جستجوی استاد راهنمای دانشگاهی

Valerie Viet Triem Tong is a Research Professor at the Paris Institute of Electrical and Electronic Engineering, School of Electrical and Electronic Engineering. She has established herself as a leading researcher in cybersecurity with a particular focus on information flow control systems, Android security, and malware analysis. Her work spans both theoretical foundations and practical security tools development. Her research interests center on Information Flow Control , where she has developed frameworks for monitoring and enforcing security policies at both operating system and application levels. She has made significant contributions to Android Security , creating tools for detecting malicious behavior in mobile applications and addressing privacy concerns in smartphone environments. Her work in Malware Analysis includes developing advanced techniques for tracking and visualizing malware behavior, with emphasis on evasive Windows malware and Android malware in the wild. She also investigates Peer-to-Peer Network Security , focusing on Sybil attack resistance and distributed identity management. Analysis of her publication record reveals a consistent trajectory from foundational work in information flow theory to increasingly applied security research. Her recent work shows a strong emphasis on practical security tools (DaViz, GUI-Mimic, BAGUETTE), security evaluation methodologies (Digital twin, CERBERE), and addressing contemporary challenges in malware analysis (debiasing datasets, handling obfuscated applications). A notable trend is her integration of visualization techniques with security analysis to make complex security data accessible to both experts and machine learning systems. As an advisor, she has mentored numerous researchers who have become first authors on significant publications, including Radoniaina Andriatsimandefitra, Tomás Concepcion Miranda, and Cedric Herzog. Her research has been supported by multiple grants focused on cybersecurity infrastructure, though specific grant details are not provided in the available information. Dr. Tong is actively involved with the CIDre security research group in Rennes, contributing to collaborative projects that bridge theoretical security models with practical implementation challenges. Her work on information flow monitoring has evolved from basic research to applied systems that address real-world security concerns across multiple platforms.

• Information Flow Control
• Android Security
• Malware Analysis and Detection
• +۵ مورد دیگر

Aravind Machiry is an Assistant Professor at Purdue University's Electrical and Computer Engineering Department and a founding member of the Purdue Systems and Software Security (PurS3) Lab . His research focuses on system security, particularly vulnerability detection, prevention, and secure system development using static/dynamic program analysis, fuzzing, type systems, and machine learning. Designing practical solutions for software and embedded system security Recipient of NSF CAREER and Amazon Research awards Active participant in SPLASH 2025 as OOPSLA Review Committee member His recent work includes automated vulnerability detection in embedded software, spatial memory safety enhancements, and security analysis of GitHub workflows. He has received recognition for his research through multiple distinguished paper awards and industry funding. Selected scientific awards include NSF CAREER Award (2024) Amazon Research Award (2022) Test of Time Award at FSE 2023 for DynoDroid Distinguished Paper Award at OOPSLA 2022 for 3c Qualcomm Innovation Fellowship (2025) His research team has developed frameworks like ARGUS for taint analysis of CI/CD workflows and FuzzUEr for UEFI interface fuzzing, discovering hundreds of critical vulnerabilities in open-source projects and thousands of command injection flaws in GitHub repositories.

• Software Security
• Embedded Systems
• Program Analysis
• +۹ مورد دیگر

Mathias Payer is an associate professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive research group since 2018. He focuses on strengthening software and system security through fuzzing, vulnerability mitigation, and compiler-based approaches. His work includes open-source prototypes and contributions to embedded systems, IoT security, and trusted execution environments. Education: PhD in Computer Science (Dr. sc. ETH) from ETH Zurich (2012), postdoctoral researcher at UC Berkeley (2012–2014), and assistant professor at Purdue University (2014–2018). Tenured at EPFL since 2021. Research Interests: Fuzzing frameworks, memory safety, vulnerability analysis, compiler optimizations for security, and firmware security. Projects include Enclosure , HexType , and DP3T (decentralized contact tracing). Awards: Multiple best/distinguished paper awards at top venues (e.g., Usenix Security, NDSS, RAID). Co-founded the EPFL polygl0ts and Purdue b01lers CTF teams to foster cybersecurity innovation. Labs/Teams: HexHive group, CTF initiatives, and collaborations with industry (e.g., Intel SGX, Android security).

• Software Security
• System Security
• Fuzzing
• +۵ مورد دیگر

Aws Albarghouthi is affiliated with the University of Wisconsin-Madison, USA. He is an active researcher with significant contributions to program synthesis, formal verification, and machine learning. Key roles: Author, Session Chair, Committee Member in conferences like PLDI, POPL, VMCAI, SPLASH, and ICFP. Research spans quantum computing, differential privacy, and static analysis. Research Trends include: Quantum Circuit Compilation and Optimization Probabilistic Verification of Fairness and Privacy Synthesis of Datalog and MapReduce Programs Neural-Augmented Static Analysis Bias Detection in Data Security Robustness in Machine Learning

• Program Synthesis
• Formal Verification
• Quantum Computing
• +۵ مورد دیگر

Dr. Yves Le Traon is a Full Professor of Computer Science at the University of Luxembourg, where he serves as Vice-Director of the Interdisciplinary Centre for Security, Reliability and Trust (SnT). He leads the 25-member SerVal research group (SEcurity, Reasoning and VALidation), focusing on software testing, security, and data-intensive systems. Previously, he chaired the CSC Research Unit (2013-2016) and pioneered model-driven engineering at INRIA. PhD and engineering degree in Computer Science from Institut National Polytechnique, Grenoble (1997) Former Associate Professor at University of Rennes (1998-2004) His research spans three main areas: innovative software testing and repair , Android security through static analysis and machine learning , and robust machine learning system design . Collaborations include industry leaders like PayPal, CREOS, and Cebi in fintech, smartgrid, and industry 4.0 domains. Awarded IEEE Fellow (2022) and Facebook Testing & Verification Research Award (2019) , he chairs editorial boards for STVR, SoSym, and IEEE Transactions on Reliability. His team has produced 20+ PhD graduates including Li Li (Monash University), Donia El Kateb (European Investment Bank), and Alexandre Bartel (SnT Research Associate). Commercial impact includes co-founding Datathings for runtime AI decision systems.

• Machine learning systems
• Software testing
• Software security
• +۸ مورد دیگر

Pr. Jean-François Lalande is a Professor at CentraleSupélec, affiliated with Inria's PIRAT and CIDRE teams. His research focuses on the security of IT infrastructures, Android applications, and C embedded software, including access control policies, intrusion detection tools, and software code analysis. He has led projects like PEPR DefMal (2022–2028) and ANR LYRICS (2011–2015) for privacy-preserving cryptographic protocols in NFC systems. Roles: Conference Chair (EICC 2025, EICC 2020), Workshop Organizer (IWSMR, 3SL, COLSEC, SHPS). Editorial: Guest Editor for journals like Information Technology and Future Generation Computer Systems . His work spans malware analysis, privacy in mobile systems, and security validation. He has served on technical program committees for international conferences (IEEE, ACM) and national events like SSTIC. His students include PhD graduates such as Romain Brisse and Tomas Miranda Concepcion.

• Security of IT infrastructures
• Security of Android applications
• Security of C embedded software
• +۶ مورد دیگر

Simone Aonzo is a Class 2 Lecturer in the Digital Security department at EURECOM, a leading research and education institution in France focused on digital sciences. He is actively engaged in cybersecurity research with a strong emphasis on malware analysis, Android security, and machine learning applications in threat detection. His research interests span several critical areas in modern cybersecurity, including: Android and Windows malware analysis Evasive techniques used by malware Machine learning vulnerabilities in security systems Binary analysis and cryptographic function detection Phishing and social engineering attacks Security hardening using AI The trends in his recent publications (2024–2025) reflect a deep focus on adversarial machine learning, evasive malware behaviors, and the application of AI in both offensive and defensive security contexts. His work frequently appears in top security venues such as RAID, NDSS workshops, and IEEE-affiliated conferences, demonstrating his active contribution to the research community. He has no listed scientific awards in the provided text. Simone Aonzo is involved in mentoring and training through academic collaborations and educational events such as the PEPR Cybersecurity Winter School. While specific advisees are not listed, his collaborative publications suggest an active role in guiding junior researchers. There is no mention of grants, but his publication output implies ongoing research funding. He also contributes to community knowledge through talks and workshops. He is associated with the Digital Security research group at EURECOM, which focuses on cutting-edge cybersecurity challenges, including malware analysis, privacy, and system security. The team employs advanced techniques in machine learning, reverse engineering, and automated analysis to study modern threats.

• Cybersecurity
• Malware Analysis
• Android Security
• +۵ مورد دیگر

Oum El Kheir Aktouf is a Professor in Computer Science at Grenoble Institute of Technology (Esisar Engineering School) and a member of the LCIS laboratory, France. She previously served as a Visiting Professor at San José State University, USA, during a sabbatical leave. Education : Master and PhD in Computer Science from Grenoble Institute of Technology Her research focuses on dependability, safety, and security of embedded and interconnected systems, including sensor-based applications and multi-agent architectures. She employs runtime testing, diagnosis, and monitoring approaches. Her work spans mobile application testing, fault diagnosis in RFID and wireless sensor networks, and security frameworks for autonomous systems. Recent publications highlight trends in Android security benchmarking , decentralized cryptography , and multi-agent resilience . She has participated in 12 funded national and international research projects and supervised courses in operating systems, real-time systems, distributed computing, and system dependability.

• Dependability
• Safety
• Security
• +۵ مورد دیگر

Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, part of the College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University, where he led the MS in Software Engineering program and developed numerous courses in software testing, web engineering, and software analysis. His research has significantly influenced both academia and industry in software testing and engineering education. His research interests span software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has pioneered techniques such as bypass testing and model-based testing, with applications embedded in tools like Selenium. His work emphasizes practical, impactful research—what he calls "science fiction"—with a clear path to real-world use by software engineers. His recent publications reflect a strong trend in cost-effective mutation testing, model-based testing strategies, educational innovations like self-paced learning models (e.g., SPARC), and security aspects of web applications. The keywords across his work include software testing, empirical studies, automation, and education, with subfields such as fault localization, test oracles, input partitioning, and scalable pedagogy. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University Faculty Member of the Year (2020) Virginia Outstanding Faculty Award (2019) George Mason Teaching Excellence Award (2013) 10-year Most Influential Paper Award, MODELS 2020 Best Paper Award, ICST 2021 Most Influential Paper, ISSRE (2019) Jeff Offutt has advised numerous students and collaborated internationally, including at Swedish universities. He has led major educational initiatives such as the NSF-funded SPARC project, aimed at improving scalability and diversity in introductory CS courses. He has also been actively involved in curriculum development, including co-authoring IEEE/ACM guidelines for software engineering programs. His leadership extends to founding and chairing major conferences like IEEE ICST and serving as Editor-in-Chief of Software Testing, Verification and Reliability . He leads research projects on smart test automation, minimal mutation, and K–5 computer science integration. His work has resulted in widely used tools including muJava, Mothra, and SpecTest. He frequently gives keynote talks on testing, education, and research methodology, and is known for his popular talk "How to Get Your Paper Rejected."

• Software Testing
• Mutation Testing
• Model-Based Testing
• +۸ مورد دیگر

Daniele Antonioli is an Assistant Professor at EURECOM, affiliated with the Software & System Security (S3) group. His research spans applied system security and privacy, focusing on wireless communication (Bluetooth, Wi-Fi), embedded and mobile systems (e.g., smartphones, cars, fitness trackers), and cyber-physical systems like industrial control systems. His research interests include Applied System Security , Privacy , Wireless Communication Security , Embedded Systems Security , Automotive Security , IoT Security , Applied Cryptography , and Threat Modeling . His work frequently targets real-world protocols and proprietary systems, uncovering critical vulnerabilities in Bluetooth (e.g., KNOB, BIAS, BLURtooth), FIDO2 (CTRAPS), and IoT ecosystems (BreakMi, E-Spoofer). Recent publications demonstrate a strong trend in automotive and IoT security , protocol-level attacks , and privacy-preserving technologies , with work published in top venues like IEEE S&P, ACM CCS, NDSS, and USENIX Security. He has contributed to the DP3T/GAEN contact tracing framework, now used in Android and iOS. Mille E Una Lode Award CLUSIT Award'22 He has advised multiple PhD and Master’s students and received grants from the German Research Foundation (DFG). He teaches courses such as Mobile System Security and a Bluetooth-focused course at EURECOM. He has also been active in the research community, serving as Associate Editor for ACM TOPS and co-chairing NDSS'26 Artifact Evaluation. He leads or contributes to research projects including the AttackDefense Framework (ADF) , ENCOPIA , and ORSHIN , focusing on threat modeling, privacy assurance, and resilient IoT systems.

• Applied System Security
• Privacy
• Wireless Communication Security
• +۱۳ مورد دیگر

Dr. AZAHARI Afiqah is a researcher at EURECOM's Digital Security department, focusing on blockchain technology, cybersecurity, and military applications. She has published extensively on decentralized systems, digital forensics, and smart supply chain solutions. Her research spans multiple domains including: Blockchain-based attendance systems Military supply chain traceability Digital forensic process modeling Smart library and inventory systems Android malware detection frameworks Recent work emphasizes blockchain integration with biometric authentication, temperature monitoring, and GPS tracking. She has contributed to developing innovative solutions for secure digital environments and knowledge management systems.

• Digital Security
• Blockchain Technology
• Cybersecurity
• +۵ مورد دیگر

Clémentine Maurice is a full-time CNRS researcher at the University of Lille's CRIStAL laboratory, specializing in computer security with a focus on microarchitectural vulnerabilities. She leads the Spirals research group and previously worked at IRISA (Rennes) and Graz University of Technology. Her research spans side-channel attacks, fault injection, and hardware-software interactions. Education: PhD in Telecommunications from Telecom ParisTech (2015), postdoc at Technicolor and Eurecom. Academic background includes reverse-engineering CPU components and analyzing JavaScript timers in browsers. Research interests emphasize exploiting hardware vulnerabilities such as cache side-channels, port contention, and power-based fingerprinting. Notable contributions include PhaseSCA, BlueScream, and Rowhammer.js attacks, with awards including the 2023 DIMVA Best Paper and Mozilla Security Hall of Fame recognition. Grants: Leads the REV project under PEPR Cybersecurity, participates in ANR-funded projects like MIAOUS and ARCHI-SEC. Service roles include program committee positions at USENIX Security, EuroS&P, and DIMVA. Publications span 200+ works with a focus on practical attacks like Drammer (mobile rowhammer) and KASLR bypasses. Active in outreach through conferences, workshops, and mentoring PhD students via the Gilles Kahn award jury.

• Computer Security
• Microarchitecture
• Side-Channel Attacks
• +۵ مورد دیگر

Jean-Francois Lalande is a Professor at CentraleSupélec , affiliated with the Inria PIRAT team . His research focuses on IT infrastructure security, Android application security, and embedded C software security, with specific interests in access control policies, intrusion detection tools, and software code analysis. Participated in PEPR DefMal (2022–2028): Defense Against Malware Coordinated CominLabs Kharon (2014–2018): Android Malware Monitoring His recent publications emphasize Android malware analysis, smart card security, and privacy-preserving protocols. Key trends include code obfuscation, information flow tracking, and empirical evaluation of security tools. He has served as co-chair for multiple workshops including the International Workshop on Information Security Methodology and Replication Studies (2019–2022) and organized the Cybersecurity Exercise for Red and Blue team Entertainment (CERBERE). Lalande advises PhD students in cybersecurity domains and collaborates on projects addressing Android malware detection, static analysis tools, and security verification.

• Cybersecurity
• Android Application Security
• Embedded Software Security
• +۶ مورد دیگر

Zaineb Chelly Dagdia Garcia is a Professor at University of Lille, France, with office S3.11, ESPRIT, Scientific City. She is a member of the Operational Research, Knowledge And Data (ORKAD) research group at the CRIStAL laboratory and the Institute for Translational Research in Inflammation (Inifinite). Dr. Garcia earned her HDR (qualification for supervising research) from the University of Paris-Saclay, France. This prestigious qualification demonstrates her expertise in leading research projects and mentoring doctoral candidates in computational intelligence. Her research spans Artificial Intelligence , Machine Learning , Evolutionary Algorithms , and Artificial Immune Systems , with particular focus on privacy preservation , scalable machine learning , and granular computation . She applies these techniques to critical domains including medical applications (particularly sepsis treatment optimization) and cybersecurity (especially malware detection and secure data processing). Analysis of her recent publications reveals a strong trajectory toward developing privacy-preserving synthetic data generation techniques, explainable AI for healthcare applications, and novel approaches to mobile security. Her work consistently bridges theoretical advances in computational intelligence with practical implementations addressing real-world challenges in sensitive domains requiring high reliability and ethical considerations. Dr. Garcia's significant scholarly contributions have been recognized through numerous prestigious awards: Marie Skłodowska Curie Individual European Fellowship (MSCA-IF) Young Researcher First Price (IEEE EHB'2013) ACM-W Award Best Reviewer Award (iCDEc 2018) Marie Sklodowska Curie Ambassador Female Scientist Role Model designation Selection for Heidelberg-Laureate-Forum (HLF'2017) Inclusion among 30 MSC talented researchers for Falling Walls Labs 2018 Her research program receives substantial funding from European Union's research and innovation programs, national grants, multi-partner projects, and bilateral research collaboration programs. As an HDR holder, Dr. Garcia supervises PhD students and postdoctoral researchers, contributing significantly to academic training in artificial intelligence and computational intelligence. Her work through the ORKAD research team at CRIStAL laboratory and Inifinite institute demonstrates a strong commitment to interdisciplinary research addressing complex societal challenges through computational approaches.

• Artificial Intelligence
• Machine Learning
• Evolutionary Algorithms
• +۷ مورد دیگر

Pierre-François Gimenez is a cybersecurity and machine learning researcher affiliated with the Laboratory Confidentiality, Integrity, Availability, Distribution . His work focuses on intrusion detection systems, malware analysis, and secure software design. Research Interests : Secure programming languages resistant to injection attacks Anomaly detection in network environments Machine learning applications for cybersecurity Malware dataset validation and bias mitigation Recent Publication Trends : His articles from 2025 demonstrate expertise in graph-based detection of advanced threats, synthetic network traffic generation, and robust malware detection frameworks. He also explores preference learning for recommendation systems in interactive configuration.

• Cybersecurity
• Machine Learning
• Network Security
• +۳ مورد دیگر