Find Academic Supervisors

Nathan S. EvansView profile

Associate Professor

• Network Security
• Automotive Security
• Distributed Systems
• +3 more

Dr. Nathan S. Evans is a Teaching Associate Professor and Academic Director for Cyber Security at the University of Denver. He holds a PhD in Computer Science from Technische Universität München (2011) and has extensive industry experience, including roles as Senior Principal Research Engineer at Symantec Research Labs and CTO of CloudHawk. His research focuses on network security, automotive security, low-level systems, and distributed systems. Dr. Evans is actively involved in academic and industry initiatives such as the Colorado Research Institute for Security and Privacy (CRISP) and organizes cyber competitions like the Mountain West Cyber Challenge. Education: PhD in Computer Science, Technische Universität München (2011) MSc in Computer Science, University of Denver (2009) BSc in Computer Science and BA in Criminal Justice, Baldwin Wallace College (2006) Research Interests: Evans' work bridges theoretical security concepts with practical applications. His recent studies address emerging threats in automotive networks, mobile device security, and cloud infrastructure. He emphasizes hands-on education through initiatives like DU's Cyber Security Master’s program. Articles Overview: Recent publications highlight advancements in cryptocurrency mining analysis, container security, and automotive system vulnerabilities. His work often explores real-world implications of theoretical security models. Labs/Teams: As CRISP’s Point-of-Contact, he leads interdisciplinary efforts in cyber defense. He mentors students in competitions like CyberForce and NSA Ghidra SRE Challenge, fostering workforce development.

Ehsan ZaffarView profile

Professor

• Civil Rights
• Civil Liberties
• National Security
• +4 more

Ehsan Zaffar is a civil rights lawyer, educator, and social innovator currently holding faculty positions at Arizona State University's School of Social Transformation and Sandra Day O'Connor College of Law. He serves as the Chief Difference Engineer of The Difference Engine at Arizona State University. Previously, he taught at George Washington University and George Mason University. Zaffar served for a decade as a Senior Advisor on Civil Rights at the U.S. Department of Homeland Security, advising the Secretary on civil rights implications of national security policies. Zaffar received his law degree from Pepperdine University School of Law with a certificate in Dispute Resolution from the Straus Institute. His background as a child refugee fleeing war has profoundly shaped his commitment to civil rights and serving vulnerable communities. Zaffar's research focuses on the critical intersection of civil rights, civil liberties, and national security policy. His work examines how to build resilient communities while maintaining civil liberties in homeland security contexts. He has pioneered approaches to community engagement that balance security needs with fundamental rights, particularly in surveillance, privacy, and religious freedom. His scholarship addresses economic insecurity issues and develops practical solutions to inequality, including the Women's Power & Influence Index. His publications reveal an unusual interdisciplinary breadth spanning civil rights/security policy and software engineering. In policy, he authored 'Understanding Homeland Security: Foundations of Security Policy' (2019). In technology, he published eight research papers from 2009-2021 covering architectural decay, software quality, and self-adaptive systems, demonstrating rare expertise across both domains. Zaffar has received significant recognition for his public service: U.S. State Department's Benjamin Franklin Award for Public Diplomacy Department of Homeland Security Secretary's Award for Excellence As an educator, Zaffar has taught over 100 courses on civil rights, civil liberties, and privacy. His advising extends to government policy where he implemented UN Human Rights Council Resolution 16/18 on religious intolerance. He has secured millions for The Difference Engine's initiatives including the Distinguished Innovation Fellows program. His founding of the Los Angeles Mobile Legal Aid Clinic represents an innovative approach to legal services for vulnerable communities. Zaffar directs The Difference Engine at Arizona State University, building models to combat inequality nationwide. He serves on influential boards including the ACLU of California, Team Rubicon, and The Non Profit Partnership. His 'UnfairNation' podcast explores power, inequality, and civil justice, extending his educational mission beyond traditional academic settings.

• High-Performance Computing
• Parallel Programming
• GPU Computing
• +3 more

assoz. Prof. Dipl.-Ing. Dr. Peter Thoman is an Associate Professor in the Department of Computer Science at the University of Innsbruck. His work focuses on high-performance computing, parallel programming models, and GPU-accelerated systems. He leads research in areas such as SYCL standard implementations, distributed computing optimizations, and energy-efficient algorithms for exascale applications. His research interests include task-based parallelism, heterogeneous computing architectures, and scalable runtime systems. Notable contributions include the Celerity API for accelerator clusters and the LIGATE drug discovery platform. He is affiliated with the University of Innsbruck’s technical research groups and collaborates on projects like the AllScale framework. Dr. Thoman’s teaching includes courses on parallel programming and high-performance computing systems. He is a member of the Department’s leadership team under Prof. Thomas Fahringer.

• Cyber-Physical Systems
• Runtime Monitoring
• Software Engineering
• +3 more

Dr. Michael Vierhauser is an Assistant Professor in the Department of Computer Science at the University of Innsbruck. His research focuses on Cyber-Physical Systems (CPS), runtime monitoring, autonomous systems, and software engineering methodologies. He specializes in safety-critical systems, human-machine interaction, and innovative educational technologies for programming and software development. Key research areas include: Runtime monitoring frameworks for CPS and UAVs Development of adaptive systems and self-protective IoT devices Integration of AI into software engineering education Agile methodologies for sustainability assessment His recent publications emphasize field-testing of drone missions, automated simulation testing for aerial systems, and frameworks like FORTE for scalable environmental monitoring. He leads projects like Dronology, an incubator for CPS research, and contributed to tools such as ReMinds and GRuM for runtime monitoring. Dr. Vierhauser collaborates on digital transformation initiatives in underground construction and has designed learning analytics dashboards to improve programming education outcomes. His work bridges theory and practice through real-world applications in emergency response systems and industrial 4.0 contexts.

Alvine Boaye BelleView profile

Assistant Professor

• System Assurance
• Safety Assurance
• Autonomous Driving Systems
• +3 more

Dr. Alvine Boaye Belle is an Assistant Professor in the Department of Electrical Engineering & Computer Science at Lassonde School of Engineering, York University. She leads the DARE! research group and serves on multiple international committees, including ICSE and RE conferences. Her work bridges software engineering with equity, diversity, and inclusion (EDI) initiatives. PhD in Software Engineering (École de Technologie Supérieure, University of Quebec) 2-year Industrial Postdoctoral (University of Ottawa) Graduate Diploma in Public Administration & Governance (McGill University) Dr. Belle's research focuses on system assurance for autonomous systems, generative AI applications in software engineering, and EDI in computing . She applies machine learning to safety case automation and vulnerability detection, as shown in her publications with high-impact journals. Her recent work explores deep learning and SVM models for Android malware detection with 99% accuracy. She mentors a diverse group of students across Bachelor's, Master's, and PhD levels, emphasizing accessibility and social impact in technology. Keynote speaker at Black History Month events Moderator of EDI-focused panels at ICSE conferences Editorial board member for journals like IEEE Software and Information and Software Technology

Polyvios PratikakisView profile

Associate Professor

• Parallel Programming
• Distributed Systems
• Programming Languages
• +2 more

Polyvios Pratikakis is Associate Professor in the Computer Science Department at University of Crete and Visiting Researcher at FORTH-ICS. Research develops tools for parallel/distributed software execution, focusing on programming languages, runtimes, and static analysis for modern hardware. Current projects include EuroEXA (programming models for exascale applications) and ETAK (earthquake simulation deployment in cloud environments). Past projects include ASAP (big data workflows), Myrmics/BDDT/PARTEE (task-parallel runtimes), and GreenVM (JVM for non-cache-coherent architectures). Additional research examines software fault tolerance and static analysis for parallel programs. Teaching includes undergraduate/graduate courses on Parallel Programming, Type Systems, Multicore Programming, and Computer Science fundamentals. Supervises multiple MSc/PhD students in compiler design, runtime systems, and social network analytics. Service includes program committees (EuroPar, CF), HiPEAC organization, and faculty committees at University of Crete.

David BremnerView profile

Professor

• Programming Languages
• Computational Geometry
• Mathematical Optimization
• +3 more

David Bremner is a Professor of Computer Science at the University of New Brunswick (UNB) with a cross-appointment to the Department of Mathematics and Statistics. He holds degrees from the University of Calgary (B.Sc. Hons., 1990), Simon Fraser University (M.Sc., 1993), and McGill University (Ph.D., 1997). After a postdoctoral fellowship at the University of Washington (1997-1999), he joined UNB in 2000. His research focuses on Programming Languages, Computational Geometry, and Mathematical Optimization. He teaches courses such as Programming Language Interpretation and contributes to software projects like inetools and Sparktope . Active in academic service, he organizes programming competitions and oversees graduate studies. His work emphasizes practical applications in memory management, JIT compilation, and algorithm design.

Georgiy KrylovView profile

Assistant Professor

• High Performance Computing
• Compilers and Runtime Environments
• FPGA CAD
• +2 more

Georgiy Krylov is an Assistant Professor at the Faculty of Computer Science, University of New Brunswick. He holds a PhD from UNB (2024), and master's and bachelor's degrees from Nazarbayev University (2018 and 2016). His research focuses on high-performance computing, compilers/runtime environments, FPGA CAD, and quantum/reversible computing. Education: PhD in Computer Science, University of New Brunswick (2024) MSc in Computer Science, Nazarbayev University (2018) BSc in Computer Science, Nazarbayev University (2016) Research Interests: His work spans compiler optimization, quantum circuit design, FPGA applications, and ahead-of-time (AOT) compilation techniques. He explores geometric refactoring for quantum circuits, heterogeneous logic implementations, and GPU acceleration in genetic algorithms. Publications Trends: Recent work emphasizes AOT compilation frameworks (e.g., Eclipse OMR), quantum computing optimizations, and FPGA-based CAD tools. Earlier studies focused on GPU-accelerated algorithms for quantum circuit synthesis. Grants/Advising: No specific grants or advisees listed. Active in open-source compiler toolchains and hardware-software co-design projects.

Lars Ailo BongoView profile

Professor

• Operating Systems
• Concurrent Programming
• Data-intensive Computing
• +5 more

Lars Ailo Bongo is a Professor at the Department of Computer Science, UiT The Arctic University of Norway. His research interests span operating systems, concurrent programming, data-intensive computing, and applications of machine learning in healthcare and bioinformatics. He has been actively involved in teaching courses such as Operating Systems, Concurrent Programming, and Algorithms, emphasizing open-access educational materials. Notably, three of his master’s students received awards for their theses: Nina Angelvik (2018), Bjørn Fjukstad (2014), and Martin Ernstsen (2013). He also advises students like Johan Ravn, whose master’s project led to a startup. Bongo’s work includes developing scalable bioinformatics pipelines (e.g., NeLS infrastructure), optimizing genomics workflows, and advancing tools for medical image analysis. He pioneered open-access course repositories on GitHub and contributed to visualization frameworks like GeneNet VR. His research bridges computer science with healthcare, focusing on tumor infiltration lymphocyte analysis, AI-driven diagnostics, and ethical AI applications in mental health. He has held roles as a postdoc at Princeton and TA at the University of Tromsø. His scientific contributions span over 50 peer-reviewed articles, covering topics from parallel computing to synthetic health data interoperability. He emphasizes reproducibility and transparency in data management, exemplified by projects like Occode for historical data transcription and MORTAL language for cross-paradigm computing. In education, Bongo advocates for accessible teaching materials and has designed courses like INF-2202 Concurrent Programming, which utilize modern tools (e.g., Go language) and GitHub repositories. His teaching philosophy integrates practical coding with theoretical foundations, fostering student innovation and open-source collaboration.

Dirk PflügerView profile

Professor

• Scientific Computing
• High-Performance Computing (HPC)
• Parallel and Distributed Systems
• +3 more

Dirk Pflüger is a Professor at the University of Stuttgart's Institute of Parallel and Distributed Systems, within the Faculty of Computer Science, Electrical Engineering and Information Technology. His research focuses on high-performance computing (HPC), parallel and distributed systems, and sparse grids. He has led projects in astrophysical simulations, machine learning applications, and uncertainty quantification. Notable contributions include developing scalable algorithms for exascale computing using HPX, Kokkos, and SYCL frameworks. His expertise spans distributed computing architectures, task-based parallel programming, and interdisciplinary applications in astrophysics and medical AI. Recent work includes optimizing hyperparameter tuning, simulating stellar mergers, and enhancing blood glucose prediction models using deep reinforcement learning. Pflüger's research emphasizes performance portability, fault tolerance, and cross-platform collaboration. He has contributed to open-source tools like PLSSVM and hws, which address hardware monitoring and GPU acceleration challenges. His work bridges theoretical advancements with practical implementations for real-world computational problems.

Dongyoon LeeView profile

Associate Professor

• Computer Systems
• Software Reliability
• Software Security
• +9 more

Dongyoon Lee is an Associate Professor in the Department of Computer Science at Stony Brook University. His research focuses on building reliable, secure, and efficient software systems, spanning compiler design, operating systems, security, and hardware architecture. He holds a Ph.D. (2013) from the University of Michigan, Ann Arbor, and has held positions at Virginia Tech (2014-2019) and internships at Microsoft Research, NEC, and IBM. Education: Ph.D. in Computer Science & Engineering, University of Michigan, Ann Arbor (2013) M.S. in Computer Science & Engineering, University of Michigan, Ann Arbor (2009) B.S. in Electrical and Computer Engineering, Seoul National University (2004) Research Interests: Lee's work addresses challenges in software reliability (e.g., concurrency bugs, transient faults), security (e.g., memory safety, kernel permissions), and runtime systems (e.g., stream processing, distributed storage). He leads the COSY Lab (Compilers, Operating Systems, and Security), emphasizing cross-stack solutions. Recent Article Trends: Recent publications focus on homomorphic encryption compilers (e.g., DaCapo , HECATE ), energy-efficient systems ( Write-Light Cache ), and security tools like DevFuzz for device driver testing. Themes include optimizing performance-security trade-offs and addressing vulnerabilities in edge computing and embedded systems. Awards: Distinguished Paper Awards (ESEC/FSE 2018, ASE 2019), ICTAS Junior Faculty Award (2017), Google Research Award (2015), and ProQuest Distinguished Dissertation Award (2013). Advising & Grants: Supervises students in Ph.D., MS, and undergraduate programs. Secured grants including NSF SaTC funding for homomorphic encryption compilers and projects with the South Korean Agency for Defense Development (ADD). Leads research on ARM TrustZone security and energy harvesting systems. Labs/Teams: COSY Lab (Compilers, Operating Systems, and Security) at Stony Brook, collaborating on cross-disciplinary projects with industry and government partners.

Thomas FahringerView profile

Professor

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +4 more

Thomas Fahringer is a full Professor and Head of the Distributed and Parallel Systems Group at the University of Innsbruck's Institute of Computer Science. His research focuses on parallel computing, distributed systems, and high-performance computing (HPC), with particular emphasis on GPU acceleration, cloud/edge computing, and serverless architectures. He leads interdisciplinary projects involving scientific workflows, resource management systems, and exascale computing solutions. Key research areas include: Design of high-level APIs for accelerator clusters (e.g., Celerity-RSim) Optimization of IoT and LoRa networks using machine learning Scalable key-value stores for geo-distributed systems Workflow scheduling in edge-cloud continuum environments Recent work emphasizes automation of deployments, energy-efficient transmission policies, and fault-tolerant orchestration of serverless functions. He actively participates in community initiatives like the Workflows Community Summit, driving advancements in scientific workflows and HPC ecosystems. His lab develops frameworks such as Apollo and AllScale, targeting exascale computing and distributed runtime systems.

Kevin HamlenView profile

Associate Professor

• Cybersecurity
• Malware Analysis
• Software Security
• +4 more

Kevin Hamlen is an Associate Professor of Computer Science at the Erik Jonsson School of Engineering and Computer Science , The University of Texas at Dallas . He holds a Ph.D. and MS in Computer Science from Cornell University (2006 and 2002) and dual BS degrees in Computer Science and Mathematical Sciences from Carnegie Mellon University (1998). His research focuses on cybersecurity, including malware analysis, active defense mechanisms, and formal verification of secure systems. Notable contributions include the Frankenstein malware synthesis framework and the Red Herring decoy system for detecting cyberattacks. Professional preparation includes roles as a Research Intern at Microsoft Research (2002), Research and Teaching Assistant at Cornell (1998–2006), and Technical Consultant at Microsoft Research Redmond (2001). His work has been recognized with awards such as the NSF CAREER Award (2011) and the Air Force Young Investigator Program Award (2008). Research interests emphasize proactive cybersecurity measures, including techniques to deceive attackers (e.g., honey-patching, dynamic deception), vulnerability detection, and securing cloud and IoT ecosystems. His publications span topics like control-flow integrity, binary code analysis, and threat intelligence integration with the MITRE ATT&CK framework. Awards highlight his teaching excellence (2013) and contributions to applied security research. His lab collaborates on projects like Confidential Computing and Federated Learning for Smart Vehicles , addressing emerging security challenges in distributed systems.

Henri CasanovaView profile

Professor

• High Performance Computing
• Parallel and Distributed Systems
• Workflow Management Systems
• +4 more

Henri Casanova is a Professor in the Information & Computer Sciences Department at the University of Hawaiʻi at Mānoa. His research focuses on High Performance Computing (HPC), including workflow management systems, distributed application simulation, and HPC storage systems. He teaches courses such as ICS 312 (Machine-Level and Systems Programming) and contributes to the development of tools like SimGrid and WRENCH for enabling scalable workflow research. Education and Affiliations: PhD in Computer Science (implied by academic rank and publications) Member of the HPC and distributed systems research community Research Interests: Casanova’s work bridges theoretical HPC concepts with practical implementations. He emphasizes workflow automation, simulator development (e.g., SimGrid for distributed systems), and energy-aware scheduling. His research addresses challenges in large-scale data management, fault tolerance, and resource optimization across HPC, cloud, and cyberinfrastructure platforms. Publications: Recent work includes advancements in workflow benchmarking (WfBench), automated workflow generator tools (WfChef), and simulation-driven scheduling methodologies. His articles frequently explore scalability, reproducibility, and interdisciplinary applications of HPC frameworks. Awards and Recognition: While no specific awards are listed, his extensive contributions to workflow and simulation tools reflect community impact. Grants and Collaborations: Involved in NSF-funded projects (e.g., CyberTraining) and collaborates with institutions like INRIA (France) on tools like SMPI and WRENCH. Labs and Teams: Leads or contributes to research groups focused on distributed systems simulation, workflow automation, and HPC infrastructure optimization at the University of Hawaiʻi.

Weija ShangView profile

Professor

• Parallel Processing
• Computer Architecture
• Parallelizing Compiler
• +7 more

Weija Shang is a Professor at the School of Engineering, Santa Clara University, where she has been since 1994. She previously served at the Center for Advanced Computer Studies, University of SW Louisiana (1990–1993). Her research spans parallel processing, computer architecture, parallelizing compilers, algorithm theory, and non-linear optimization. PhD in Computer Engineering, Purdue University (1990) MS in Computer Engineering, Purdue University (1984) BS in Computer Engineering, Changsha Institute of Technology (1982) Her publications focus on parallel computing , GPGPU optimization , FPGA design , and video coding techniques. Key themes include supernode transformations , media distribution algorithms , and stack optimization in recursive programs. Scientific awards include: Clare Boothe Luce Professor (1994–2000) NSF Research Initiation Award (1991) NSF Career Award (1995) She has supervised numerous research projects in parallel programming and compiler design, contributing to high-performance computing and distributed systems through collaborations with institutions like Xilinx and NASA.