Find Academic Supervisors

Vasileios KemerlisView profile

Professor

• Operating Systems Security
• Software Security
• Hardware-assisted Protection
• +3 more

Vasileios Kemerlis is a Professor of Computer Science at Brown University and Director of the Secure Systems Lab (SSL). His research focuses on OS, systems, and software security, with recent work on kernel hardening techniques using hardware features like ARM's memory tagging and pointer authentication. Research interests include: Operating systems protection against memory-safety vulnerabilities Software supply chain security defenses Hardware-assisted isolation mechanisms eBPF subsystem security Publications demonstrate consistent focus on practical kernel protection solutions, evolving from virtualization-based approaches to hardware-assisted mitigations. Recent works leverage ARM CPU features for efficient kernel isolation against heap-based attacks. Awards include: Distinguished Paper Award at ACM ASIACCS 2023 Distinguished Reviewer Award at ACM CCS 2024 Directs the Secure Systems Lab with PhD students working on kernel protection, speculative execution attacks, and software hardening. Lab regularly presents at top security conferences including IEEE S&P, USENIX Security, and ACM CCS.

• Biometric Security
• Cybersecurity
• Internet of Things (IoT)
• +3 more

Song Wang is a Senior Lecturer in the Department of Engineering at La Trobe University, Melbourne, Australia. She holds a B.Eng. from Xi'an Jiaotong University and a Ph.D. in Control Theory from the University of Melbourne. Her research focuses on biometric security, IoT security, and privacy-preserving authentication systems, with a particular emphasis on applying machine learning and deep learning to solve challenges in healthcare, cybersecurity, and multimedia security. Dr. Wang's academic journey includes roles as a design engineer at NEC Australia (2000–2004) and as a Lecturer (2005–2008) before becoming a Senior Lecturer at La Trobe University (2009–present). Her work has explored cancellable biometrics, secure IoT authentication, and model inversion attacks in AI systems. She has collaborated extensively on projects involving medical imaging (e.g., Alzheimer’s disease prediction via structural MRI) and privacy-preserving frameworks for EEG and fingerprint authentication. Her recent publications highlight advancements in graph convolutional networks for driver drowsiness detection, homomorphic encryption for biometric data, and lightweight authentication systems for resource-constrained IoT devices. These contributions underscore her expertise in bridging theoretical research with practical applications in cybersecurity and healthcare. No scientific awards are explicitly mentioned in the provided materials. Her research has been supported by collaborations with institutions like the University of Melbourne and industry partners, though specific grants are not detailed.

MUHARREM ERGUNView profile

Professor

• Postharvest Physiology
• Horticultural Science
• Plant Physiology
• +5 more

Prof. MUHARREM ERGUN is a Professor in the Department of Horticultural Sciences at Bingöl Üniversitesi, Turkey. He previously held academic positions at Kahramanmaraş Sütçü İmam Üniversitesi and has been part of the faculty at Bingöl since 2010. His academic journey includes a PhD from the University of Florida, USA (2003), with prior degrees from Ege Üniversitesi and Orta Doğu Teknik Üniversitesi. His research focuses on postharvest physiology, plant quality preservation, and horticultural innovations. Notable areas include ethylene inhibition techniques using 1-MCP, walnut genotype analysis, and functional food studies. He has authored over 35 international journal articles and contributed chapters to books on topics like fresh-cut produce technology and sustainable agriculture. His work frequently addresses challenges in vegetable and fruit storage, quality enhancement, and genetic diversity. Ergun has supervised 8 PhD/Master’s theses, including studies on walnut selection, carrot preservation, and cucumber quality. He has led or participated in research projects such as the 'Integrated Project to Develop Walnut Cultivation in Turkey' (TÜBİTAK, 2008–2012). His international collaborations include studies at the University of Nebraska and BOKU Wien. Awards include a YOK Fellowship (2013) and TÜBİTAK-funded research (2008). He has published 10+ books/monographs, including contributions to seminal texts like Taze Kesilmiş Ürün Teknolojisi and Genel Sebzecilik . His current research interests span innovative horticultural practices, phytochemical analysis, and sustainable food systems.

Yuying LiView profile

Professor

• Computational Optimization
• Data Science
• Computational Finance
• +3 more

Yuying Li is a Professor at the University of Waterloo's Cheriton School of Computer Science. Research focuses on computational optimization algorithms for finance, including neural network approaches for leverage-constrained portfolios, benchmark outperformance strategies, and inflation-regime asset allocation. Holds a BSc from Sichuan University (1982), MMath (1985) and PhD (1988) from Waterloo. Her work bridges continuous optimization, machine learning, and financial engineering. Recent publications develop neural alternatives to dynamic programming for portfolio management, with applications to ETF leverage, decumulation strategies, and high-inflation environments. Methodological innovations address computational scalability and regime-specific modeling.

• 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

David MercierView profile

Professor

• Information Fusion
• Belief Functions
• Uncertainty Management
• +3 more

David Mercier is a Professor at the University of Artois, France, affiliated with the LGI2A laboratory and the IUT de Béthune's Department of Networks and Telecommunications. He holds a HDR (Habilitation à Diriger des Recherches) from 2015 and a PhD from the University of Technology of Compiègne (UTC), France (2006). His research focuses on information fusion, belief functions, and uncertainty management, with applications in electrical engineering, transportation systems, and machine learning. Education DEA (M.S. Equivalent) in Artificial Intelligence, University Paul Sabatier, Toulouse (2003) PhD in Information Fusion for Postal Address Recognition, UTC (2006) HDR (Research Habilitation), University of Artois (2015) Research & Awards Notable contributions include work on contextual belief function corrections, vehicular network information fusion, and multi-target tracking. He received a co-best student paper award at BELIEF 2016. His research spans electrical machines diagnosis, stochastic simulations, and deep learning integration with Dempster-Shafer theory. Students & Involvement Supervised PhD theses include studies on evidential deep learning and motor fault diagnosis. Active in the Belief Functions and Applications Society (board member since 2010). Co-edited special issues in International Journal of Approximate Reasoning and authored book chapters on belief function applications. Labs & Teams Primary affiliation with LGI2A laboratory, collaborating with institutions like LSEE and industrial partners such as Solystic and SNCF. Research integrates theoretical advances with practical applications in smart mobility and fault detection.

Xinyu XingView profile

Associate Professor

• Operating Systems Security
• Artificial Intelligence Security
• Cybersecurity
• +3 more

Xinyu Xing is an Associate Professor in the Department of Computer Science at Northwestern University and co-founder of Sec3. His research focuses on operating systems security, AI security, and kernel exploitation. He earned his Ph.D. from Georgia Tech under Dr. Wenke Lee and Dr. Nick Feamster. His team actively participates in CTF competitions and presents at top conferences like BlackHat and DEFCON. Key research areas include heap memory protection, reinforcement learning applications in security, and kernel vulnerability analysis. Notable contributions include frameworks like BandFuzz (collaborative fuzzing), RICE (reinforcement learning optimization), and ShadowBound (heap memory protection). His work has been recognized with awards such as the CCS 2018 Outstanding Paper Award and ACSAC 2017 Best Paper Award. Over 20 students under his guidance have received prestigious awards and moved to roles at Meta, Apple, and top universities. Education: Ph.D., Computer Science, Georgia Institute of Technology Alumni: 10+ former students hold academic or industry positions globally Lab/Team: Active in Sec3, DEFCON CTF, and industrial conference presentations

Marios KogiasView profile

Assistant Professor

• Operating Systems
• Networking
• Distributed Systems
• +4 more

Marios Kogias is an Assistant Professor in the Department of Computing at Imperial College London, conducting research at the intersection of operating systems, networking, and distributed systems with a focus on tail-tolerance, fault-tolerance, and confidentiality using emerging datacenter hardware. He holds a PhD in Computer Science from EPFL (2020) supervised by Ed Bugnion, where his thesis won the Dennis M. Ritchie Award and received an Honourable Mention for the Eurosys Roger Needham PhD Award. His undergraduate degree in Electrical and Computer Engineering is from NTUA. His research spans operating systems, networking, distributed systems, cloud computing, and confidential computing, with significant contributions to microsecond-scale computing, serverless architectures, and eBPF applications. Current work emphasizes tail-latency optimization in datacenter environments and confidential computing security. Recent publications reveal strong trends in microsecond-scale systems, confidential computing, and serverless workflows, demonstrating expertise in leveraging hardware innovations for performance and security guarantees across distributed environments. His scientific awards include: Dennis M. Ritchie Award (2021) Honourable Mention for the Eurosys Roger Needham PhD Award (2021) IBM Fellowship Microsoft Swiss JRC Fellowship Distinguished Artifact Award (ASPLOS 2021) Best Student Paper Award (Eurosys 2020) Dr. Kogias actively mentors PhD students including Konstantinos Prasopoulos (co-advised with Ed Bugnion), Scofield Liu, Farzad Mohammadi, and Adel Sefiane. He teaches Networked Systems, Computer Networks and Distributed Systems, and Object-Oriented Design at Imperial, supported by fellowships from IBM and Microsoft during his doctoral research. His collaborative work spans EPFL, Microsoft Research Cambridge, and Imperial College London, focusing on systems architecture for next-generation datacenter applications.

Nigel HusseyView profile

Professor

• Marine Biology
• Conservation Physiology
• Aquatic Ecosystems
• +4 more

Professor Nigel Hussey is a Biology faculty member at the University of Windsor's Great Lakes Institute for Environmental Research (GLIER). His research focuses on marine megafauna ecology, animal tracking technology, and Arctic ecosystem conservation. Key areas include Greenland shark behavior, beluga whale migration patterns, and the impacts of climate change on Arctic species. Hussey has pioneered the use of acoustic telemetry and satellite tracking to study species such as narwhals, manta rays, and Greenland halibut. He collaborates with Inuit communities in northern Canada to develop sustainable fisheries practices and advises doctoral students like Eric Ste-Marie and Danielle Orrell. His work emphasizes global data-sharing initiatives to enhance conservation efforts, particularly in understudied regions like the Red Sea and Sudan's coastal waters. Education and professional background: While specific educational details are not provided in the texts, his professorial role implies advanced degrees in marine biology or ecology. His research spans over a decade, with notable contributions to understanding elasmobranch behavior, Arctic food webs, and the effects of anthropogenic pressures on marine life. He has contributed to UNESCO World Heritage Site nominations and published in high-impact journals like Nature . Research labs/teams: Active in GLIER, leading interdisciplinary projects involving acoustic tagging and habitat modeling. Collaborates with institutions worldwide on conservation physiology and marine megafauna tracking. His fieldwork includes Arctic expeditions and deep-sea exploration using submersibles.

DING XuhuaView profile

Professor

• System/software security
• Applied cryptography
• Hardware-assisted secure systems
• +4 more

DING Xuhua is a Professor of Computer Science at the School of Computing and Information Systems , Singapore Management University . He directs the Centre on Security, Mobile Applications & Cryptography (SMC) and leads research in system/software security and applied cryptography. PhD in Computer Science from the University of Southern California (2003) Prior degrees: B.Eng and M.Sc from Shanghai JiaoTong University His research focuses on trustworthy systems using hardware virtualization to counter kernel/user-space attacks, with emphasis on: Virtualization-based malware analysis Hybrid symbolic execution frameworks Secure forensics on compromised TrustZone/ARM devices Privacy-preserving cryptographic protocols Content-based video stream authentication His recent publications (2025-2021) span computer science , cybersecurity , and applied cryptography , with a trend toward hardware-assisted security and dynamic analysis tools. Notable awards include the Best student paper (ACISP 2012) and Best paper (IFIP CMS'12) . He mentors PhD students and leads two NRF research grants , with open positions for postdocs and engineers at OASIS and SMC labs.

Jay PscheidtView profile

Professor

• Plant Pathology
• Disease Management
• Agricultural Extension
• +4 more

Dr. Jay Pscheidt is a Professor in the Department of Botany and Plant Pathology at Oregon State University (OSU), affiliated with the College of Agricultural Sciences. His work focuses on diagnosing and managing plant diseases in woody perennials, including tree fruits, nuts, berries, grapes, ornamentals, and turf. He leads the Fruit and Ornamental Disease Management Testing Program and co-edits the Pacific Northwest Plant Disease Management Handbook . His research emphasizes applied diagnostics, fungal/bacterial disease control, and pesticide efficacy testing, often using innovative technologies like intelligent spray systems. Dr. Pscheidt holds multiple leadership roles, including editorial work for peer-reviewed journals and extension publications. His research group includes faculty assistants like Brent Warneke, Nicole DiManno, and Martin James Whitney. He has received prestigious awards such as the APS Excellence in Extension Award (2023) and the Briskey Award (2022). His outreach efforts prioritize delivering practical solutions to growers via websites, courses (e.g., the Phytophthora Online Course ), and extension guides. Key research areas include eastern filbert blight management, mummy berry disease dynamics, and bacterial blight in hazelnuts. He collaborates on projects like sensor-based spray technology to optimize pesticide use and reduce environmental impact. His recent publications address genetic diversity of pathogens, grower decision-making patterns, and disease-resistant cultivar development. Dr. Pscheidt’s grants and collaborations span federal and institutional funding, with a focus on specialty crops. His lab’s work directly impacts Oregon’s agricultural economy, particularly in hazelnut, wine grape, and blueberry industries. He maintains active involvement in both field research and educational outreach, ensuring science translates into actionable farming practices.

• Machine Learning
• Artificial Intelligence
• Data Science
• +5 more

Tommi Kärkkäinen is a Professor at the Faculty of Information Technology, University of Jyväskylä. His research focuses on machine learning, artificial intelligence, and their applications in fields such as nanotechnology, healthcare, and education. He leads projects funded by the Research Council of Finland, including initiatives on catalyst design using AI and structural analysis of hybrid nanoparticles. Education: Formal academic qualifications not explicitly listed in the text. Key Projects: Models and Methods of Self-Similar Network Traffic Analysis (2023–2026), High Performing Machine Learning for Novel Catalyst Design (2022–2024), and Structure Prediction of Hybrid Nanoparticles via Artificial Intelligence (2018–2022). Research Interests: Digitalization-driven data processing, machine learning for material science, and AI ethics in education. His work bridges theoretical advancements with practical implementations in healthcare diagnostics, flight training simulations, and educational equity. Notable contributions include developing neural network models for epilepsy detection, AI-driven catalyst design frameworks, and methodologies for evaluating digital competence in healthcare personnel. His work often involves interdisciplinary collaboration across nanoscience, education technology, and cognitive science. Grants: Over €16M secured through Research Council of Finland programs, including Profi3 (2017–2021) and Profi6 (2021–2026). Awards: Received the Best Student Paper Award (2024) for work on smart city place-belongingness strategies. Labs/Teams: Active in follow-up groups like OHTE (Engineering) and HUMBLE (Human-Machine Intelligence).

Dietmar LeisenView profile

Professor

• Financial Derivatives Pricing
• Risk Management
• Financial Market Equilibrium
• +5 more

Prof. Dietmar Leisen is a Professor of Banking at the Department of Banking, Johannes Gutenberg University Mainz. He leads the Chair of Banking and oversees research assistants like Lars Scheuer and Elisabeth Stanowitsch. His research focuses on financial derivatives valuation, systemic risk analysis, venture capital contracting, and risk management strategies. He has published extensively in top journals such as Journal of Financial Stability and Quantitative Finance . Key research interests include: Dynamic equilibrium models with heterogeneous agents Stochastic volatility pricing frameworks Systemic risk governance in banking systems Incentive mechanisms in venture capital financing Long-term investment strategies Recent work explores systemic risk linkages, executive compensation impacts on risk-taking, and structural models of bank default dynamics. His contributions address critical issues in financial regulation, market stability, and derivative pricing methodologies.

Tudor DumitrașView profile

Associate Professor

• System Security
• Machine Learning
• Big Data
• +5 more

Tudor Dumitraș is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Maryland, with a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and core faculty status in the Maryland Cybersecurity Center. His research focuses on data-driven security, empirical studies of adversary behavior, and the security of machine learning systems. Education Ph.D. and M.S. in Electrical and Computer Engineering from Carnegie Mellon University Diplôme d’Ingénieur in Computer Science from Ecole Polytechnique, Paris, France B.S. in Computer Science from "Politechnica" University, Bucharest, Romania Dumitraș's work bridges system security, big data analysis, and machine learning. He developed the Worldwide Intelligence Network Environment (WINE), an innovative platform for sharing cybersecurity field data between academia and industry. His research includes malware detection using machine learning, analysis of zero-day attacks, and mitigation of adversarial threats against AI models. Recent publications highlight his contributions to adversarial machine learning, vulnerability exploit prediction, and neural network security. Scientific awards include the NSA Best Scientific Cybersecurity Paper Honorable Mention (2013), A.G. Jordan Award from Carnegie Mellon (2011), ACM SIGPLAN John Vlissides Award (2009), and multiple conference best paper awards. He has secured research funding from Amazon Web Services and received scholarships from the French government. Dumitraș advises graduate students and contributes to professional communities through program committee service, including on USENIX Security'24. He leads the development of security datasets and tools like Exploitability.app, HardwareFail.ml, and FeatureSmith. His outreach includes TED-style talks explaining cybersecurity concepts to broad audiences.