Find Academic Supervisors

Nguyen Phong HoangView profile

Assistant Professor

• Network Security
• Online Privacy
• Internet Measurement
• +3 more

Nguyen Phong Hoang is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Systopia Lab and Security and Privacy Group. His research focuses on network security, online privacy, and Internet measurement, with particular emphasis on improving networked system security and reinforcing privacy through large-scale data collection. He has pioneered projects like GFWeb and GFWatch to measure China’s Great Firewall and other censorship mechanisms. Prior to UBC, he was a Postdoctoral Scholar at the University of Chicago under Prof. Nick Feamster, and completed his PhD at Stony Brook University under Prof. Michalis Polychronakis. His work has been supported by the OTF’s Information Controls Fellowship, enabling collaborations with groups like the Citizen Lab (U of Toronto) and UMass Amherst. He currently teaches courses on computer networking and network security at UBC. Research interests include DNS censorship detection, domain name encryption protocols (e.g., DNS-over-HTTPS), and methods to evade Internet censorship. His publications analyze global network interference, connection tampering, and the impact of encryption protocols on censorship resistance. He has developed tools like GFWeb’s interactive dashboard for longitudinal censorship monitoring and contributed to improving I2P (Invisible Internet Project) resilience against surveillance. Phong has also served on program committees for major conferences including IEEE S&P, USENIX Security, and IMC. Phong’s academic journey includes time at Kyoto University and JAIST in Japan, where he explored location privacy in dating apps and network anonymity. His interdisciplinary approach bridges technical cybersecurity solutions with policy implications, contributing to both academic discourse and public understanding of Internet freedom challenges.

A. ContinellaView profile

Associate Professor

• Systems Security
• Malware Detection
• Privacy Disclosures
• +5 more

A. Continella is an Associate Professor in the Semantics, Cybersecurity, and Services group at the University of Twente, affiliated with the International Secure Systems Lab (iSecLab). Previously, they served as a Postdoctoral Researcher at UC Santa Barbara’s Computer Science Department and earned a Ph.D. cum laude from Politecnico di Milano. Their research focuses on systems security, particularly analyzing software for malware detection, privacy leaks, and vulnerability identification. They emphasize open science and actively participate in Capture The Flag (CTF) competitions, including DEFCON Finals with Shellphish. Education: Ph.D. cum laude in Computer Science and Engineering, Politecnico di Milano, Italy Research exchanges at UC Santa Barbara and University of Sydney’s School of Computer Science Research Interests: Security of daily-use software Ransomware defense mechanisms Obfuscated privacy leaks in Android apps Program analysis for firmware vulnerabilities Awards: Ph.D. cum laude distinction Labs & Collaborations: International Secure Systems Lab (iSecLab) SecLab at UC Santa Barbara

Daniel WichsView profile

Associate Professor

• Cryptography
• Computer Security
• Algorithms
• +5 more

Daniel Wichs is an Associate Professor at the Khoury College of Computer Science , Northeastern University , and Senior Scientist at NTT Research . His work focuses on Cryptography , particularly in computing on encrypted data, lattice-based cryptography, and information-theoretic security. Education: PhD in Computer Science (NYU, 2011), BS/MS in Mathematics and Computer Science (Stanford, 2005). His research spans Cryptography , with emphasis on theoretical foundations , program obfuscation , and secure computation . Recent work explores computationally bounded error correction , succinct arguments , and RAM-based cryptographic systems . He has received the Alfred P. Sloan Foundation Fellowship (2018), NSF CAREER Award (2018), and IBM Josef Raviv Fellowship (2011-2013). His students include Manu Kondapaneni , LaKyah Tyner (co-advised), and Ethan Mook , many of whom now hold academic positions. He leads the Cryptography and Privacy Group at Northeastern and has organized major conferences like the Simons Summer Program in Cryptography (2025). His teaching includes advanced courses on Foundations of Cryptography and Theory of Computation .

• Cloud Computing
• Container Orchestration
• Cloud-Native Applications
• +4 more

Nane Kratzke is a Professor at Lübeck University of Applied Sciences, specializing in cloud computing and cloud-native applications. His research addresses practical challenges in container orchestration, cloud security, and vendor lock-in for small and medium enterprises. He holds a Diplom in Computer Science and a Doctorate in Natural Sciences, though specific institutions are not documented in available sources. Research interests include cloud-native architecture design, Kubernetes orchestration, moving target defenses for cloud security, and cost modeling of cloud services. His work bridges academic research and industry needs, particularly for SMEs seeking cloud portability through multi-cloud strategies and runtime transferability. Analysis of recent publications (2022-2024) reveals a strategic shift toward AI-driven cloud management techniques like prompt engineering, building on foundational contributions in cloud observability, security mechanisms, and transferability frameworks established between 2016-2021. Key recurring themes include mitigating vendor lock-in and enabling seamless application migration across cloud environments. No scientific awards are documented in the provided information sources. Details regarding graduate student advising, research grants, and laboratory facilities are not specified in current datasets, though his publications on programming assessment tools indicate engagement with computer science education.

Faysal ShezanView profile

Assistant Professor

• Security and Privacy
• Cyber-Physical Systems
• Medical Healthcare Security
• +7 more

Faysal Shezan is an Assistant Professor in the Computer Science and Engineering department at the University of Texas at Arlington. His research focuses on security and privacy intersections with cyber-physical systems, medical healthcare, software engineering, and machine learning. He received his PhD from the University of Virginia (2023) and a BS from Bangladesh University of Engineering and Technology (2016). His work has been published in top-tier venues like NDSS, WWW, PoPETs, and SOUPS. Research Interests : Security & Privacy, Cyber-Physical Systems, Medical Healthcare, GDPR Compliance, LLM Security Lab : Cyber Guard Research Lab Recent Publications span vulnerability repair automation (USENIX 2025), IoT privacy analysis (NDSS 2023), GDPR compliance (WWW 2020), and VR security (SSPX 2022). His work combines program analysis, machine learning, and NLP for security solutions. Awards : CPS Rising Stars (2022), UT System Rising Stars (2023), Microsoft Azure credits ($20k, 2023) Grants : REU Program Grants (2023-24), Departmental REU Support He advises students with publications at IEEE S&P (2024) on LLM security topics and leads the Cyber Guard Research Lab exploring software security, IoT vulnerabilities, and LLM privacy.

Michael EichbergView profile

Professor

• Software Engineering
• Static Analysis
• Software Development Tools
• +3 more

Michael Eichberg is a Professor at Technische Universität Darmstadt, Germany, where his work centers on software engineering, static analysis, programming languages, and secure software development tools. He is the principal architect of the OPAL framework for Java bytecode analysis and has an extensive publication record spanning PLDI, ICSE, ESEC/FSE, ISSTA, ASE, FSE, SOAP, and other premier venues. Research Interests: Static program analysis and its scalability to real-world code bases Software security, particularly cryptographic API misuse and Android app repackaging detection Concurrent and parallel programming models, including deterministic concurrency in Scala Software architecture conformance, drift and erosion detection, and rule reuse Development of open extensible tools and frameworks (OPAL, LectureDoc, QScope, Sextant, XIRC, IRC) Publication Trends: His recent work (2015-2022) demonstrates a strong focus on empirical evaluation of static analysis techniques, modular composition of analyses, and security-related program understanding. Key themes include unsoundness in call graph construction, purity and immutability analyses, parallelization of static analyses, and large-scale studies of cryptographic API misuse. Tools & Frameworks: OPAL – A flexible Java bytecode analysis and manipulation framework (core developer until 2019) LectureDoc 2 – Web-based lecture material authoring and presentation system QScope – Open extensible metrics framework for modern software projects Sextant – Eclipse-integrated software exploration tool XIRC/IRC – Frameworks for enforcing system-wide properties and architectural constraints

• Hardware Security
• Machine Learning Applications
• VLSI Design
• +3 more

Sara Tehranipoor serves as an Assistant Professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University's Benjamin M. Statler College of Engineering and Mineral Resources. Her research program spans hardware security foundations to applied machine learning solutions, with expertise in hardware security primitives, side-channel analysis, and hardware obfuscation techniques. Her academic background includes: Ph.D. from University of Connecticut (2017) M.S. from Shahid Beheshti University of Tehran, Iran (2013) B.S. from Babol Noshirvani University of Technology, Iran (2011) Dr. Tehranipoor's scholarly work addresses critical vulnerabilities in integrated circuit security through innovative approaches combining traditional hardware security methods with machine learning frameworks. Her research demonstrates particular strength in developing countermeasures against physical attacks and creating robust hardware trust anchors for IoT devices. She has received the following recognition: Best Technical Paper Award at VLSID 2017 and Embedded Systems 2017 As an educator, she has mentored over 40 graduate and undergraduate students in research theses and senior design projects. Her professional service includes editorial roles for IEEE Consumer Electronics Magazine and Discover Internet of Things Journal, along with active committee participation in IEEE/ACM conferences (ISQED, GLSVLSI, DAC) and leadership in Women in Engineering initiatives including the Silicon Valley Cybersecurity Conference WMiCS session.

Seetal PotluriView profile

Assistant Professor

• Trustworthy Machine Learning
• Hardware Security
• FPGA Virtualization
• +2 more

Seetal Potluri is Assistant Professor in the Department of Electrical & Computer Engineering at the University at Albany, SUNY's College of Nanotechnology, Science, and Engineering. He holds a Ph.D. in Electrical Engineering from IIT Madras and researches trustworthy ML systems, FPGA security, and hardware reverse engineering. Research addresses security challenges in hardware-accelerated AI systems, focusing on: 1) Model extraction vulnerabilities in neural network hardware; 2) Secure FPGA virtualization for cloud environments; 3) Side-channel attacks on cryptographic hardware; 4) Explainable ML for hardware security validation. Work bridges machine learning theory with hardware implementation security. Publications demonstrate consistent focus on hardware-level attack vectors (scan-chain exploitation, cache attacks) and defensive strategies (obfuscation, formal verification). Recent work increasingly targets cloud FPGA security and post-quantum cryptography implementations. Research contributions have been recognized with best paper awards at leading hardware security venues. Awards & Honors: Best Paper Recognition Award, IEEE HOST 2022 Runner-up, IEEE TTTC Doctoral Thesis Contest 2015 (Asia) Professional service includes technical program committees for DAC and ICCAD conferences. Teaching and research activities are based in CNSE Downtown 305E, with contact via spotluri@albany.edu or 518-956-8248.

Guowei YangView profile

Senior Lecturer

• Software Engineering
• Machine Learning
• Programming Languages
• +1 more

Dr. Guowei Yang is a Senior Lecturer at the School of Electrical Engineering and Computer Science , The University of Queensland, Australia. He transitioned to this role in 2021 after serving as a tenured Associate Professor at Texas State University's Department of Computer Science. His research focuses on the intersection of Software Engineering Machine Learning Programming Languages Cybersecurity with an emphasis on system reliability and security. His recent publications (2022-2025) analyze: Android API compatibility challenges Symbolic execution optimizations Fuzzing techniques for JVM security Moving target defense strategies Automated patch generation Constraint classification in code analysis He leads a research group seeking students with backgrounds in software engineering, formal methods, and AI. Current funding includes a 2023-2026 Oracle Corporation grant for DevSecOps analysis. Dr. Yang supervises multiple PhD and Master's projects, often as principal advisor, focusing on topics like deep learning testing, IoT analysis, and DevSecOps integration.

Amin RezaeiView profile

Assistant Professor

• Computer Security
• Machine Learning
• Computer Architecture
• +3 more

Amin Rezaei is an Assistant Professor in the Department of Computer Engineering and Computer Science at California State University, Long Beach (CSULB). He directs the Computer Architecture, Reliability, and Security Laboratory (CARS-Lab) and serves as the undergraduate advisor for Computer Engineering. His expertise spans computer security, machine learning, and computer architecture, with a focus on hardware security and protecting hardware intellectual property. Rezaei holds a Ph.D. in Computer Engineering from Northwestern University. He is a senior member of IEEE and a lifetime member of ACM and AAAI. His research has been funded by NSF grants totaling $500,000, and he has published over 50 peer-reviewed articles in top venues like DAC, ICCAD, and DATE. He has also served on technical program committees for major conferences such as IPDPS and GLSVLSI. His research interests include hardware security, machine learning applications in secure systems, and novel logic locking techniques. Key projects include developing CycPUF (a cyclic physical unclonable function) and frameworks for detecting hardware Trojans using multimodal deep learning. His lab emphasizes democratizing research by publicly sharing source code. Education: Ph.D. in Computer Engineering, Northwestern University Awarded Academic Excellence Award, University of Louisiana at Lafayette Awards: Walter P. Murphy Fellowship, Northwestern University Royal E. Cabell Fellowship, Northwestern University Grants: NSF CISE-MSI and CRII programs. Rezaei’s advising focuses on undergraduate Computer Engineering students, with Spring 2025 hours on Zoom. His lab’s current research includes projects on hardware Trojan prediction, ML-based security evaluations, and dynamic logic locking.

Manuel MaarekView profile

Associate Professor

• Cybersecurity
• Computer Security
• Secure Programming
• +6 more

Manuel Maarek is an Associate Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University, specializing in Computer Science. His research focuses on cybersecurity, secure programming, and educational technologies, particularly leveraging serious games and collaborative methodologies for enhancing security awareness. His work integrates formal methods with practical applications, addressing topics like Bitcoin transaction analysis, developer-centric security training, and blockchain privacy. He has co-authored over 29 peer-reviewed publications and received awards including the 2018 Teaching Excellence Award and the 2022 EICC Best Paper Award. Key Research Themes: Cybersecurity Education, Secure Programming Practices, Cryptocurrency Analysis, Game-Based Learning Collaborations: Active in international collaborations, particularly in cybersecurity co-design and blockchain forensics Maarek’s recent projects include the 'Serious Slow Game Jam' methodology for cybersecurity education and investigations into large language models for student feedback. He actively contributes to improving software engineering education through integrated learning platforms like Canvas and GitLab.

Niclas AndrénView profile

Senior Lecturer

• Corporate Finance
• Risk Management
• Macroeconomics
• +5 more

Niclas Andrén is a Senior Lecturer and Head of Department in the Department of Business Administration at Lund University. He directs the master program in Accounting and Finance and teaches courses in corporate finance, credit risk assessment, corporate valuation, and corporate restructurings. His research focuses on corporate financial constraints, risk management during financial distress, and the interplay between cash flow, investment decisions, and macroeconomic factors. Andrén's work contributes to UN Sustainable Development Goals, particularly through his exploration of corporate governance and financial strategies that enhance firm resilience. He has presented research at international conferences, including the Financial Management Association European Conference (2018) and the Financial Management Association International (2018). His research articles emphasize trends in corporate hedging behaviors under distress, the evolving role of cash flow proxies in investment analysis, and the implications of credit ratings for financial constraints. He has also explored how firms navigate macroeconomic risks and exchange rate uncertainties, reflecting his interdisciplinary approach to finance and economics. No scientific awards explicitly mentioned. In advising, he co-supervised doctoral theses for H. Jankensgård (2018) and Anamaria Cociorva (2018). His project, ' Essays on credit ratings ', examines financial constraints through the lens of credit rating mechanisms. Collaborations span international territories, though specific details are obfuscated. Andrén’s research lab/teams are not explicitly detailed in the provided texts.

Alex BiryukovView profile

Professor

• Applied Cryptography
• Cryptanalysis
• Authenticated Encryption
• +4 more

Alex Biryukov is a full professor in Cryptography and Information Security at the University of Luxembourg, affiliated with the Computer Science and Communications Research Unit (CSC) and the Interdisciplinary Centre for Security, Reliability and Trust (SnT). Previously, he served as an associate professor and visiting professor at K.U.Leuven, contributing to European standards (NESSIE) and ECRYPT consortia. His expertise spans applied cryptography, cryptanalysis, lightweight cryptography for IoT, cryptocurrency security, and privacy technologies like Tor and blockchain. Biryukov has held roles as program chair for FSE'07, SAC'10, and INDOCRYPT'15, and is a program committee member for top conferences including CRYPTO and CCS. He leads the FNR CORE project ACRYPT on lightweight cryptography for IoT and contributes to the COST Action IC1403 on cryptanalysis of ubiquitous systems. His teaching focuses on symmetric cryptography, network security, and real-world applications. Biryukov earned his M.Sc. and Ph.D. from the Technion and completed postdoctoral research at the Weizmann Institute under Adi Shamir. Research interests include cryptanalysis of block ciphers (e.g., AES, SIMON, SPECK), cryptocurrency protocols, and privacy-enhancing technologies. He has pioneered attacks on AES variants and contributed to lightweight algorithms like SPARX and Argon2. Biryukov's work bridges theoretical cryptography with practical implementations, addressing security in embedded systems and blockchain.

Sumit SarkarView profile

Professor

• Personalization and Recommendation Systems
• Crowdsourcing
• Sharing Economy
• +6 more

Sumit Sarkar is the Charles and Nancy Davidson Chair Professor of Information Systems and Director of PhD Programs at the Jindal School of Management, University of Texas at Dallas. He also serves as the Academic Director of the International Center for Decision and Risk Analysis. His research focuses on personalization systems, crowdsourcing, data privacy, and software project management. He holds a PhD from the University of Rochester, an MBA from the Indian Institute of Management Calcutta, and a BTech from the Indian Institute of Technology New Delhi. Professor Sarkar’s research interests span multiple domains including recommendation systems, knowledge management, and the sharing economy. His work emphasizes practical applications such as privacy-preserving data sharing, optimal contest design for crowdsourcing platforms, and strategic pricing in digital markets. Notable contributions include frameworks for hiding sensitive association rules and methodologies for evaluating online review credibility. Education: PhD, University of Rochester, 1991 MBA, Indian Institute of Management Calcutta, 1982 BTech, Indian Institute of Technology New Delhi, 1979 His awards include the AIS Fellowship (2022), INFORMS President’s Service Award (2021), and the Davidson Chair appointment (2011–present). He has held leadership roles in professional organizations such as the Workshop on Information Technology and Systems and served on editorial boards of journals like MIS Quarterly and Management Science . Professor Sarkar’s work bridges theory and practice, addressing challenges in information systems through interdisciplinary approaches. His current projects explore AI-driven counterfactual explanations, competitive dynamics in search advertising, and the ethical implications of recommendation systems.

• Bayesian Statistics
• Machine Learning
• Data Clustering
• +3 more

Jan Greve is a Researcher at the Institute for Statistics and Mathematics at Wirtschaftsuniversität Wien (Vienna University of Economics and Business). His research focuses on Bayesian statistical methods, including cluster analysis, mixture models, and metadata anonymization. He has contributed to both theoretical advancements and practical software tools in computational statistics. Greve's recent work includes developing novel approaches for partition structures in Bayesian nonparametrics and creating anonymization techniques for text corpora. He has authored/co-authored peer-reviewed articles and preprints, alongside software contributions like the 'fipp' package for Bayesian mixture models. He has actively participated in academic activities such as presenting on topics like 'Mixtures of finite mixtures and the telescoping sampler' at international conferences. His research bridges theoretical statistics with applied data science challenges.