Find Academic Supervisors

• Algorithms
• Big data analytics
• Blockchain
• +12 more

Dr. Wojciech Golab is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on distributed systems, concurrency control, and persistent memory algorithms. He has received recognition for his work on shared memory algorithms from ACM Computing Reviews. His academic career includes teaching courses like ECE 252, ECE 356, and ECE 454 in the past five years. Education: PhD in Computer Science, University of Toronto (2010) M.Math in Computer Science, University of Waterloo (2004) BSc in Computer Science, University of Toronto (2002) Dr. Golab's research interests span algorithms, blockchain, distributed systems, fault tolerance, and scalable storage solutions. His work emphasizes practical applications of theoretical computer science, such as optimizing transaction processing and ensuring consistency in distributed environments. His recent publications explore topics like detectable synchronization objects for persistent memory, blockchain sharding protocols, and efficient mutual exclusion algorithms under system failures. These contributions highlight advancements in both theoretical foundations and real-world distributed system design. Awards: ACM Computing Reviews 'Notable Computing Items' recognition (2012) Dr. Golab has collaborated with industry partners like Hewlett-Packard Labs, Google, and Cisco to advance research in distributed computing and cloud systems. He currently oversees graduate studies in his department and welcomes applications from prospective students.

• Computer Architecture
• High-Performance Computing (HPC)
• Cloud Computing
• +4 more

Prof. Weikuan Yu is a Professor in the Department of Computer Science at Florida State University. His research focuses on computer architecture, high-performance computing (HPC), cloud computing, parallel file systems, and deep learning applications. He holds the role of Chair and can be contacted via yuw@cs.fsu.edu or (850) 644-5442. His expertise includes optimizing storage systems and I/O behaviors in scientific workflows, developing scalable distributed systems, and applying machine learning to improve computational efficiency. Notable projects include work on burst buffer systems (e.g., BurstFS, TRIO), persistent memory management (PHAST), and distributed deep learning frameworks (e.g., compression techniques for time-evolutionary data). Recent research trends emphasize enhancing HPC storage efficiency through novel file systems and I/O emulation, as well as leveraging machine learning for fault tolerance and configuration tuning. His work bridges hardware-software co-design to address challenges in exascale computing and big data analytics. Prof. Yu has contributed to multiple open-source projects and frameworks, including OpenSHMEM-based key-value stores and MapReduce optimizations. His publications highlight advancements in parallel processing, distributed algorithms, and energy-efficient memory architectures.

Hartwig AnztView profile

Associate Professor

• Algorithm Engineering
• High Performance Computing
• Numerical Linear Algebra
• +3 more

Hartwig Anzt is a Research Associate Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, and Director of the Innovative Computing Lab (ICL). He holds a Senior Research Scientist position at the Steinbuch Centre for Computing at Karlsruhe Institute of Technology (KIT), where he previously held an Early Career Award and a Junior Professorship. He earned a Diploma in Industrial Mathematics (2009) and a PhD in Applied Mathematics (2012) from KIT, with a year of studies at the University of Ottawa. His research focuses on algorithm engineering for computational mathematics, particularly numerical linear algebra, GPU computing, and mixed-precision methods. Key areas include asynchronous algorithms, communication-avoiding techniques, and sustainable software engineering for exascale computing. He leads development of the Ginkgo library, designed for high-performance numerical linear algebra on heterogeneous architectures. Anzt's work emphasizes practical software solutions for scientific computing, including sparse linear algebra, batched solvers, and FAIR-compliant research software practices. His contributions span fusion plasma simulations, cardiac electromechanics, and scalable data compression techniques for extreme-scale systems. Education: Diploma (2009), PhD (2012) in Applied Mathematics from KIT Key Roles: ICL Director, xSDK Multiprecision Project Lead Software Contributions: Ginkgo Library, JuMonC Tool, Compressed Basis GMRES

Ali HursonView profile

Professor

• High-performance computing
• Pervasive computing
• Mobile databases
• +11 more

Dr. Ali Hurson is a Professor in the Department of Electrical and Computer Engineering at Missouri University of Science and Technology. His research spans high-performance computing, pervasive computing, mobile databases, personalized education, intelligent transportation systems, and cyber-physical systems. PhD, Computer Science, University of Central Florida MS, Computer Science, University of Iowa BS, Physics, University of Tehran Dr. Hurson’s research focuses on mobile data access systems, cybersecurity for critical infrastructure, and educational technologies. His work addresses challenges in data dissemination, power management, and fault propagation in heterogeneous systems. His recent publications emphasize agent-based modeling for cyber attacks, predictive analytics in education, and fault tolerance in cyber-physical systems. Trends include integration of machine learning, security frameworks, and sustainable computing. Editor-in-Chief, Advances in Computers Editor-in-Chief, Journal of Sustainable Computing and Communication Dr. Hurson has secured over $3 million in grants from NSF, DOE, DOT, and industry partners. He has held academic roles at Penn State University and the University of Oklahoma, transitioning to Missouri S&T in 2007.

Juraj ŠtefanovičView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Medical Data Processing
• +3 more

Juraj Štefanovič is an Associate Professor and Head of the Institute of Applied Informatics at the Pan-European University . He specializes in Modeling and Simulation , Operating Systems , and interdisciplinary applications of AI in medical data processing and education. Teaches Discrete Dynamic Systems , Parallel Programming , and Usability in User Interfaces . Coordinated international research projects ACCREDIT (2017-2019) and EWA (2020-2023). Executive editor of the ITA professional magazine. Manages a Lego Robot Laboratory for secondary/elementary school outreach. Research Trends : Combines AI with medical diagnostics, system modeling, and educational robotics. Recent work focuses on neurodegenerative disease detection and Industry 4.0. Publications : Span textbooks (Operating Systems) and conference papers on simulation, cybernetics, and testing methodologies. Labs & Teams : Organizes the FIRST Lego League regional tournament for Bratislava and Western Slovakia.

• Numerical Linear Algebra
• Model Order Reduction
• Matrix Equations
• +5 more

Dr. Jens Saak is a leading researcher and team leader at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. He heads the Computational Methods in Systems and Control Theory research group and has held several leadership positions at the institute since 2010, including Head of the Scientific Computing Team (2010-2020), Head of the Matrix Equations Team (2013-2020), and currently serves as Head of the Data, Infrastructure, Software & Computing Team since 2021. Dr. Saak earned his undergraduate degree in Technomathematik from the University of Bremen (1996-2003), completed his PhD at TU Chemnitz (2003-2009), and held a postdoctoral position there (2009-2010) before joining the Max Planck Institute. His research spans computational mathematics with a focus on large-scale sparse matrix equations , model order reduction , and optimal control of complex systems. He specializes in developing efficient numerical algorithms for Lyapunov and Riccati equations, with applications in mechanical engineering (particularly machine tools), fluid dynamics, and thermal systems. His work bridges theoretical numerical analysis with practical high-performance computing implementations. Analysis of his recent publications reveals a clear trajectory toward energy-efficient computing solutions, sustainable research software practices, and increasingly sophisticated model reduction techniques for complex coupled systems. His work demonstrates a strong emphasis on practical implementations with industrial applications, particularly in mechanical engineering contexts. Dr. Saak has been instrumental in developing and maintaining research software infrastructure, with a growing focus on sustainability and reproducibility in computational science. His leadership extends to collaborative projects across the German mathematical community, particularly in research data management initiatives. His team actively contributes to open-source scientific computing tools, with significant work on the M-M.E.S.S. (Matrix Equations, Sparse Solvers) toolbox, which provides implementations of modern algorithms for matrix equations and model order reduction.

Thomas ZeiserView profile

Researcher

• High-Performance Computing
• Lattice Boltzmann Methods
• Computational Fluid Dynamics
• +3 more

Dr. Thomas Zeiser serves as Head of Systems & Services and Chief Operating Officer HPC at NHR@FAU (Center for National High Performance Computing Erlangen) at Friedrich Alexander University Erlangen-Nuremberg. He leads the Systems & Services group of NHR@FAU and HPC4FAU since the end of 2020 and serves as deputy for NHR@FAU in the NHR Betreiberausschuss. His work focuses on transitioning from serving FAU only to national center operations, managing HPC systems, procuring new infrastructure, financial controlling of NHR@FAU's budgets, and supporting planning for a new data center building. Dr. Zeiser's research interests center around High-Performance Computing with specific expertise in Lattice Boltzmann Methods , large-scale simulations, evaluation of HPC hardware and software, and efficient operation of HPC systems. His work bridges the gap between theoretical computational methods and practical implementation in high-performance environments. He has implemented the first job-based job and performance monitoring for RRZE's HPC systems and has extensive experience in procurement of HPC infrastructure. Analysis of Dr. Zeiser's publication record reveals a consistent focus on practical applications of computational methods in HPC environments. His research demonstrates a progression from fundamental lattice Boltzmann method development toward increasingly complex system-level concerns including fault tolerance, performance monitoring, energy efficiency, and scalable implementations. The publications show strong collaboration patterns with researchers at FAU and other German institutions, particularly in the areas of computational fluid dynamics and parallel computing. Dr. Zeiser regularly serves as a reviewer for various journals and compute time commissions of different HPC centers. He is also one of the local organizers for the Ferienakademie of TUM, FAU, and Universität Stuttgart held in Sarntal. His work with NHR@FAU positions him at the forefront of national high-performance computing infrastructure in Germany. At NHR@FAU and RRZE (Regional Computing Center Erlangen), Dr. Zeiser leads teams responsible for operating some of Germany's most powerful academic supercomputing resources. His group plays a critical role in supporting computational research across multiple disciplines at FAU and increasingly at the national level through the NHR initiative.

• Operating systems
• Distributed systems
• Computer Science
• +3 more

Professor Willy Zwaenepoel is a distinguished academic and Dean of the Faculty of Engineering at the University of Sydney. He holds Fellowships from ACM, IEEE, and ATSE. His research focuses on distributed systems, operating systems, and experimental computer science. Previously, he spent two decades at Rice University and nine years as Dean of EPFL's School of Computer and Communication Sciences before joining Sydney in 2018. Education: BS/MS, Ghent University (1979) MS/PhD, Stanford University (1980/1984) Research Interests: His work emphasizes distributed systems and operating systems, with contributions to key-value stores, transactional systems, and large-scale graph processing. Recent projects include optimizing geo-replicated systems and improving datacenter scheduling efficiency. Articles Trends: Recent publications address OS scheduling (Nest), distributed graph mining (Tesseract), and transactional systems' performance limits. He explores hardware-software co-design for multicore systems and energy-efficient data centers. Awards: Fellow of ACM (2021) Fellow of IEEE (2020) Fellow of ATSE (2019) Grants & Advising: Active grants include adaptive key-value store research (2021) and large-graph processing systems (2018). He advises PhD students and postdocs on distributed systems and storage challenges. Labs/Teams: Leads the Sydney systems research group focusing on scalable distributed systems and cloud infrastructure.

Tianyin XuView profile

Assistant Professor

• Programming Languages
• Formal Methods
• Software Engineering
• +3 more

Tianyin Xu is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), with a courtesy appointment in the Department of Electrical and Computer Engineering (ECE). His research focuses on ensuring reliability and security in large-scale cloud and datacenter systems, with particular emphasis on configuration management, system verification, and distributed system resilience. He has held positions including a year at Facebook's Core Systems and completed his PhD at the University of California San Diego. Dr. Xu teaches courses such as CS 598(XU) on Cloud-Scale System Reliability, CS 523 (Advanced Operating Systems), and CS 423 (Operating Systems Design). He actively contributes to academic communities through roles like co-editing the SIGOPS Blog, serving on program committees for conferences like NSDI, OSDI, and EuroSys, and organizing the UIUC Systems Research Seminar. His research has been recognized with awards including the 2025 Best Paper Award at ASPLOS, 2024 Jay Lepreau Best Paper Award, and NSF CAREER Award. His work has led to impactful contributions like the Sieve framework for testing configuration changes and the Rex tool for kernel extension safety. Dr. Xu advises a vibrant group of students and collaborates with industry partners including VMware, IBM, and Intel. His lab focuses on advancing system reliability through innovative tools and methodologies.

Isobel TaylorView profile

Research Fellow

• Securities Law
• Litigation Analytics
• Financial Regulation
• +3 more

Isobel Taylor serves as an Empirical Research Fellow at Stanford Law School, where she contributes to the Stanford Securities Litigation Analytics (SSLA) project. This initiative systematically tracks federal securities class actions and SEC enforcement proceedings involving alleged material misstatements affecting corporate valuations, with data collection spanning over 3,000 cases filed since 2000. Her research focuses on empirical analysis of litigation patterns, including settlement dynamics, case duration variables, and the impact of external factors like parallel enforcement actions or bankruptcy proceedings. The SSLA framework enables granular analysis of market-cap segmentation, allegation types, and resolution outcomes through its 40+ dimensional query system, supporting data-driven approaches to legal risk assessment. Funded through licensing agreements with D&O insurers, law firms, and institutional investors, the SSLA project maintains a team of full-time analysts who compile 1,000+ data points per case from court documents, financial disclosures, and attorney interviews. Recent developments include an interactive web platform launched in 2025 featuring real-time litigation dashboards for cases like Spirit Aviation Holdings (filed 09/30/2025) and settlement analytics for biotech sector disputes, alongside Wall Street Journal-featured research on IPO litigation risks.

Dong DaiView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• High-Performance Computing
• +5 more

Dong Dai is an Associate Professor at the University of Delaware in the Department of Computer and Information Sciences under the College of Engineering. He directs the Data Intelligence Research Lab (DIRLab) , focusing on optimizing intelligent infrastructure for high-performance, data-intensive systems using machine learning techniques. Research Interests : Artificial Intelligence, Machine Learning, High-Performance Computing, Storage Systems, Metadata Management, Graph Storage, Job Scheduling Education : PhD and BSc from the University of Science and Technology of China Grants : CCF-EAGER, CNS, CCF-Hybrid NVM, CCF-Parallel Graph-Based Paradigm, OAC-Provenance Collection Teaching : Courses include CISC 361 Operating Systems , CISC 360 Computer Architecture , ITCS 5145 Parallel Computing , and ITSC 3050 Undergraduate Research .

• Bioinformatics
• DNA Sequencing
• Genomics
• +3 more

Dries Decap is a postdoctoral researcher at the Faculty of Engineering and Architecture, Ghent University, within the Department of Information Technology (INTEC). His work focuses on bioinformatics, DNA sequencing, and computational biology with applications in genomics and high-performance computing. Research Interests: Dr. Decap specializes in developing scalable bioinformatics frameworks for DNA and RNA sequencing analysis, including tools like elPrep and Halvade . His research spans variant calling, motif discovery, and parallel computing implementations. Projects: He led his doctoral project (2011-2017) on "Doctoral project Dries Decap" under supervisors Bart Dhoedt and Jan Fostier. He also contributed to projects like IAMBEE for adaptive pathway analysis and BLSSpeller for regulatory motif discovery. Collaborations: Collaborators include Kathleen Marchal, Charlotte Herzeel, and Pascal Costanza. He has worked with institutions like IMEC and Ghent University on scalable genomic data processing solutions.

Julien ArinoView profile

Professor

• Mathematical Epidemiology
• Mathematical Population Dynamics
• Data Science
• +3 more

Julien Arino is a Professor in the Department of Mathematics at the University of Manitoba , specializing in Mathematical Epidemiology and Mathematical Population Dynamics . He is an active member of the Mathematical Biology group and focuses on the role of movement in disease transmission, with applications to both human and animal health. Department of Mathematics Faculty of Science University of Manitoba His research spans: Metapopulation dynamics with explicit movement Multi-pathogen and multi-species transmission modeling Computational epidemiology with data science integration Evaluation of travel control measures for disease variants Recent work includes publications on: Cholera transmission in Chad Multi-species bovine tuberculosis dynamics Measles resurgence patterns Software tools for R compilation and data visualization He maintains a public YouTube channel with lecture videos on Mathematical Epidemiology and contributes open-source code for scientific computing in R and Python. His methodological contributions include novel approaches to plot formatting and computational efficiency in epidemic modeling.

ATİLLA ERGÜZENView profile

Associate Professor

• Algorithms
• Distributed File Systems
• Parallel Programming
• +1 more

Atilla Ergüzen is an Associate Professor at the Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kırıkkale University. He holds the title of Professor Doctor and currently serves as Head of the Department of Computer Engineering. His academic journey began in 1993 at Kırıkkale Vocational School, where he started as a lecturer. Education: B.Sc. in Computer Engineering from Middle East Technical University (1993), M.Sc. and Ph.D. in Mechanical Engineering from Kırıkkale University Professional Roles: Lecturer (1993–), Assistant Professor (2012–), Associate Professor (2019–), Deputy Director of Kırıkkale University Distance Education Center (2012–2024) His research focuses on algorithms , distributed file systems , parallel programming , and software engineering . He has led the development of over 50 medium/large-scale software projects for public and private institutions, including the Distance Education System that enabled Kırıkkale University to rapidly transition to online education during the pandemic. He has held leadership roles in academic administration and software innovation.

Roberto Di CosmoView profile

Professor

• Theoretical Computing
• Functional Programming
• Parallel and Distributed Programming
• +6 more

Roberto Di Cosmo is a Full Professor of Computer Science at University Paris Diderot since 1999, currently on leave at Inria. He is a prominent researcher and advocate for Free Software, contributing to its adoption since 1998 through seminars, articles, and software. He co-founded the Software Heritage initiative in 2016, aiming to build a universal archive of publicly available source code, and served as director of IRILL, a research structure dedicated to Free and Open Source Software quality, since 2010. His research focuses on theoretical computing, including functional programming, parallel and distributed programming, semantics of programming languages, type systems, rewriting, and linear logic. He has led significant projects like the European Mancoosi research initiative, addressing challenges in static analysis of large software collections. His work with Software Heritage has archived over 3 billion source code files and 700 million commits across 60 million projects. This effort preserves scientific and technological knowledge, enables software reuse, and supports research through a curated archive infrastructure. Roberto Di Cosmo actively bridges academic research with societal impact, emphasizing the role of software in digital culture and advocating for open knowledge sharing.