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Johnnatan MessiasView profile

Researcher

• Blockchain governance
• Decentralized finance
• Network transparency
• +1 more

Johnnatan Messias is a Research Scientist at the Max Planck Institute for Software Systems (MPI-SWS), specializing in blockchain governance, decentralized finance, and network transparency. He holds a Ph.D. in Computer Science from MPI-SWS in collaboration with Universität des Saarlandes, advised by Prof. Krishna P. Gummadi. His work focuses on improving fairness and accountability in decentralized systems through empirical analysis of blockchain transactions and governance mechanisms. Primary research areas include DeFi protocol vulnerabilities, blockchain scalability solutions (especially rollups), and transparency in transaction ordering. He develops measurement tools like Glasnost for detecting network differentiation and SatelliteLab for heterogeneous network testing. Recent work examines governance centralization in DeFi, arbitrage dynamics in layer-2 systems, and economic sustainability of token distribution mechanisms. Publications demonstrate consistent methodological innovation in analyzing blockchain data, combining network measurements, statistical modeling, and game-theoretic frameworks. Key contributions include revealing voting power concentration in DAOs, quantifying rollup performance during inscription surges, and detecting opaque transaction prioritization in Bitcoin and Ethereum. His empirical studies have exposed systemic issues like miner collusion in fee markets and arbitrage inefficiencies in AMMs. Dr. Messias has contributed to academic service as program committee member for FC, AFT, WWW, and other major conferences. He developed open-source tools including WhatsApp Monitor for tracking misinformation and public datasets for ZK-Rollup research. Current projects investigate the impact of inscriptions on EVM networks and design frameworks for decentralized insurance on blockchain infrastructures.

Todd AustinView profile

Professor

• Computer Architecture
• Hardware Security
• Secure System Design
• +4 more

Todd Austin is the S. Jack Hu Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research focuses on secure computer architecture and hardware-software co-design for security-critical systems. His primary research interests include computer architecture , hardware security , secure system design , and side-channel protection . Austin's work emphasizes practical solutions for real-world security challenges through hardware-software co-design and formal verification techniques. Recent publications (2022-2025) demonstrate a strong focus on data-oblivious execution , moving target defenses , and hardware-based security primitives . Key themes include eliminating side-channel leakage through program transformations, sequestered encryption techniques, and architectural support for vulnerability-tolerant systems. Austin maintains active research engagement through his Austin-Lab and open-source contributions, including the widely-forked bringup-bench repository for CPU and system validation. Contact: austin@umich.edu | Office: 4637 BBB, 2260 Hayward Avenue, Ann Arbor, MI 48109-2121 | Phone: 734-936-0370

• Software Reliability
• Software Security
• Symbolic Execution
• +6 more

Cristian Cadar is a Professor in the Department of Computing at Imperial College London, leading the Software Reliability Group. He holds an ERC Consolidator Grant and is an EPSRC Early-Career Fellow. His research focuses on enhancing software reliability and security through techniques like symbolic execution and dynamic analysis. Education: PhD in Computer Science (Stanford University), M.Eng. and B.S. in Computer Science and Mathematics (MIT). Research interests include software engineering, computer systems, and security, with a focus on practical tools for testing and verification. His work has led to advancements in symbolic execution, compiler testing, and dynamic software updates. Key publications span topics like KLEE, symbolic execution optimization, and compiler fuzzing. Awards include the BCS Roger Needham Award, Humboldt Research Award, and SIGOPS Hall of Fame recognition. He advises PhD students and postdocs, focusing on systems programming and compilers. His lab develops tools like KLEE and explores multi-version execution and greybox fuzzing.

• Data Privacy
• Evolutionary Computing
• Recommendation Systems
• +5 more

Dr. Jinli Cao is a full-time Associate Professor in the Department of Computer Science and Information Technology at La Trobe University. She holds a BSc from Hebei University, China, and a PhD from the University of Southern Queensland, Australia (1997). Her research focuses on evolutionary computing, data privacy, deep learning for vulnerability assessment, and decision support systems. She has published over 150 papers in top venues such as VLDB and IEEE Transactions series. Dr. Cao leads an ARC-funded project on software vulnerability risk discovery and has secured three ARC grants. She has supervised 11 PhD, 2 Master’s, and 57 Honours students, many of whom work in academia and industries like Oracle and Commonwealth Bank. Teaching contributions include developing courses in databases, data warehouses, and artificial intelligence. Research Interests: Privacy-preserving data publishing and optimization Evolutionary algorithms for dynamic data partitioning Deep learning applications in cybersecurity and healthcare Graph-based machine learning for access control and anomaly detection Decision support systems and top-k query processing Her recent articles explore cutting-edge topics like privacy-preserving spatial crowdsourcing tasks, graph neural networks for traffic prediction, and cybersecurity frameworks for vulnerability prioritization. Awards include competitive ARC grants totaling $450,000 (2023-2025). She actively serves as an Associate Editor for Health Information Science and Systems and has examined over 100 PhD theses across Australian universities. Teaching highlights: Developed 20+ courses including Database Management Systems, Data Warehousing, and Artificial Intelligence. Coordinates units like Decision Support Systems and Intermediate Programming in Java.

Mladen VeinovićView profile

Professor

• Cybersecurity
• Network Security
• Data Protection
• +7 more

Mladen Veinović is a Professor at Singidunum University, affiliated with the Faculty of Informatics and Computing. He holds a Doctorate in Systems Theory from the School of Electrical Engineering, University of Belgrade (1996), along with postgraduate and bachelor's degrees in Automatic Control and Electronics from the same institution. His research focuses on cybersecurity, network security, signal processing, and machine learning. Key contributions include work on malware C2 infrastructure, IoT security, steganography, and robust speech processing algorithms. He has authored/co-authored over 40 books and numerous peer-reviewed articles in journals like IEEE Access, Sensors, and Computers & Security. Veinović is actively involved in education technology, developing secure communication tools and problem-based learning approaches. His work spans cloud forensics, blockchain applications, and pandemic-era teaching strategies. He has been a key contributor to projects like the WIDE web development framework and cybersecurity tools for sensor networks. Professional affiliations include Singidunum University's research institute and participation in international conferences like Sinteza and TELSIKS. His expertise bridges theoretical research and practical applications in digital systems, IoT, and information security.

Ralf MöllerView profile

Professor

• Artificial Intelligence
• Humanities-Centered AI
• Causal and Probabilistic Models
• +5 more

Prof. Ralf Möller is a Professor of Artificial Intelligence in Humanities at the University of Hamburg's Faculty of Humanities, Department of Philosophy. He leads the Institute of Humanities-Centered Artificial Intelligence (CHAI) and serves as spokesperson for the 'Data Linking' research field within the Cluster of Excellence ‘Understanding Written Artefacts’ (UWA, 2019–2025). His research focuses on intellectics, causal and probabilistic-relational models, and AI applications in humanities, emphasizing sustainable data management and multimodal foundation models. He heads the Data Linking Lab and the CHAI Institute, overseeing projects like the TAMAR initiative for manuscript research. His work bridges technical AI advancements with humanities needs, addressing challenges in data curation, federated information systems, and ethical AI integration. He contributes to interdisciplinary collaborations, including ethics committees and cultural heritage preservation initiatives. Key research themes include lifted inference in probabilistic graphical models, temporal data prediction, and synergistic OCR-LLM systems for damaged documents. His projects emphasize scalability, sustainability, and human-centered design principles. Supervising doctoral candidates in AI and humanities intersections, he advocates for AI systems grounded in cultural and ethical considerations. Labs/Teams: CHAI Institute, Data Linking Lab. Current Projects: UWA Cluster (2019–2025), Data Linking Infrastructure development, Humanities-Centered AI applications. Grants include leadership roles in institutional and collaborative research funding.

Martina LindorferView profile

Associate Professor

• Systems Security
• Privacy
• Mobile App Analysis
• +5 more

Martina Lindorfer is an Associate Professor in the Security and Privacy Research Unit at TU Wien, leading the Secure Systems Lab (SecLab). She is also a key researcher at SBA Research. Her expertise spans systems security, privacy, mobile app analysis, and malware research. Prior to her current role, she was a Postdoc at UC Santa Barbara under Christopher Kruegel and Giovanni Vigna. Lindorfer holds a PhD from TU Wien (2016) with honors, and has received awards including the ERCIM Cor Baayen Award (2018) and the ACM Early Career Award (2020). She advises students on topics like IoT security and privacy, and contributes to academic service roles like Program Co-Chair for ACSAC and WOOT. Education: PhD in Computer Science (2016, TU Wien), Master's in Software Engineering (TU Wien), Bachelor's in Computer and Media Security (Hagenberg). Research focuses on mobile and IoT security, privacy protections, and APT analysis. Her team has published impactful work on topics like Android security models, iOS permission systems, and smart TV vulnerabilities. Awards highlight her contributions to cybersecurity research, including recognition for work on HbbTV privacy (Best Dutch Cyber Security Paper, 2024) and early-career excellence. Lindorfer also engages in outreach, mentoring, and policy discussions around digital humanism and academic cloudification risks. Labs/Teams: Heads the SecLab at TU Wien, collaborates with SBA Research, and leads projects like the TU Wien Cybersecurity Center (CySec). Active in organizing conferences and mentoring students through initiatives like the Austria Cyber Security Challenge.

Christophe HauserView profile

Assistant Professor

• Software Security
• Binary Program Analysis
• Reverse Engineering
• +6 more

Christophe Hauser is an Assistant Professor at Dartmouth College and a member of the Institute for Security, Technology and Society (ISTS). His research focuses on software security, binary program analysis, reverse engineering, and vulnerability discovery across software and hardware systems. He integrates formal methods, machine learning, and program analysis to enhance cybersecurity defenses. Education: Joint PhD from CentraleSupélec (France) and Queensland University of Technology (Australia). Prior roles include Research Lead at USC Information Sciences Institute (USC-ISI) where he founded the Binary Analysis and Systems Security (BASS) group, and postdoctoral researcher at UC Santa Barbara’s Seclab. Research Interests: Binary code and firmware analysis, intrusion detection, usable security, privacy-preserving systems. Notable projects include BinPool (vulnerability dataset), BinHunter (vulnerability localization), and Harm-DoS (DoS mitigation). His work emphasizes practical applications such as automated fuzzing, decompilation analysis, and neuro-symbolic code search systems. He has contributed to open-source tools like angr and developed frameworks for firmware integrity validation (BootKeeper).

Simon WaldmanView profile

Assistant Professor

• Renewable Energy
• Physical Oceanography
• Tidal and Wave Energy
• +4 more

Simon Waldman is an Assistant Professor at Heriot-Watt University’s School of Energy, Geoscience, Infrastructure and Society, affiliated with the Institute for Life and Earth Sciences. He holds a PhD from Heriot-Watt’s Orkney campus, focusing on tidal energy modeling, and has worked at the University of Edinburgh, Marine Scotland Science, and the Pacific Northwest National Laboratory. He is Programme Director for the MSc in Renewable and Sustainable Energy Transition, and a Fellow of the Software Sustainability Institute. His research integrates renewable energy systems with physical oceanography, emphasizing computational modeling to assess energy potential and environmental impacts. He also advocates for software best practices in scientific research, contributing to reproducibility and open science. Key areas include tidal and wave energy resource characterization, policy implications of energy infrastructure, and climate change effects on marine ecosystems. Notable achievements include developing hydrodynamic models for the Scottish Shelf and North Sea wind farm planning, and receiving the 2016 ‘Best presentation in category’ award for tidal energy research in Japan. He actively engages in public outreach via events like ‘Skype a Scientist’ and contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG7) and climate action (SDG13). Education: PhD in Tidal Energy Modeling from Heriot-Watt University, Orkney. Grants & Activities: Involved in datasets like North Sea 2050 wind turbine locations and collaborates internationally on tidal energy projects. Labs/Teams: Works within Heriot-Watt’s Institute for Life and Earth Sciences, contributing to interdisciplinary energy transition initiatives.

• Computer Security
• Mobile Security
• Network Security
• +6 more

Georg Merzdovnik is a Lecturer at Vienna University of Technology (TU Wien) with a focus on computer security and privacy . His work spans binary rewriting, web privacy, IoT security, and Android application analysis, reflected in publications in top venues like ACM Computing Surveys and IEEE Euro S&P. He actively supervises student research projects in security-related domains. Primary Affiliation: Vienna University of Technology (TU Wien) Research Interests include: Binary rewriting and obfuscation techniques Web privacy mechanisms post-GDPR IoT device security in IPv6 networks Mobile application threat analysis Malware detection in Windows shellcodes Evaluation of tracker-blocking tools Thesis Supervisions (2012–2024) cover topics like IoT testbeds, Android intent firewalls, and secure messaging services.

• Cybersecurity
• Network Security
• IT Security Testing
• +3 more

Christian Schanes is a PostDoc Researcher at TU Wien's Department of Business Informatics. He holds a Dipl.-Ing. degree and a Dr.techn. from TU Wien, with a PhD titled 'Scope and depth efficient testing approach and framework for enhancing the detection of IT security bugs' (2013). His research focuses on cybersecurity, network security, automated security testing, and secure communication protocols. He teaches the course 'Introduction to Security' (2024W) and has supervised multiple graduate theses, including works on cybersecurity awareness, automated testing frameworks, and VoIP security. His research interests span IT security testing, data privacy, and vulnerability analysis in systems like VoIP and mobile payment frameworks. He has pioneered methodologies for automated security testing using machine learning and system behavior modeling. His work often addresses real-world threats, such as TLS vulnerabilities and honeynet-based attack analysis. Schanes has co-authored over 30 peer-reviewed publications, emphasizing practical solutions to cybersecurity challenges. Notable contributions include studies on mobile kernel subversion via TrustZone rootkits and large-scale VoIP threat analysis using honeynets. His research bridges theoretical frameworks with applied security solutions, impacting both academic and industry practices.

Davide BalzarottiView profile

Professor

• Reverse Engineering
• Forensic Memory Analysis
• Advanced Malware Analysis
• +3 more

Davide Balzarotti is a Professor and Head of the Digital Security Department at EURECOM. His expertise spans reverse engineering, forensic memory analysis, advanced malware analysis, and web security. He holds a PhD in Computer Engineering from the Polytechnic Institute of Milan (2006), followed by a postdoctoral fellowship at the University of California, Santa Barbara (2006–2008), and an HDR (Habilitation à Diriger des Recherches) from EURECOM in 2015. His research focuses on understanding malware behavior, improving forensic techniques, and enhancing web security through machine learning and static analysis. Notable contributions include frameworks like ModSec-Learn for boosting intrusion detection and PhishEye for monitoring phishing kits. He has received multiple awards, including the Best Paper Award at SAC 2017 and the ACM Europe Student Best Paper Award at CCS 2016. His work bridges academic research and practical cybersecurity challenges, addressing topics such as adversarial attacks, embedded system security, and evasion techniques in malware. His projects include evaluations of voting machine security (Project Everest) and collaborations to improve vulnerability detection in software. Education: PhD in Computer Engineering, Polytechnic Institute of Milan (2006) Postdoctoral Research at UCSB (2006–2008) HDR, EURECOM (2015) Awards: Best Paper Award (2017) ACM Europe Student Best Paper Award (2016) Best Student Paper Award (2013) Distinguished Paper Award (2011) Key Research Themes: Memory forensics Malware analysis Fuzzing and vulnerability discovery Web application security

Paolo ParonView profile

Senior Lecturer

• Remote Sensing
• Geomorphology
• Hydrology
• +3 more

Paolo Paron is a Senior Lecturer in Earth Science and Remote Sensing at IHE Delft, specializing in geomorphological mapping, hydro-meteorological hazards, and low-cost remote sensing technologies. He leads Mapping and Remote Sensing activities within the River Basin Development chair group. His research focuses on open-source software applications, unmanned aerial systems (UAS), and structure-from-motion (SfM) techniques for river morphology and ecosystem service mapping. He has extensive field experience in developing countries including Kenya, Mozambique, and Ethiopia. Paron holds a MSc in Geology from the University of Roma3 (2000) and a PhD in Fluvial Geomorphology from the University of Chieti (2005). He edited two UN FAO atlases for Somalia and an Afghan digital atlas for NGOs, and chairs sessions at international conferences like EGU. He serves as Associate Editor for the Journal of Maps and Topic Editor for the ISPRS International Journal of Geo-Information . Key research areas include free/low-cost remote sensing data applications, sediment dynamics, and sustainable development in arid regions. His work involves 40+ countries across Africa and Asia, emphasizing humanitarian preparedness and environmental monitoring. Paron collaborates with global institutions like IAHR on drone technology and contributes to projects such as WiODER. His expertise bridges geoscience with practical field applications, addressing water resource challenges and disaster risk reduction in data-scarce regions.

• Cybersecurity
• Database Forensics
• Machine Learning Applications in Security
• +4 more

Peter Frühwirt is an External Lecturer in the Department of Information Systems Engineering at Vienna University of Technology (E194). His research focuses on cybersecurity, database forensics, and usable security, with a particular emphasis on tamper-proof systems, QR code vulnerabilities, and forensic-aware database solutions. Education : Dipl.-Ing. Dr.techn., BSc BSc Research Interests : Cybersecurity, Database Forensics, Machine Learning Applications in Security, QR Code Security, Web Application Security, Traffic Classification His recent publications analyze forensic-aware database protocols, QR code threats, and machine learning applications for attacker profiling. He teaches courses including Advanced Software Engineering, Software Engineering Project, and Software Quality Assurance.

Yunsi FeiView profile

Professor

• Hardware-oriented security
• Computer Architecture
• Embedded Systems
• +7 more

Yunsi Fei is a Professor in the Electrical and Computer Engineering Department at Northeastern University, serving concurrently as Associate Dean of Faculty Affairs. She leads the Northeastern site of the NSF IUCRC Center for Hardware and Embedded System Security and Trust (CHEST). Her research focuses on hardware-oriented security, computer architecture, embedded systems, and IoT security, with significant contributions to mitigating side-channel and fault attacks on neural networks and hardware systems. Fei holds a PhD in Electrical Engineering from Princeton University (2004), and bachelor’s and master’s degrees in Electronic Engineering from Tsinghua University. She joined Northeastern in 2011 after faculty roles at the University of Connecticut. Her research interests span secure computer architecture, energy-efficient embedded systems, and underwater sensor networks. Notable projects include RINGS (a NSF-funded IoT resilience initiative) and secure RISC-V processor design. She has received the NSF CAREER Award and multiple best paper awards at top conferences. Fei’s work integrates hardware-software co-design to address vulnerabilities in AI accelerators and cryptographic systems. She leads the Energy-Efficient and Secure Systems (ENESS) Lab and collaborates with industry and academia through CHEST. Recent grants include $1.5M for cybersecurity in additive manufacturing and $1M for spectrum-agile IoT systems. Her awards include a 2023 Distinguished Paper Award (AsiaCCS) and 2022 Best Paper (Great Lake VLSI). She mentors students like Ruyi Ding, who joined LSU as faculty in 2025. Fei also chairs sessions on hardware security and is an affiliated faculty member with Northeastern’s Institute of Information Assurance.