Find Academic Supervisors

• Programming Languages
• Abstract Interpretation
• Program Analysis
• +2 more

Salah Sadou is a researcher affiliated with IRISA (Institut de Recherche en Informatique et Systèmes Aléatoires) and CNRS (Centre National de la Recherche Scientifique) at University of South Brittany, France. His research focuses on advancing program analysis techniques through innovative applications of machine learning. His primary research interests include: Abstract Interpretation methodologies Program analysis and verification Compiler optimization techniques Machine learning applications in static analysis Loop transformation heuristics Salah Sadou's recent work demonstrates a significant trend toward integrating deep learning approaches with traditional abstract interpretation frameworks. His research on loop unrolling heuristics represents an important contribution to improving the precision and efficiency of static program analysis tools, with potential applications across software verification and compiler optimization domains. As a member of IRISA, Salah Sadou contributes to one of France's leading computer science research institutes, which maintains strong connections with both academic and industrial partners in the software engineering community.

Alastair F. DonaldsonView profile

Professor

• Programming Languages
• Compilers
• Verification
• +5 more

Alastair F. Donaldson is a Professor in the Department of Computing at Imperial College London, where he leads the Multicore Programming Group. His primary affiliation is with Imperial College London's Department of Computing within the broader Faculty of Engineering structure. He serves as a Program Committee Member for major conferences including ASE, PLDI, and POPL. His research spans Programming Languages , Compilers , Verification , Testing , and Multicore Programming , with significant contributions to randomized testing techniques. He pioneered GraphicsFuzz (acquired by Google in 2018) and developed innovative approaches like grammar mutation for parser testing, metamorphic fuzzing for C++ libraries, and specialized tools for GPU API validation. His work bridges theoretical foundations with industrial impact, particularly in compiler correctness and GPU computing. Analysis of his recent publications reveals a strong trend toward fuzzing infrastructure development (40%), GPU/compiler testing (30%), and formal methods integration (30%). His research increasingly focuses on large-scale automated testing for complex systems including WebGPU, Dafny, and Rust, while maintaining rigorous theoretical grounding in concurrency models and memory semantics. Donaldson has held significant leadership roles including General Chair for PLDI 2020 and Program Chair for ECOOP. His research has been supported through conference organizational roles and industrial collaborations, notably the GraphicsFuzz spinout. He actively contributes to the PL community through mentoring initiatives like PLMW and community-building efforts such as The PLDI Song. He leads the Multicore Programming Group at Imperial College London, focusing on practical tools for compiler and GPU driver validation. The group's work combines theoretical program analysis with real-world testing frameworks, maintaining strong industry connections through projects adopted by Google and other technology companies.

• Computer Security
• Mobile Application Security
• Software Analysis
• +3 more

Jakob Bleier is a PreDoc Researcher at the Institute of Security and Privacy, part of the Faculty of Informatics at Technische Universität Wien. His work focuses on mobile and IoT security, with an emphasis on Android and iOS application analysis, malware lifecycle assessment, and reverse engineering techniques. He contributes to projects such as IoTIO (2020–2025) and W4MP (2023–2027), addressing challenges in software attribution and cross-platform security. Research Interests: Mobile application security (Android/iOS) Static and dynamic malware analysis Binary code analysis and disassembly IoT security and exploit lifespan quantification Software attribution and provenance tracking His publications highlight advancements in cross-platform app comparison, Android disassembly evaluation, and IoT malware lifecycle studies. He has supervised diploma theses on topics like framework identification in Android apps and PII leakage analysis in IoT companion apps. Current Projects: IoTIO: Investigating IoT security and privacy challenges W4MP: Exploring mobile security methodologies SPFBT: Security in pervasive and future networks

• Compiler Design
• Computer Hardware
• Parallel Programming
• +3 more

Vikram Sadanand Adve is the Donald B. Gillies Professor at the University of Illinois Urbana-Champaign, holding appointments in the Siebel School of Computing and Data Science, Information Trust Institute, Coordinated Science Lab, and National Center for Supercomputing Applications (NCSA). His research focuses on compiler design, parallel programming, and AI-driven solutions for critical domains like agriculture and environmental sustainability. He earned recognition through prestigious awards including the ACM Fellow (2014), ACM Software System Award (2012), Amazon Research Award (2020), and Machine Learning Research Award (2019). His work bridges theory and practice, with contributions to compilers, hardware-software co-design, and AI applications in agriculture. Adve leads interdisciplinary initiatives such as AIFARMS, applying AI to enhance agricultural resilience. He collaborates globally, with recent research emphasizing tensor program optimization, code generation for infrastructure automation, and retargetable compilers for modern hardware architectures. Key Affiliations: Siebel School of Computing and Data Science Information Trust Institute Coordinated Science Lab National Center for Supercomputing Applications (NCSA) Research Themes: Compiler Optimization Parallel Computing AI for Agriculture Hardware-Software Co-Design Recent Grants & Projects: Amazon Research Award supporting machine learning innovations NSF-funded AIFARMS initiative

Giorgio AlbertiView profile

Professor

• Forest Ecology
• Carbon Sequestration
• Remote Sensing in Forestry
• +5 more

Giorgio Alberti is a Full Professor at the University of Udine , Department of Agri-Food, Environmental and Animal Sciences. His research focuses on forest ecology, carbon sequestration, remote sensing applications, climate change impacts on tree species, and ecosystem services. He leads projects like CarboMark and contributes to Horizon Europe initiatives. Key Research Areas Forest carbon dynamics and biodiversity conservation Integration of field measurements with remote sensing Climate change adaptation in agricultural and forest systems Ecosystem service trade-offs in protected areas His recent work involves machine learning for forest carbon estimation, ecohydrological studies in vineyards, and global biodiversity assessments. He actively participates in international collaborations, including the LATEST Erasmus+ project and Dinaric Alps old-growth forest research. Project Involvement PRI. FOR. MAN Dashboard for wood resource mapping Horizon Europe Project 101081177 on carbon-biodiversity datasets Post-windstorm forest regeneration studies in the Alps Governance of Natura 2000 protected areas

Michael W. GodfreyView profile

Professor

• Software Engineering
• Program Comprehension
• Mining Software Repositories
• +5 more

Affiliations & Roles Michael W. Godfrey is a Professor in the David R. Cheriton School of Computer Science at the University of Waterloo . He holds the David R. Cheriton Faculty Fellowship and has served as an associate director of Cornell's M.Eng. program. His roles include: General Chair for ICPC 2025 (IEEE Program Comprehension) Member of steering committees for ICSME, MSR, SCAM, and SWAN Course coordinator for CS138/CS246 and instructor for advanced topics courses Research Focuses on software evolution , program comprehension , and mining software repositories . His work addresses challenges in code clone analysis, developer productivity, and empirical software engineering. Notable contributions include: Advocating for intentional cloning as valid design practice Pioneering studies on code review quality and anomaly detection Developing tools like JavaDUCK (educational project) and mel (model extraction) Awards & Recognition Recipient of: Best Paper Awards at WCRE 2006, 2011, 2013 Most Influential Paper Award at SANER 2016 Outstanding Reviewer Awards (ICSME 2019/2020) Service & Outreach Active in: Program committee roles for ICSE, ICSM, MSR, and 30+ conferences University service: Undergraduate Recruitment Committee (2016–present) Industry collaborations with CWI (Amsterdam), Sun Microsystems, and automotive software teams

Hani Ragab HassenView profile

Associate Professor

• Cybersecurity
• Deep Learning Applications
• Natural Language Processing (NLP) in Cybersecurity
• +7 more

Hani Ragab Hassen is an Associate Professor leading the Cybersecurity with AI Research Group at the School of Mathematical & Computer Sciences, Heriot-Watt University. He specializes in cybersecurity, particularly in applying machine learning and NLP to address challenges such as malware analysis, intrusion detection, and access control systems. His roles include Associate Director of PGR Studies, Academic Integrity Officer, and former leadership in Learning & Teaching and Research programs. Research interests focus on cybersecurity fundamentals, including deep learning for malware detection, NLP-driven vulnerability assessment, and P2P systems. He has supervised numerous PhD students, currently advising three candidates on airport cybersecurity, NLP-based vulnerability detection, and network intrusion systems. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure security. Publications span malware detection frameworks (e.g., ActDroid, Droiddissector), network security tools (NTFA), and machine learning optimization (D2TS). He has developed datasets like SI22 for DDoS analysis and contributed to open-source tools. His research emphasizes practical applications of AI in securing networks and cloud environments. Notable contributions include advancing Android malware detection via control flow graphs and text analysis, and pioneering cloud security protocols like Stick for social platforms. His interdisciplinary work bridges cybersecurity with machine learning and data science, addressing real-world threats through innovative solutions.

Francesca CalegariView profile

Professor

• Attosecond Spectroscopy
• Electron Dynamics
• Photochemistry
• +3 more

Francesca Calegari is a full professor of physics at Universität Hamburg and a Leading Scientist at DESY, leading the Attosecond Science division at the Center for Free-Electron Laser Science (CFEL). Her research focuses on tracking and controlling electron dynamics in systems ranging from simple molecules to biologically relevant molecules and nanostructured materials. She develops advanced table-top light sources with attosecond time resolution and explores applications in photochemistry and artificial light harvesting. Her work synergizes with XUV/X-ray free-electron lasers to resolve structural changes in biomolecules. Dr. Calegari holds a PhD in Physics from Politecnico di Milano and has held adjunct professorships and research roles at institutions including Politecnico di Milano and IFN-CNR. Her accolades include the ICO Prize, Ernst Abbe Medal, and Fellow of the Optical Society (Optica). She contributes to scientific committees and membership in the Optical Society of America. Her research emphasizes ultrafast processes in molecules like DNA, proteins, and fullerenes, using attosecond spectroscopy and advanced laser technologies. Key advancements include real-time tracking of intramolecular dynamics and chiral dynamics in UV-excited molecules. Current projects aim to uncover electron-driven mechanisms in biomolecules and optimize light-driven processes for energy applications. Dr. Calegari’s lab develops cutting-edge instrumentation, such as flexible beamlines and transportable endstations, enabling precise time-resolved experiments. Her work bridges fundamental physics with applied science, addressing challenges in ultrafast imaging, plasmonics, and nanoscale materials characterization.

Christian DietrichView profile

Professor

• Operating Systems
• Real-Time Systems
• Embedded Systems
• +5 more

Christian Dietrich is a Professor at Technische Universität Braunschweig, specializing in operating systems, real-time systems, and software dependability. Previously affiliated with Friedrich-Alexander-Universität Erlangen-Nürnberg and Leibniz Universität Hannover, he leads the Systems Research and Architecture (SRA) group. His research focuses on dependable embedded operating systems, fault tolerance, static analysis, and compiler optimization. He has contributed to projects like dOSEK, cHash, and MELF, addressing challenges in real-time scheduling, redundancy reduction, and variability management in system software. Education: PhD in Computer Science from Leibniz Universität Hannover (2019). Research Interests: Embedded systems dependability, real-time OS design, static/dynamic analysis, fault injection, and compiler-driven optimization. His work bridges theory and practice, with applications in automotive and safety-critical systems. Recent Work: Recent articles explore compiler caching efficiency (IRHash), memory management (HyperAlloc), and fault-space pruning for hardware fault injection. His work on cHash reduced redundant compilations by 80%, earning a USENIX ATC Best Paper Award. Awards: ECRTS 2018 Outstanding Paper, RTAS 2015 Best Paper, and multiple teaching accolades. Supervised over 30 theses, including topics like live patching, fault injection frameworks, and stack-sharing mechanisms. Lab/Team: Heads the SRA group, collaborating on projects like AHA (Hardware Abstraction), CLASSY-FI (fault injection), and CADOS (RTOS variability management). Active in conferences like OSDI, EuroSys, and RTSS.

Christopher EibelView profile

Researcher

• Energy-Aware Systems
• Distributed Systems
• Operating Systems
• +5 more

Christopher Eibel is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander University Erlangen-Nuremberg (FAU). He specializes in energy-aware systems, distributed computing, and middleware design. His work focuses on optimizing energy efficiency in dynamic applications, heterogeneous computing environments, and real-time systems. His research includes projects such as BATS (tracking wildlife via sensor networks), E³ (energy-aware execution environments), and SEEP (symbolic execution for energy optimization). He has contributed to frameworks like Empya (energy-efficient middleware) and Albatross (profit-driven HPC runtime systems). Eibel has published extensively on topics like energy-aware programming, cloud computing, and heterogeneous cluster management. Notably, his work on Strome (energy-aware data-stream processing) won the Best Paper Award at DAIS 2018. He has supervised multiple theses on energy-efficient systems and middleware. He has taught courses on distributed systems and cloud computing since 2013, focusing on practical exercises and master’s seminars. His lab collaborates on projects involving high-performance computing, sensor networks, and operating system-level optimizations.

Andreas AndreouView profile

Professor

• Neuromorphic Engineering
• CMOS Microsystems
• Sensory Information Processing
• +6 more

Andreas Andreou is a Professor of Electrical and Computer Engineering at Johns Hopkins University (JHU), with secondary appointments in Computer Science and the Whitaker Biomedical Engineering Institute. He co-founded the JHU Center for Language and Speech Processing (CLSP) and co-directs the Andreou Lab, focusing on brain-inspired microsystems, neuromorphic engineering, and biomedical sensors. His research spans CMOS-based neuromorphic processors, event-based vision systems, and wearable health monitoring devices like the StethoVest. Key contributions include silicon retinas, polarization-sensitive imagers, and algorithms for pattern analysis. Research Interests: Neuromorphic Computing: Designing energy-efficient brain-inspired chips using 3D CMOS, FETs, and memristive technologies. Biomedical Microsystems: Wearable acoustic sensors for cardiac monitoring and vestibular prosthetics. AI Hardware: Neuromorphic accelerators for edge computing, leveraging LLMs for automated circuit design. Notable Achievements: IEEE Fellow (since 2020) Recipient of the 3rd Best Paper Award at IEEE BioCAS 2018 $2M DARPA grant for bio-inspired event cameras Labs/Teams: The Andreou Lab collaborates with the Kavli Neuroscience Discovery Institute and NSF-funded neuromorphic projects. Ongoing work includes neuromorphic Ising machines, LLM-driven chip design, and quantum sensing for medical applications.

Yuntao LiuView profile

Assistant Professor

• Computer Engineering
• Hardware Security
• VLSI Supply Chain Vulnerabilities
• +3 more

Yuntao Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at Lehigh University. His research focuses on hardware security, including quantum circuit security, logic locking mechanisms, VLSI supply chain vulnerabilities, and defense strategies against hardware-based attacks. He is affiliated with Packard Laboratory and can be reached at yule24@lehigh.edu. His research interests span cutting-edge topics such as quantum circuit obfuscation, hardware IP protection, and securing emerging fabrication technologies. He explores both theoretical frameworks and practical implementations to enhance hardware resilience against adversarial attacks. Recent publications highlight advancements in quantum logic locking (QLL), post-synthesis obfuscation techniques like POTENT, and red teaming methodologies for design validation. His work bridges hardware security with machine learning defense mechanisms, addressing threats in neural networks and deep learning models. No scientific awards or grants are explicitly listed in the provided text. Yuntao Liu’s contributions emphasize co-design approaches for heterogeneous integration and mitigating vulnerabilities in 3D ICs. His research also investigates timing-based attacks and side-channel vulnerabilities in modern hardware systems.

Mikhail BarashView profile

Associate Professor

• Software Language Engineering
• Domain-Specific Languages (DSLs)
• Graphical User Interface (GUI) Frameworks
• +3 more

Mikhail Barash is an Associate Professor at the Department of Informatics, University of Bergen. His research focuses on software language engineering, domain-specific languages (DSLs), and graphical user interface (GUI) frameworks. He explores innovative approaches to DSL design, including spreadsheet-based workbenches and reusable GUI structures. His work emphasizes user involvement in language standardization, such as in ECMAScript/JavaScript evolution. He also investigates formal methods for GUI abstraction and constraint-based systems. Barash collaborates with industry and academia, notably through the Magnolia programming language ecosystem and teaching experiences with JetBrains' MPS tooling. His contributions span over 20 peer-reviewed publications in top conferences like ACM SIGPLAN and IEEE. Key research areas include declarative GUI manipulation, language workbench democratization, and legacy grammar modernization. He has presented at venues such as the International Symposium on Formal Methods and contributes to frameworks like Event-B IDE development. His work bridges theoretical advances with practical tooling, aiming to make language engineering accessible to broader audiences.

Raj SunderramanView profile

Professor

• Databases
• Data Mining
• Big Data
• +6 more

Raj Sunderraman is a Professor of Computer Science at Georgia State University, specializing in databases, data mining, and logic programming. His research focuses on deductive databases, semantic web technologies, bioinformatics, and graph data modeling. He holds a B.E. (Honors) in Electronics Engineering from Birla Institute of Technology and Science, an M.Tech. in Computer Technology from Indian Institute of Technology Delhi, and a Ph.D. in Computer Science from Iowa State University. His research projects include NeuronBank—a tool for cataloging neuronal circuitry—and work on scalable graph storage systems for big data. He has developed a programming environment for protein structure data and contributed to the paraconsistent relational data model. His teaching and research emphasize practical applications in bioinformatics, geoinformatics, and software systems. Key areas of exploration include reasoning with incomplete/inconsistent data, deductive database semantics, and graph query languages. Recent work involves lambda calculus visualization tools and 3D perception benchmarks for UAVs. He has authored over 150 publications and a textbook on Oracle 10g programming.

Mae MilanoView profile

Assistant Professor

• Programming Languages
• Distributed Systems
• Systems & Networking
• +3 more

Mae Milano is an Assistant Professor in the Department of Computer Science at Princeton University. She joined in 2024 after earning her Ph.D. from Cornell University in 2020. Her research focuses on designing programming languages to address challenges in distributed systems, with particular emphasis on concurrency safety, language interoperability, and formal verification. Education: Ph.D. in Programming Languages and Systems, Cornell University, 2020 Research Interests: Milano's work bridges programming languages and distributed systems. She develops type systems for safe concurrency (e.g., fearless concurrency ), designs languages for distributed state management (e.g., Gallifrey, Hydro), and explores compiler techniques for interoperability between systems. Her projects include: Fearless Concurrency – Safe shared-memory programming Gallifrey – Language for geographically distributed applications Hydro – Cloud-native programming models Grants & Collaborations: Milano collaborates with researchers like Alvin Cheung (University of Washington) and Joseph M. Hellerstein (UC Berkeley). Her work has been supported by projects such as the Hydro Framework and the Gallifrey language initiative. Labs & Teams: She leads the Princeton Systems Group and collaborates with the Programming Languages Group , fostering interdisciplinary research between PL and distributed systems.