Find Academic Supervisors

• Artificial Intelligence
• Natural Language Processing
• Knowledge Management
• +7 more

Jorjeta Jetcheva is an Assistant Professor in the Computer Engineering Department at San José State University, part of the Charles W. Davidson College of Engineering. She brings extensive industry experience from leadership roles at Accenture, Fujitsu Laboratories of America, Itron, and Firetide, where she led innovations in AI, smart grids, and wireless networking. Her research focuses on Artificial Intelligence-based Personal Assistants, Natural Language Processing, and Knowledge Management . Her work bridges human-centered AI and enterprise applications, with emphasis on intelligent agents, knowledge platforms, and ethical AI systems. She explores how AI can enhance user productivity, decision-making, and system security across domains such as healthcare, energy, and customer service. The recent publications highlight a strong trend in Natural Language Processing applied to real-world problems like fake health news detection, agent assist systems, and knowledge graph integration. Her research also spans Smart Grid analytics, cybersecurity, and AI ethics , reflecting a multidisciplinary approach grounded in both theoretical rigor and practical deployment. Scientific Awards: Best Application Paper Award at IEEE Big Data Service 2022 Best Paper Award at SmartGridComm 2014 Top 10 Finalist, Fujitsu Next Generation Product Idea Contest 2016 ('Robo Butler') CSU STEM-NET Faculty Fellow (2023) Advising and Grants: Professor Jetcheva is the Principal Investigator of a $2.5 million NSF S-STEM grant titled 'Empowering Students to Succeed in Engineering and Computer Science'. She actively mentors graduate students, including Master’s student Garima Chaphekar, with whom she co-authored an award-winning paper on fake health news detection. She serves on the SJSU AI Advisory Committee and leads the AI Research Cluster, fostering interdisciplinary collaboration and student success. Labs and Teams: She leads the AI Research Cluster at SJSU, promoting innovation in artificial intelligence across departments. Her work involves close collaboration with students, industry partners, and interdisciplinary teams focused on deploying scalable, ethical AI solutions.

• Cloud Computing
• Educational Technology
• Computer Networks
• +4 more

Sławomir Zieliński is a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków. His academic role involves teaching and research focused on cloud technologies and educational informatics. He maintains an office at D-17, ul. Kawiory 21, and can be contacted via email at slawek@agh.edu.pl or phone at +48 12 328 33 77. Zieliński's research explores intersections between cloud computing and educational technology, particularly: Cloud-native applications and serverless architectures for environmental monitoring Automated orchestration of educational services in cloud environments IoT-enhanced collaborative learning platforms Software-defined networking optimizations Remote teaching methodologies and pandemic-responsive education systems Performance evaluation frameworks for distributed systems His work demonstrates consistent innovation in adapting cloud infrastructure to educational challenges. Recent publications (2015-2024) reveal strong thematic focus on cloud-based educational technologies, distributed systems optimization, and pandemic-era teaching solutions. Dominant research threads include: Cloud infrastructure for remote education (6+ publications) Performance evaluation methodologies for networks and cloud services (4 publications) IoT integration in educational ecosystems (3 publications) Serverless computing applications in environmental systems

• Chaos Engineering
• Software Engineering
• Distributed Systems
• +3 more

Javier Ron Arteaga is a doctoral student and researcher at KTH Royal Institute of Technology, Sweden, affiliated with the Department of Theoretical Computer Science. He is funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP) and supervised by Martin Monperrus and Benoit Baudry. Education: B.Sc. in Computer Science from ESPOL University (Ecuador), M.Sc. in Software Engineering of Distributed Systems from KTH. Teaching: Assistant in courses such as Automated Software Testing and DevOps (DD2482), Operating Systems (ID1200, ID1206), Scalable Machine Learning and Deep Learning (ID2223), and Software Engineering Fundamentals (DD2480). His research focuses on applying chaos engineering principles across diverse software layers and application domains. This involves identifying and applying domain-specific and layer-specific perturbation models to analyze runtime environments and software architectures for insights into their strengths and weaknesses. He is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) Fellowship. His studies contribute to the field of computer science through innovative approaches to runtime system resilience and architectural analysis.

Dragos TruscanView profile

Professor

• Software Testing
• Model-Based Testing
• AI in Test Automation
• +7 more

Prof. Dragos Truscan is a Professor of Computer Science at the Faculty of Natural Sciences and Engineering within Åbo Akademi University , focusing on Information Technology and Mission Critical Software Systems . Research interests include validation and verification , automated test generation using model-based technology and AI , test left-shifting , and runtime monitoring of industrial software systems Active in Security Requirements Engineering , DevOps , Deep Learning , and Software Component analysis Recent work explores: 2025 - Reinforcement learning for security testing and visual fault localization 2024 - Explainability in network attack detection and hyperparameter optimization 2023-2024 - Model-based requirements engineering in large collaborative projects Scientific Recognition Best Paper Award (2024) Best Paper Award (2013) Academic Activities Organizing member of IEEE International Conference on Software Services Engineering (2025) Hosted scholars like Victoria Zsók and Dr. Dumitru Iulian Nastac

• Software Engineering
• Computer Science
• Microengineering
• +3 more

Eric Silva is a Lecturer at the Swiss Federal Institute of Technology Lausanne (EPFL), affiliated with the School of Engineering. His teaching focuses on software architecture, covering agile project management, design patterns, robust code development, and DevOps practices such as automation of testing and continuous integration/deployment. Research and Teaching Interests Software Engineering Computer Science Microengineering DevOps Agile Project Management Design Patterns

Lisovenko Iryna DmytrivnaView profile

Assistant Professor

• Parallel and Distributed Computing
• GPU Computing
• Automatic Program Parallelization
• +3 more

Lisovenko Iryna Dmytrivna serves as Assistant Professor in the Department of Computer Systems and Networks at Yuriy Fedkovych Chernivtsi National University since 2002, following her 2000 diploma in Computer Systems and Networks from the same institution. Her professional trajectory includes software engineering at a municipal medical institution (2000–2002) and ongoing contractual collaboration with Elogic Commerce since 2018. Her academic credentials include: Yuriy Fedkovych Chernivtsi State University, Faculty of Physics, Department of Computer Science, specialty "Computer Systems and Networks" (2000) Dr. Lisovenko's research centers on parallel and distributed computing, emphasizing automatic parallelization techniques, GPU-accelerated non-graphical computing, and structural analysis of program intermediate representations. She concurrently investigates specialized computer systems for data stream processing and develops methodologies for enterprise accounting automation, bridging theoretical computer science with business process optimization. Her scholarly output demonstrates sustained innovation in high-performance computing architectures. Analysis of her 15 most recent publications (2012–2021) reveals three dominant research thrusts: GPU-based parallelization (40% of works, including Kalyna encryption and bitonic sorting implementations), algorithmic optimization for diverse hardware (33%, covering sorting networks and structural matrices), and applied systems for real-world problems (27%, spanning smart home control, social media analysis, and enterprise automation). This evolution reflects increasing focus on practical GPU applications while maintaining core expertise in parallel algorithm design. She actively contributes to academic development through teaching Parallel and Distributed Computing, Economic and Legal Aspects of Enterprise Automation, and DevOps/DevNet courses, while authoring 12+ methodological manuals including "Parallel and Distributed Computing: Laboratory Workshop" (2022) and "System Administration of Linux OS" (2021). Her professional development includes certifications in Constitutional Law, Finance and Investment, DevNet Associate, and All Digital Week initiatives (2020–2021).

Frank LeymannView profile

Professor

• Quantum Computing
• Cloud Computing
• Service-Oriented Architecture
• +7 more

Frank Leymann is a Professor at the Institute for Architecture of Application Systems, University of Stuttgart. His research spans quantum computing, cloud systems, middleware, and business process management. Affiliation: University of Stuttgart, Institute for Architecture of Application Systems Key Projects: PlanQK, EniQmA, OpenTOSCA, SeQuenC Academic Recognition: Over 30 years of publications in service computing and quantum technologies Research Interests: His work focuses on quantum software engineering , hybrid quantum-classical systems , and cloud application architectures . Notable contributions include TOSCA standardization for cloud deployment and systematic studies on quantum optimization. Recent Publications: 2025-2024 articles emphasize quantum algorithm expressivity , cross-chain blockchain transactions , and post-quantum security . Earlier works (2023-2021) address quantum workflow provenance , QAOA optimization , and IoT platform architectures . Technical Leadership: Director of a multidisciplinary team developing frameworks like OpenTOSCA and tools for quantum application deployment.

• Network Architectures
• Network Protocols
• Information Security and Assurance
• +4 more

Sonia Fahmy is a Professor and Associate Department Head in the Department of Computer Science at Purdue University. She joined Purdue in 1999 and was recently elevated to IEEE Fellow status. Fahmy is a member of CERIAS (Center for Education and Research in Information Assurance and Security) and has made significant contributions to network architectures and protocols research. Research Interests: Design and evaluation of network architectures and protocols Network support for virtual reality applications Network measurement and management Cellular networks optimization and security Network experimentation methodologies Professor Fahmy's research has evolved to address emerging challenges in networking, with recent work focusing on virtual reality networking, 5G security, and quality-of-experience optimization. Her publications reveal a consistent trajectory from fundamental network protocol design toward addressing the specific requirements of modern applications like VR and volumetric video streaming. Scientific Awards: IEEE Fellow National Science Foundation CAREER Award (2003) Professor Fahmy has successfully mentored numerous PhD students who have gone on to careers at leading technology companies and academic institutions. Her research has been supported by substantial funding from the National Science Foundation, Department of Homeland Security, and industry partners including Cisco, Meta, Juniper Networks, and AT&T. She leads several active research projects including network support for virtual reality applications (NSF and Meta projects), network measurement and management (Juniper Networks and GENI Project), cellular networks security (NSF projects), and network experimentation (DHS and NSF projects).

Mattia FazziniView profile

Assistant Professor

• Software Engineering
• Software Testing
• Software Maintenance
• +5 more

Mattia Fazzini is an Assistant Professor in the Department of Computer Science & Engineering at the University of Minnesota's College of Science and Engineering. His primary academic appointment focuses on software engineering research and teaching, with active involvement in major conferences including ASE, ISSTA, ICSE, and MOBILESoft where he has served in leadership roles such as General Co-chair (MOBILESoft 2023) and Program Committee Co-chair. His research centers on software testing, maintenance, and security , with particular emphasis on mobile applications. Key research themes include: Developing techniques for automated Android testing and maintenance Addressing API compatibility issues across Android versions Creating tools for test oracle generation and bug reproduction Investigating security vulnerabilities in mobile ecosystems Optimizing test suites through test double analysis His recent publications (2021-2025) reveal strong focus on Android-specific challenges, with recurring themes in compatibility testing, automated test generation, and security analysis. Over 60% of his work involves tool development for practical testing scenarios, particularly targeting mobile platforms. Notable recognitions include: IEEE TCSE Distinguished Paper Award (2024) for work on test suite optimization ACM Distinguished Paper Award (2022) for COVID-19 app analysis As an educator, he advises multiple PhD and Master's students while teaching undergraduate and graduate courses including CSCI 3081W (Program Design) and CSCI 5802 (Software Engineering II). His service contributions span conference organization (MOBILESoft, ISSTA, ICSE) and extensive program committee work across top software engineering venues. He leads research projects focused on practical testing solutions with real-world applicability in mobile software development.

Xiaoyin WangView profile

Associate Professor

• Software Testing and Analysis
• Software Privacy
• Program Analysis
• +3 more

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, specializing in software testing, privacy, and program analysis. Her research focuses on enhancing software quality through innovative approaches to build systems, virtual reality testing, and privacy policy enforcement. She earned her PhD from Peking University in 2012 and completed postdoctoral work at UC Berkeley. Her research interests span Software Testing and Analysis , Software Privacy , Build Systems , and Virtual Reality Testing . She develops techniques for detecting privacy leaks in mobile apps, optimizing build scripts, and testing immersive applications. Her work bridges program analysis with practical software engineering challenges, particularly in security-critical contexts. Recent publications reveal strong trends in Virtual Reality testing frameworks (e.g., VRGuide, VRTest), automated build diagnostics (PExReport, HireBuild), and privacy policy verification (GUILeak, DAISY). Her research increasingly integrates machine learning for bug prediction and test oracle generation, with significant contributions to augmented reality testing and cross-project compatibility analysis. President's Research Achievement Award (UTSA, 2019) NSF CAREER Award (2019) for build script analysis Distinguished PhD Dissertation Awards from CCF (2013) and Peking University (2012) MSRA Fellowship (2009) Wang actively advises PhD students including Rodney Rodriguez (defended 2022, now at Accenture) and Xueling Zhang (defended 2021, now Assistant Professor at RIT). She leads NSF-funded projects including CAREER: Analysis and Repair of Build Scripts for DevOps and EAGER: Tracing Privacy-Policy Statements into Code . Her service includes chairing ICSE 2019 proceedings and serving on ASE/ICSE/ISSTA program committees. Current work focuses on security analysis for AR applications and automated privacy compliance verification.

Leopoldo TeixeiraView profile

Assistant Professor

• Software Engineering
• Refactoring
• Formal Methods
• +6 more

Leopoldo Teixeira is an Assistant Professor at the Informatics Center (CIn) of the Federal University of Pernambuco (UFPE) in Brazil. Since May 2023, he has served as Head of Graduate Studies at his department. He leads the Software Testing and Analysis Research group and is affiliated with the Software Productivity Group and CIn-Trust. Dr. Teixeira was a CAPES-Alexander von Humboldt Experienced Research Fellow at the Chair of Software Engineering of Universität des Saarlandes in 2022, where he collaborated with Sven Apel on variability analysis over time and space. His educational background includes: PhD in Computer Science from Federal University of Pernambuco (CIn-UFPE, 2014), supervised by Paulo Borba and Rohit Gheyi MSc in Computer Science from CIn-UFPE (2010) Bachelor's degree in Computer Engineering from the Polytechnic School of Pernambuco (2007) Dr. Teixeira's research focuses on providing strong foundations for improving software quality and productivity. His work spans software product lines, configurable systems, refactoring, formal methods, software testing, and mobile development. He has made significant contributions to understanding challenges in highly configurable systems and software evolution, with particular emphasis on theoretical rigor combined with practical applicability. His publication record demonstrates expertise across software testing methodologies, analysis of configurable systems, and formal verification techniques. Recent work addresses pressing challenges in containerization practices (Dockerfile repair), test reliability (flaky test detection), and formal specification of API properties, showing his ability to tackle both theoretical and practical aspects of software engineering. Dr. Teixeira has received recognition through the CAPES-Alexander von Humboldt Experienced Research Fellowship. CAPES-Alexander von Humboldt Experienced Research Fellow (2022) Dr. Teixeira actively contributes to the software engineering community through extensive service on program committees of major conferences including ICSE, FSE, ASE, and SPLASH across multiple years. In 2024, he served as Conference and Local Organization Chair for FSE. He mentors students through his leadership of the Software Testing and Analysis Research group at CIn-UFPE. His laboratory work focuses on software testing and analysis, particularly in the context of configurable systems and software product lines. The research group investigates practical approaches to improve software quality through better testing methodologies, analysis techniques, and formal verification approaches for complex software systems.

Anil MadhavapeddyView profile

Professor

• Planetary Computing
• Computer Systems
• Programming Languages
• +7 more

Anil Madhavapeddy is the Professor of Planetary Computing at the University of Cambridge Computer Laboratory, where he co-leads the Energy & Environment Group and is a member of the Systems Research Group. He is also a Fellow at Pembroke College where he serves as Director of Studies in Computer Science. Madhavapeddy completed his PhD from the University of Cambridge in 2003 and his BEng in Information Systems Engineering from Imperial College in 1999. He holds a JM Keynes Fellowship since 2022 for his work combining computer science with economics, and serves on the management committee of the Cambridge Conservation Initiative where he co-directs 4C (Cambridge Centre for Carbon Credits) and the Centre for Earth Observation. His research spans computer systems and programming languages with a strong focus on applying these technologies to global conservation, biodiversity, and climate change challenges. He leads the OCaml Labs group and has made significant contributions to open-source projects including OCaml, Docker, Xen, and OpenBSD. His work often bridges computer science with environmental science, developing computational approaches to address planetary-scale challenges. Madhavapeddy's recent publications demonstrate a clear trajectory toward integrating programming language research with environmental monitoring and conservation. His work spans from foundational programming language techniques to applied geospatial computing systems, with increasing emphasis on biodiversity measurement, carbon credit systems, and planetary-scale environmental monitoring. JM Keynes Fellowship (2022-present) As an educator, Madhavapeddy teaches undergraduate courses including Foundations of Computer Science, Software & Security Engineering, and Cloud Computing. He mentors MPhil and PhD students and co-founded the award-winning book 'Real World OCaml' (2nd Edition, 2022). He has co-founded several companies including Unikernel Systems, High Energy Magic, Segfault, and Tarides to translate research into real-world impact. Madhavapeddy leads the OCaml Labs group at Cambridge and works closely with the Energy & Environment Group, collaborating with colleagues from Plant Sciences, Zoology, Economics, and NGOs including UNEP-WCMC and the IUCN. His current efforts are primarily focused on conservation technology through partnerships with organizations like Canopy PACT.

Mustafa ULAŞView profile

Assistant Professor

• Data Mining
• Big Data
• Machine Learning
• +7 more

Mustafa ULAŞ is an Assistant Professor in the Software Engineering Department at Fırat University, Turkey. He also serves as a University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since October 2020. With academic roots entirely at Fırat University, he has established himself as a prominent researcher in data science and software engineering. Born in November 1981 in Elazığ, Turkey PhD in Electrical-Electronics Engineering (2011) Master's in Computer Engineering (2006) Bachelor's in Electrical-Electronics Engineering (2003) Dr. ULAŞ's research spans multiple domains of computer science and engineering with particular emphasis on practical applications. His work bridges theoretical computer science with real-world problems in healthcare, finance, and industrial systems. Recent publications reveal a strong focus on machine learning applications, especially in medical diagnostics and explainable AI, while maintaining his longstanding interest in VLF signal analysis for earthquake prediction. His publication record shows a clear evolution from foundational work in database systems and medical imaging to cutting-edge research in deep learning and explainable AI. The most recent articles (2024-2025) predominantly focus on healthcare applications of machine learning, particularly diabetes and cancer diagnosis, while maintaining parallel research streams in industrial applications, financial analytics, and drone network optimization. This multidisciplinary approach demonstrates his ability to adapt core computational techniques to diverse problem domains. Dr. ULAŞ has been actively involved in numerous research projects, including TÜBİTAK-funded initiatives such as the 'Enriched Virtual Laboratory' and 'A New Approach in Teacher Education: Effective Blended Learning.' His project portfolio spans infrastructure development, educational technology, and advanced research applications. As an educator, he teaches courses including C Programming and Algorithms, Internet-Based Programming, Server Operating Systems, and Web Project Management. His administrative roles include serving as University Advisor and Coordinator of the Digital Transformation and Software Office at Fırat University since 2020.

• Data-Intensive Systems
• Machine Learning
• Concept Drift
• +3 more

J.S. Rellermeyer is a Professor at Delft University of Technology's College of Electrical Engineering, Mathematics and Computer Science , specializing in Data-Intensive Systems . His work bridges software engineering, machine learning, and distributed systems to address challenges in AI reliability and sustainability.

Muhammad Ali BabarView profile

Professor

• Software Security & Privacy
• Big Data Platforms & Architectures
• Empirical Software Engineering
• +6 more

Muhammad Ali Babar is a Professor in the School of Computer Science at the University of Adelaide. He leads a theme on architecture and platform for security as service in the CyberSecurity Cooperative Research Centre (CSCRC), which has an estimated budget of A$140 Millions over 7 years with A$50 Millions provided by the Australian government. Prof Babar has established CREST (Centre for Research on Engineering Software Technologies), directing the research, education, and engineering activities of more than 25 researchers and engineers. He has attracted more than $12 Millions in funding from industry and government since 2017. Prof Babar's research focuses on Secure Software Systems and Services for emerging technologies including Cloud Computing, Edge Computing, Internet of Things (IoT), and Big Data. His work sits at the intersection of Software Engineering, Artificial Intelligence (ML/NLP), and Cyber Security, employing empirical research methods both qualitative and quantitative. His recent publications demonstrate a strong emphasis on vulnerability prediction, secure microservices management, and applying large language models to security challenges. With over 320 peer-reviewed scientific papers and 17,763 citations (h-index 66 as of January 2025), Prof Babar ranks among the leading Software Engineering researchers in Australia and New Zealand. His research has been recognized with the most influential paper award for the Australasian Software Engineering Conference in 2014 and multiple best paper awards at international conferences. Most influential paper for Australasian Software Engineering Conference (2014) Multiple best paper awards at international conferences Prof Babar obtained his Ph.D. in Computer Science and Engineering from the University of New South Wales, Australia. His research is conducted in collaboration with industry and government partners including DST, ActewAGL, TSS, ATO, Jemena, Cisco, DST Group, Health SA, and Defence SA, as well as key players in the Australian Cyber Security ecosystem such as AustCyber, Data61, DST Group, Oceania Cyber Security Centre, and Australian Cyber Collaboration Centre (AC3). Prof Babar is eligible to supervise Masters and PhD students and has led high-performing R&D teams that have successfully carried out high-quality research in close collaboration with industry. His leadership in the Cyber Security Cooperative Research Centre represents a significant contribution to Australia's cyber security research capabilities and industry engagement.