جست‌وجوی استاد و پژوهشگر

Eric Howardمشاهده پروفایل

پژوهشگر ارشد

• Quantum Physics
• Machine Learning
• Gravitational Waves
• +۴ مورد دیگر

Dr. Eric Howard is a Research Fellow at Macquarie University , affiliated with the School of Engineering , School of Mathematical and Physical Sciences , and School of Computing . His research spans interdisciplinary domains at the intersection of quantum physics, machine learning, and AI-driven systems. Key research themes include: Quantum cryptography for Industry 4.0 security Machine learning in IoT temperature sensing Adversarial AI in cybersecurity 6G wireless communication optimization Quantum information processing Deep learning for data imputation Recent publications demonstrate a focus on emerging technologies, with articles on quantum Bayesian inference , 6G signal processing , and smart city IoT systems . His collaborative work extends to blockchain-enabled supply chain visibility and generative AI applications in programming. Research collaborations span institutions in India (AIP Publishing) and Australia, with technical contributions to quantum dynamics, neural network applications, and nanosensor development.

Venkata Sriram Siddhardh Nadendlaمشاهده پروفایل

استادیار

• Cyber-physical-human systems
• Human-system interaction
• Statistical inference
• +۵ مورد دیگر

Dr. Venkata Sriram Siddhardh Nadendla serves as an Assistant Professor in the Department of Computer Science within the College of Engineering at Missouri University of Science and Technology. His research bridges theoretical foundations in information theory with practical applications in cyber-physical-human systems across critical infrastructure domains. His educational background includes: PhD in Electrical Engineering and Computer Science from Syracuse University MS from Louisiana State University BE from SCSVMV University, India Dr. Nadendla's research spans cyber-physical-human systems with particular emphasis on human-system interaction , statistical inference , and multi-agent decision making . His work integrates machine learning, game theory, and behavioral decision theory to address challenges in transportation systems, mining safety, and cybersecurity. Recent publications show growing focus on fairness in AI systems and neuromorphic computing applications. Analysis of his 15 most recent publications reveals concentration in transportation systems (20%), cybersecurity (25%), human-AI interaction (30%), and healthcare applications (10%), with remaining work spanning mining safety and theoretical decision frameworks. His research demonstrates consistent progression from theoretical foundations toward practical implementations in critical infrastructure. Dr. Nadendla is actively affiliated with the Center for Intelligent Infrastructure at Missouri S&T, where he contributes to developing smart infrastructure solutions. His work uniquely combines quantum cognition models with traditional game theory approaches to model human decision-making in complex systems.

• Cybersecurity
• Infocommunications
• Cloud Technologies
• +۵ مورد دیگر

Alexey Nikolaevich Nazarov is a Professor at the Department of Software Engineering, Faculty of Computer Science, National Research University Higher School of Economics (HSE), where he has worked since 2015. His academic and teaching experience spans 14 years, with a focus on cybersecurity, cloud technologies, and information confrontation in social media. Doctor of Technical Sciences (2000) Engineer-Mathematician, Moscow Geological Prospecting Institute (1980) UN and ITU-certified expert His research interests center on cybersecurity , information warfare , and mathematical modeling , particularly in IoT and social media contexts. Articles highlight trends in neural network intrusion detection , ferroelectric memory devices , and cloud resource optimization . He has supervised 5 postgraduate and 2 doctoral students, organized scientific seminars, and contributed to cloud technology curricula. His expertise includes international standards (ITU, VAK), Skolkovo grant #87 (2012), and leadership in cybersecurity research.

• Deep Learning
• Internet of Things (IoT) Security
• Software Defined Networking (SDN)
• +۴ مورد دیگر

Adnan Akhunzada is a prolific researcher with extensive contributions to computer science, particularly in artificial intelligence, cybersecurity, and internet of things. His work spans deep learning architectures, software defined networks, and security frameworks for emerging technologies. Research Interests include: Deep learning for micro-expression and image analysis Quantum control systems with reinforcement learning AI-based phishing and malware detection Federated learning for drone services Cryptographic protocols for UAV communications Publication Trends show expertise in: Hybrid neural network architectures Cybersecurity for industrial IoT Privacy-preserving crowdsourcing Sign language recognition datasets 5G-assisted cognitive communication

Felipe Gohring de Magalhaesمشاهده پروفایل

استادیار

• Integrated circuits
• Microelectronics
• Computer systems organization
• +۷ مورد دیگر

Felipe Gohring de Magalhaes is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he has been working since July 2018 and assumed his current position in October 2024. He holds a dual doctorate from PUC-RS (Brazil) and Polytechnique Montréal (2016), with degrees in both computer science and computer engineering. His research spans embedded system architectures, real-time systems, avionics, and cybersecurity for emerging technologies. He is affiliated with the Microelectronics and Microsystems Research Group and the Multidisciplinary Institute for Cybersecurity and Cyber Resilience, reflecting his focus on integrated circuits, microelectronics, and system security. Professor Gohring de Magalhaes has published over 40 articles in international journals and conferences, with recent work focusing on photonic integrated circuits security, optical neural networks, and post-quantum cryptography for avionic systems. His publication trend shows consistent output with increasing focus on security aspects of emerging computing technologies. He has supervised at least one PhD student to completion and teaches courses including Introduction to Programming and Operating System Kernel. His research interests align with NSERC topics in integrated circuits, microelectronics, computer systems organization, and VLSI systems.

Maha Abdelhaqمشاهده پروفایل

استادیار

• Mobile Ad Hoc Networks
• Intrusion Detection Systems
• Network Performance Analysis
• +۴ مورد دیگر

Maha Abdelhaq is an Assistant Professor in the Department of Computer Science at Princess Nourah bint Abdulrahman University. Her research spans mobile ad hoc networks, cybersecurity, and AI-driven solutions for IoT and 6G systems. She has authored over 100 publications, with recent work focusing on adaptive learning frameworks, anomaly detection, and quantum-enhanced privacy mechanisms. Her core research interests include: Network performance analysis and intrusion detection in dynamic environments Machine learning applications for IoT security and edge computing 6G network optimization using quantum and federated learning techniques Recent publications (2023-2025) reveal a strong emphasis on AI/ML-driven methodologies, with trends in: Real-time anomaly detection for cyber-physical systems Resource-aware federated learning for medical IoT Hybrid quantum-classical approaches for vehicular network security No awards, lab affiliations, or supervised students are documented. Collaborative projects frequently address emerging challenges in decentralized network security and metaverse applications.

Fernando Magno Quintão Pereiraمشاهده پروفایل

دانشیار

• Compilers
• Code Generation
• Compiler Optimizations
• +۳ مورد دیگر

Fernando Magno Quintão Pereira is an Associate Professor at the Federal University of Minas Gerais (UFMG), Brazil, specializing in compiler design and program analysis. His academic journey began with a Ph.D. from UCLA in 2008 under Jens Palsberg's supervision, establishing his foundation in compiler research. His research focuses on compilers , with core expertise in code generation , compiler optimizations , and static program analyses . Recent work explores quantum compilation, binary analysis, and security-aware compilation techniques. His publications reveal consistent contributions to major conferences including PLDI, CGO, and SPLASH, with emphasis on practical optimization frameworks and theoretical compiler advancements. Analysis of his 15 most recent publications (2020-2026) shows dominant themes in binary optimization (e.g., AnghaBench), security-aware compilation (e.g., Memory-Safe Elimination of Side Channels), and emerging architecture support (e.g., Quantum Computing Compilation). His work bridges theoretical compiler principles with real-world systems challenges. He actively contributes to the academic community through: Program committees for PLDI (2020-2025), CGO (2021-2026), and SPLASH conferences Leadership roles including CGO Finance Chair (2026) and PLDI Diversity & Inclusion Co-Chair (2023-2024) Organizing JENSFEST 2024 and serving on multiple conference steering committees Pereira maintains an active research group evidenced by continuous publication output and conference leadership, with his personal website ( homepages.dcc.ufmg.br/~fernando/ ) serving as a hub for his academic activities.

• network security
• network measurement and analysis
• cloud computing
• +۴ مورد دیگر

Dr. Kuai Xu serves as a Professor of Computer Science at Arizona State University's School of Mathematical and Natural Sciences within the New College of Interdisciplinary Arts and Sciences. He maintains affiliations with the Center for Cybersecurity and Trusted Foundations, focusing on securing critical network infrastructures. His academic credentials include: Ph.D. in Computer Science, University of Minnesota (2006) M.S. in Computer Science, Peking University, China (2001) B.S. in Computer Science, Peking University, China (1998) Dr. Xu's research centers on network security , network measurement , and IoT systems , with significant contributions to smart home security, network behavior analysis, and social media epidemiology. His work bridges theoretical modeling and practical implementations for real-world network challenges. Recent publications (2022-2025) reveal a concentrated focus on IoT security frameworks, machine learning-driven activity inference from device traffic, and pandemic surveillance through social media analysis. Key themes include DNS security hardening, attack graph modeling, and privacy-preserving spatial analytics in smart environments. Through courses like ACO 331 (Network Forensics Analysis) and ACO 361 (Secure Coding Concepts), Dr. Xu mentors students in cybersecurity fundamentals while supervising research via ACO 399 and individualized instruction (ACO 499). His teaching integrates cutting-edge research into classroom applications. As an active affiliate of ASU's Center for Cybersecurity and Trusted Foundations, Dr. Xu contributes to interdisciplinary initiatives addressing emerging threats in home networks, IoT ecosystems, and social media platforms.

• Cybersecurity and Privacy
• Artificial Intelligence
• Distributed Computing
• +۶ مورد دیگر

Dr. Keshav Sood is a Senior Lecturer at Deakin University's School of Information Technology, where he leads research in cybersecurity, AI, and next-generation networks. His affiliations include roles as Graduate Research Coordinator and South Asia Country Coordinator. He completed his PhD at Deakin University and a post-doctoral fellowship at the University of Newcastle. Research Interests: Dr. Sood focuses on securing distributed systems, with emphasis on: Federated learning for intrusion detection in IoT/5G networks Biometric privacy in immersive technologies (VR/AR) RF fingerprinting for IoT device authentication Quantum-resistant software-defined networks Adversarial robustness in voice authentication systems His publications consistently explore AI-driven security frameworks, with recent work addressing data sparsity in IoT sensors, cross-domain IIoT authentication, and phishing mitigation using large language models. Awards: Professor of IT Award (2016) IEEE TNSE Excellent Reviewer (2023) Deakin HDR Supervision Award (2023) Course Team Award for Industry Certification Alignment (2021) Supervision & Grants: Dr. Sood currently advises 8 graduate researchers and has secured $655,313 in competitive funding. Key projects include: Smart Farming Cyber Resilience (DFAT Maitri Grant) Secure Access for Critical Infrastructure (Cyber CRC) IoT Data Integrity for Defense Systems (Australian Defence) He leads the Deakin Cyber Research and Innovation Centre, focusing on scalable security solutions for industry partners.

• Digital Communications
• Signal Processing
• Specific Emitter Identification
• +۷ مورد دیگر

Donald R. Reising serves as a Guerry and UC Foundation Professor of Electrical Engineering in the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). He holds appointments in both the Electrical Engineering department and the Computational Science program, with active roles in university governance as Faculty Senate Chair (2022-2025) and member of multiple strategic committees including the PhD Computational Science Committee. B.S. in Electrical Engineering, University of Cincinnati (2006) M.S. in Electrical Engineering, Air Force Institute of Technology (2009) Ph.D. in Electrical Engineering, Air Force Institute of Technology (2012) Dr. Reising's research spans three interconnected domains: wireless security through Specific Emitter Identification (SEI) and RF fingerprinting, smart grid intelligence for real-time disturbance analysis, and radiation effects characterization in microelectronics. His work integrates machine learning with signal processing to solve critical infrastructure protection challenges, particularly in adversarial environments where traditional security measures fail. Recent publications demonstrate increasing focus on deep learning countermeasures against SEI spoofing attacks and edge-computing solutions for power grid resilience. His 15 most recent publications reveal strong emphasis on adversarial machine learning (6 articles), SEI robustness under environmental stressors (5 articles), and smart grid data analytics (3 articles), with growing interdisciplinary work in quantum correlations and transportation safety. This trajectory shows evolution from foundational RF fingerprinting techniques toward comprehensive security frameworks for critical infrastructure. IEEE Chattanooga Chapter's Outstanding Engineer Award (2022) UTC’s Outstanding University Service Award (2018) AFRL Sensors Directorate Dr. Samuel M. Burka Award (2013) Association of Old Crows Research Excellence Award (2009) MASINT Committee Academic Excellence Award (2009) Dr. Reising leads multiple research initiatives including the RF Security Lab and Smart Grid Analytics Group, securing consistent funding from DoD agencies (AFRL, ARL), NSF, and industry partners like EPRI. His service extends to advising graduate students through the Computational Science PhD program and directing undergraduate research in radiation effects characterization. Current projects focus on SEI resilience against deep learning attacks, quantum-enhanced signal processing, and edge-computing solutions for grid cybersecurity.

• Wireless Communications
• Signal Processing
• Artificial Intelligence
• +۵ مورد دیگر

Berker Peköz serves as Assistant Professor in the Department of Electrical Engineering and Computer Science at Embry-Riddle Aeronautical University's College of Engineering. His expertise spans wireless communications, artificial intelligence security, and hardware systems, with significant contributions to 5G/6G technologies and aerospace applications. His educational foundation includes: B.S. in Electrical & Electronics Engineering M.S. in Electrical Engineering Ph.D. in Electrical Engineering Research focuses on cutting-edge intersections of communications and AI, particularly transformer model security, antenna-based authentication, and error-correction for emerging hardware. His work bridges theoretical innovation with practical aerospace implementations, evident in patents for antenna array geometries and publications addressing real-world challenges like contested IoT environments and spectral efficiency. Recent publications (2019-2025) show accelerating output with increasing emphasis on AI security frameworks. Scientific recognition includes: National Academy of Inventors membership (2019) Tau Beta Pi honor society induction (2018) Funding is evidenced through patent activity and consistent publications, though specific grants aren't detailed. He mentors students through undergraduate courses (EE 307 Avionics I, EE 327 Electrical Engineering Fundamentals) with likely graduate research supervision in communications security. His interdisciplinary approach connects electrical engineering fundamentals with next-generation AI and aerospace systems, positioning students for careers in secure communications and hardware innovation.

Sébastien Bardinمشاهده پروفایل

پژوهشگر

• Program Analysis
• Formal Methods
• Security
• +۵ مورد دیگر

Sébastien Bardin is a Senior Researcher and CEA Fellow at the Software Safety and Security Laboratory of Commissariat à l'Energie Atomique (CEA) in Paris-Saclay, France, with affiliation to University Paris-Saclay. He leads significant research initiatives including the BINSEC group on binary-level security analysis (since 2012) and the QBricks group on quantum program verification (since 2020), and served as Head of the Software Quantum Program at CEA LIST from 2021-2023. His research focuses on formal methods and automatic program analysis with applications in software security. Key areas include binary-level security analyses such as vulnerability detection & assessment, reverse engineering, and malware deobfuscation, as well as quantum programming and verification. His methodological expertise spans symbolic execution, abstract interpretation, software model checking, and SMT solving. Bardin's publications demonstrate consistent impact across top venues in security and formal methods, with notable papers at ESOP, CAV, ICSE, NDSS, and S&P. His work on robust symbolic execution, directed fuzzing, and binary-level analysis has established him as a leading researcher in security-oriented program analysis. Recent publications show growing emphasis on quantum program verification alongside continued contributions to binary security analysis. Scientific Awards: ICSE 2021 ACM SIGSOFT Distinguished Paper Award RTAS 2021 Best Paper Award CAV 2021 Selected Paper CEA Fellow (2021-present) ACM Senior Member (2021-present) Bardin actively mentors PhD students and has advised numerous researchers who have received recognition including GDR Sécurité and GDR GPL PhD awards. His service to the community is extensive, with leadership roles in GDR Sécurité, RESSI, and organizing major conferences including CAV 2023 (sponsor co-chair) and FIC 2023 (scientific program chair). He also contributes to multiple program committees across security and formal methods venues.