). Awards: Siebel Scholarship (2020) William Rainey Harper Dissertation Fellowship (2020) QCE Best Paper Award (2024) IEEE Micro Top Picks Honorable Mention (2023, 2020) IBM Q Best Paper Award, First Prize (2020) Mathematics Competition Runner Up (2016)

Riham AlTawyمشاهده پروفایل

دانشیار

• IoT Security
• Lightweight Cryptography
• Blockchain Consensus Mechanisms
• +۳ مورد دیگر

Riham AlTawy is an Associate Professor and MTIS Program Director at the Department of Electrical and Computer Engineering, University of Victoria. She previously held positions as an NSERC Postdoctoral Fellow at the University of Waterloo and an NSERC Canada Graduate Scholar at Concordia University. Her research focuses on IoT security, blockchain consensus mechanisms, lightweight cryptographic primitives, and privacy-preserving protocols. She leads the IoTSec group, which develops application-specific cryptographic solutions for IoT authentication and privacy challenges. Education includes postdoctoral training at the Communication Security (ComSec) group (University of Waterloo) and doctoral studies at Concordia University. Her work has led to publications in top venues such as IEEE Transactions and CANS conferences. She actively seeks PhD research assistants and postdoctoral fellows in cryptographic research. Key research areas include authentication protocols for edge computing, privacy in cross-domain systems, and lightweight algorithms for constrained devices. Her group emphasizes practical solutions for real-world IoT security challenges.

• Quantum Computing
• Artificial Intelligence
• Neuromorphic Computing
• +۵ مورد دیگر

Professor Frank Zhigang Wang is a faculty member at the School of Computing , University of Kent. His research focuses on Quantum Computing , Neuromorphic Computing , and Cloud Computing , with significant contributions to Memristor Technology and Green Computing . He has secured £5 million in research grants from EC/UK/industries and chaired/co-chaired over 10 international conferences, including IEEE and ACM events in Manchester, Delhi, Beijing, and Shanghai. Key research areas: Quantum Computing, Artificial Intelligence, Neuromorphic Systems, Cloud Security. Professional roles: Fellow of the British Computer Society, former IEEE Region 8 Area 2 Coordinator. His work explores Landauer Bound optimization in quantum systems, Spin-Encoded Quantum Computers , and Topological Electronics . Recent publications address post-quantum cryptography and memristor-based neuromorphic architectures . He has supervised 15 PhD students (14 completed) and 7 research fellows. Awards include Best Teacher Award nominations (2016, 2022) and ACM/IEEE Super Computing Challenge Finalist (2007).

Roozbeh Razavi-Farمشاهده پروفایل

استادیار

• Machine Learning
• Cybersecurity
• Federated Learning
• +۵ مورد دیگر

Roozbeh Razavi-Far is an Assistant Professor at the Faculty of Computer Science and the Canadian Institute for Cybersecurity at the University of New Brunswick. His research focuses on machine learning, big data analytics, and cybersecurity of cyber-physical systems and IoT devices. He has authored/co-authored over 150 publications and is listed by Stanford as among the top 2% of most cited researchers (2022). His work spans federated learning, transfer learning, quantum machine learning, and dependable AI systems. He serves as an Associate Editor for Neurocomputing, Machine Learning with Applications, and IEEE Transactions on Industrial Cyber-Physical Systems, among others. As an IEEE Senior Member, he chairs IEEE Computational Intelligence and Systems, Man, and Cybernetics Societies. Previously, he directed the Learning System and Cybernetics Group at the University of Windsor (2016–2022). His research interests emphasize security in non-stationary environments, adversarial machine learning defenses, and real-time analytics for smart grids. Awards include NSERC-DG, NSERC-ECR, and USRG grants. He has mentored students who received NSERC Alexander G. Bell, MITACS, and Ontario Graduate Scholarships. His recent publications highlight advancements in privacy-preserving split learning, blockchain-based federated learning security, and graph-based malware detection. He also explores quantum computing applications in AI and cybersecurity frameworks for cyber-physical systems.

John D. Kubiatowiczمشاهده پروفایل

استاد

• Computer Architecture
• Quantum Computing
• Distributed Systems
• +۷ مورد دیگر

Professor John D. Kubiatowicz is a faculty member at the University of California at Berkeley in the Department of Electrical Engineering and Computer Sciences since 1998. He holds a PhD in Electrical Engineering and Computer Science (minor in Physics) from MIT (1998), an M.S. in EECS (1993), and a double B.S. in Electrical Engineering and Physics (1987) from MIT. His research interests span Quantum Computing Architectures Distributed Systems and Storage Network Security and Peer-to-Peer Protocols Introspective and Manycore Operating Systems Edge and Fog Computing Hardware-Assisted Security He has pioneered systems like OceanStore , a global-scale distributed file system, and Tessellation , a manycore OS with continuous adaptation. The scientific awards he has received include Presidential Early Career Award (PECASE, 2000) Scientific American 50 (2002) Diane S. McEntyre Teaching Award (2003) IEEE ICRA Best Paper (2025) George M. Sprowls Award for MIT PhD thesis (1998) Okawa Research Grant (1998) Best Paper at International Conference on Supercomputing (1993) His recent publications focus on Quantum Circuit Design and Optimization Edge/Fog Computing Architectures Secure Runtime Systems Distributed Garbage Collection Manycore OS Innovations Hardware-Assisted Security Mechanisms He leads the Quantum Architecture Research Center and co-founded the SWARM Lab at Berkeley, advancing a vision of self-adapting, secure systems from the chip level to internet scale.