Find Academic Supervisors

Tushar SharmaView profile

Assistant Professor

• Software Engineering
• Machine Learning
• Code Quality
• +7 more

Tushar Sharma is an Assistant Professor at the Faculty of Computer Science, Dalhousie University, Canada. His research focuses on software code quality , refactoring , sustainable AI , and machine learning for software engineering (ML4SE) . He holds a PhD in Software Engineering from Athens University of Economics and Business (2019) and an MS in Computer Science from IIT-Madras (India). Current affiliations: Dalhousie University, SMART Lab, IEEE Senior Member Past experience: Siemens Research (2019-2021), Siemens Corporate Technology (2008-2015) Research interests span code quality assessment, technical debt management, and sustainable AI. He founded Designite , a widely used software design quality assessment tool, and contributed to the book Refactoring for Software Design Smells . Recent work examines energy-efficient language models for code, reproducibility issues in configuration scripts, and human-guided code smell detection. Publication trends reveal expertise in code smell detection, refactoring techniques, and green AI. His articles address topics like commit message generation, model quantization, and empirical studies on code quality. Collaborative efforts include tools like DesigniteJava 2.0 and frameworks for attention mechanisms in code language models. Scientific recognition: Dean's Research Excellence Award (2025), Best Artifact Award (SCAM 2023) Grants: Mitacs Accelerate grants ($225K, $15K, $30K), NSERC Discovery Grant ($154M CFREF climate action project), DRA computing resources ($51K) He actively contributes to academic service as PC Co-chair (ICSE 2024), editorial board member (JSS), and organizer of workshops on technical debt. His media coverage highlights environmental impacts of AI and software quality challenges.

Gemma CatolinoView profile

Assistant Professor

• Software Engineering
• Empirical Software Engineering
• Human Factors in Software Development
• +10 more

Gemma Catolino is an Assistant Professor at the Department of Computer Science, University of Salerno, and affiliated with the Software Engineering (SeSa) Lab. She has also served as an Assistant Professor at Tilburg University and Eindhoven University of Technology through the Jheronimus Academy of Data Science from September 2022 to December 2023, and previously as a Postdoctoral Researcher at Delft University of Technology and Tilburg/Eindhoven institutions. PhD in Computer Science, University of Salerno (2020), supervised by Prof. Filomena Ferrucci MSc in Management and Information Technology, University of Salerno (2016, magna cum laude) BSc in Computer Science, University of Molise (2014) Her research centers on empirical software engineering, focusing on both technical and social aspects affecting software development. Key areas include code smells, defect prediction, testability, changeability, and the emerging concept of “Community Smells”—social dysfunctions in developer teams. She investigates how human factors, team diversity (especially gender), and developer experience influence software quality and maintenance effort, often using mining software repositories and machine learning techniques. Her recent publications span high-impact journals and conferences such as IEEE TSE, EMSE, JSS, ICSE, and ICSME, with a strong trend toward integrating social and technical metrics for just-in-time defect prediction in mobile applications, analyzing community dynamics, and applying software quality metrics to cybersecurity contexts like dark web analysis. She has also contributed to MLOps and serverless computing. She has received several honors including a DEI research grant (2020), Best Technical Paper at BENEVOL 2019, first and second place in ACM Student Research Competitions (2018, 2017), and the Best Master Thesis award from the Italian Software Metrics Association (2017). Gemma Catolino has been actively engaged in academic service as a referee for top journals like IEEE TSE, EMSE, JSS, and IST, guest editor for special issues, and program/organizing committee member for major conferences including ICSE, MSR, SANER, and MobileSoft, where she served as Program Co-Chair in 2022. She has also contributed as a teaching assistant, lecturer, and course coordinator in machine learning and software engineering courses. She leads and contributes to research projects involving international collaborations, particularly with researchers such as Prof. Filomena Ferrucci, Prof. Andy Zaidman, Prof. Willem-Jam van den Heuvel, and Prof. Alexander Serebrenik. Her work bridges empirical software engineering with practical tool development and socio-technical analysis, positioning her at the forefront of modern software engineering research.

Markus BorgView profile

Lecturer

• Artificial Intelligence
• Software Engineering
• Empirical Software Engineering
• +11 more

Dr. Markus Borg is a Senior Researcher and Adjunct Lecturer at Lund University, Sweden, specializing in the intersection of software engineering and applied artificial intelligence. He is a Principal Researcher at CodeScene and contributes to editorial boards for Empirical Software Engineering and IEEE Software . His work bridges academic research with industrial practice through collaborations with Ericsson and contributions to open-source tools like SMIRK. Markus's research focuses on empirical software engineering , technical debt , safety engineering , and requirements engineering for AI-integrated systems. He explores two key directions: AI4SE (applying machine learning to software engineering challenges like defect management and technical debt remediation) and SE4AI (ensuring quality assurance for ML components in safety-critical domains such as automotive systems). His work aligns with regulatory frameworks like the EU AI Act and industry standards for automotive safety. 2025 Contributions : Gamify Track: Two papers on gamification in software maintainability ICSE Journal-First: Longitudinal study on automated bug assignment at Ericsson IDE Track: Trust calibration in AI-assisted refactoring TechDebt Technical Papers: ACE tool for LLM-based technical debt remediation 2024 Contributions : PROFES: AI Act compliance in requirements engineering MO2RE: Code quality specifications TechDebt: Maintainable code ROI analysis Programming with AI: CodeScene platform demonstration 2023 Contributions : CAIN: ML testing in automotive perception systems EASE: Code ownership and defect resolution Mutation Track: Safety-critical mutation testing validation His recent publications emphasize automated defect management , LLM-driven refactoring , and safety validation for ML components , particularly in automotive contexts. Tools like SMIRK and ACE demonstrate practical applications of his research. Markus actively participates in program committees for ICSE, TechDebt, and ICSME, with a focus on bridging academic research with industrial AI/SE challenges.

• Applied artificial intelligence
• Artificial intelligence
• Deep learning
• +6 more

Flavio Giobergia is a Researcher at the Department of Control and Computer Science (DAUIN) within Politecnico di Torino . His work spans applied artificial intelligence , with a focus on deep learning and machine learning applications. Research Interests : Machine learning under limited label availability, LLM-assisted code refactoring, subgroup performance analysis in ASR models, exoplanet atmospheric reconstruction, and predictive maintenance systems. Teaching : Course owner for Data Science and Machine Learning Lab and Large Language Models at Politecnico di Torino. Projects : Scientific head for the MAD – STANDARD BANKING project (2025–2026) and ImEDA (2023–2024), focusing on anomaly detection and model efficiency. Publications : 15+ recent works on topics including machine unlearning benchmarks, synthetic data for hallucination detection, and drift detection limitations, presented at top conferences like KDD, Interspeech, and IEEE AICT. Collaborations : Active in the SmartData@PoliTO center and co-author with Elena Baralis, Alkis Koudounas, and others.

Massimiliano Di PentaView profile

Professor

• Software Engineering
• Empirical Software Engineering
• Code Obfuscation
• +11 more

Massimiliano Di Penta is an Ordinary Professor in the Department of Engineering (DING) at the University of Sannio . His research focuses on Software Engineering , Code Obfuscation , Software Security , and Empirical Software Engineering , with a strong emphasis on Open-Source Systems and Machine Learning in Software Development .

Hironori WashizakiView profile

Professor

• Systems Engineering
• Software Engineering
• Machine Learning
• +3 more

Hironori Washizaki is a Professor at Waseda University 's School of Fundamental Science and Engineering and a Visiting Professor at the National Institute of Informatics. He serves as IEEE Computer Society 2025 President and has led initiatives in software engineering, ML design patterns, and IoT systems. His work bridges academia and industry through roles at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., LTD. Research Interests: His work spans software engineering, quality assurance, ML/IoT design patterns, and education innovation. He leads the SmartSE professional education program and standardizes software engineering bodies of knowledge through ISO/IEC/JTC1/SC7/WG20 . Scientific Awards: Golden Core Member (IEEE CS) Spirit of Computer Society Award KDDI Foundation Award Science and Technology Award, MEXT Best Paper Awards at ICSE, CSEE&T, and IWESEP Leadership & Grants: He has secured major grants (JSPS, MEXT) and held editorial roles at IEEE Transactions on Emerging Topics in Computing, IJSEKE, and IEICE journals. As IEEE CS Japan Chapter Chair and SEMAT Japan Chapter Chair , he fosters international collaborations. Labs & Teams: He leads the Global Software Engineering Laboratory at Waseda, focusing on traceability, reuse, and quality. This lab drives projects like ProMeTA (program metamodel taxonomy) and Trace ANY (software maintenance metrics).

Riccardo CoppolaView profile

Researcher

• Automated GUI Testing
• Software Metrics
• Non-functional Properties Evaluation
• +4 more

Dr. Riccardo Coppola is a post-doctoral researcher at Politecnico di Torino's Department of Control and Computer Engineering. With a PhD in Control and Computer Engineering (2021), his work focuses on automated GUI testing, gamification mechanics in software engineering, and non-functional property evaluation. He actively contributes to conferences like ICSE, ESEM, and A-TEST as organizer, chair, and author. M.Sc. & PhD: Politecnico di Torino Current Role: Researcher Research spans: Automated GUI testing for web & mobile applications Software metrics for gamification effectiveness Non-functional property evaluation (maintainability, accessibility) Integrating gamification mechanics into testing frameworks His publications demonstrate trends in gamification-driven testing tools, visual element identification algorithms, and LLM applications for UML modeling. Conference contributions show interdisciplinary focus bridging gamification, accessibility, and traditional software engineering. Roles include: 2025 Gamify Workshop Organizer & Session Chair 2024 A-TEST Programme Committee 2023 INTUITESTBEDS Organizing Committee

Jacopo SoldaniView profile

Associate Professor

• Service-based Software Engineering
• Cloud-Native Applications
• Microservices Architecture
• +3 more

Jacopo Soldani is an Associate Professor in the Department of Computer Science at the University of Pisa, Italy. He holds Italian National Habilitation as Associate Professor in Computer Science (SSD: 01/B1) and Computer Engineering (SSD: 09/H1) from 2021-2030. His roles include editorial board membership for top journals and organizing international conferences/workshops in software engineering. Education: PhD (2017), MSc (2013), and BSc (2011) in Computer Science from University of Pisa. Research focuses on service-based software engineering, cloud-native applications, microservices architecture, and systematic literature reviews. Key interests include security smells, failure analysis, and energy-efficient deployment strategies. His work addresses challenges in cloud-IoT integration, failure root cause analysis, and explainable AI in systems. Recent publications (2023-2025) emphasize security in microservices, failure resilience, and sustainable software design. Over 140+ publications in venues like ACM Computing Surveys, IEEE Transactions, and ESOCC/ICSOC conferences. Labs/Teams: Leads research on FREEDA (failure-resilient deployment) and NEST (energy observability). Active in open-source tool development (e.g., μTOSCA toolchain, KubeHound). Collaborates with industry on TOSCA orchestration and edge computing.

Carmine GravinoView profile

Professor

• Software Engineering
• Artificial Intelligence
• Cybersecurity
• +4 more

Carmine Gravino is a Full Professor at the Department of Computer Science at the University of Salerno. His research focuses on software engineering, artificial intelligence (AI), and cybersecurity, with notable contributions to requirements engineering, functional size measurement, and AI-driven educational technologies. He leads initiatives in metaverse applications for education (e.g., SENEM) and has pioneered work on blockchain-based security in digital learning environments. His academic journey includes extensive exploration of AI in healthcare (e.g., diabetes prediction models) and cybersecurity methodologies. He actively contributes to international collaborations via Erasmus+ programs, fostering educational exchanges and research partnerships in software engineering and emerging technologies. Gravino’s publications emphasize practical solutions like RECOVER (requirements generation from stakeholder conversations) and Echo (use case quality enhancement via LLMs). His work bridges theoretical advancements with real-world applications, such as green computing optimizations using GPUs and model-driven development frameworks for web applications. He maintains a strong presence in academic service, overseeing teaching, research, and laboratory activities. His research agenda includes advancing explainable AI, ethical guidelines for emotion recognition systems, and fostering innovation in software quality assurance.

• Software Engineering
• Program Synthesis
• Program Analysis
• +4 more

Ali Shokri is a tenure-track Assistant Professor in the Department of Computer Science at the University of Houston. His research focuses on program synthesis, software security, and formal methods, with applications in code translation, bug detection, and interprocedural analysis. Education: Ph.D. in Computing and Information Sciences, Rochester Institute of Technology (2023) M.Sc. in Information Technology, Tarbiat Modares University (2014) B.Sc. in Software Engineering, University of Tehran (2007) Research interests include automated software productivity tools, code reliability frameworks, and formally verified binary analysis. He has published in top venues like OOPSLA'24, ICSE'25, and ASE'21, where his program synthesis paper won first place. His work bridges academia and industry through collaborations with Google and PARC. Scientific contributions include patents on mathematical model extraction from binaries using SMT solvers and genetic algorithms. He serves on program committees for ICSE, LangSec, USENIX, and ASE conferences, emphasizing software engineering and security research.

Stefano LambiaseView profile

Researcher

• Social and Human Aspects of Software Engineering
• Cultural and Geographical Dispersion
• Community Smells
• +6 more

Stefano Lambiase is a researcher in Computer Science currently affiliated with Aalborg University in Denmark, where he holds an institutional email address (stla@cs.aau.dk). He earned his PhD in Computer Science from the University of Salerno at the Software Engineering Laboratory (SESA Lab), with a doctoral project titled "Longitudinal Data-Driven Software Project Management" focusing on the social and human aspects of Software Development and Management. His educational background includes: PhD in Computer Science from University of Salerno (2019-present) Master's Degree in Computer Science from University of Salerno (2019-2021), with thesis on "Cultural and Geographical Dispersion Impact on Communication and Collaboration of Software Development Teams" Bachelor's Degree in Computer Science from University of Salerno (2015-2019), with thesis on "Test Smell Detection and Suggestions (TESEUS)" Stefano's research interests center around the human and social dimensions of software engineering , with particular focus on cultural and geographical dispersion in software development teams, community smells (socio-technical anti-patterns), and their impact on productivity and software quality. His work bridges theoretical frameworks with practical applications, developing tools like CADOCS (a conversational agent for community smell detection) and DARTS (a test smell detection and refactoring plugin). He has also explored emerging areas including quantum software communities, metaverse development, and the integration of large language models in software engineering practices. His publication record demonstrates a consistent focus on socio-technical aspects of software development, with recent work examining cultural dispersion effects, community smells in various contexts (including machine learning systems and quantum computing), and educational applications in the metaverse. His research employs diverse methodologies including empirical studies, surveys, interviews, and tool development. Stefano has received recognition for his work, including a Best Paper Award at the 25th Euromicro Conference on Software Engineering and Advanced Application (SEAA 2022) for his paper "'There and Back Again?' On the Influence of Software Community Dispersion Over Productivity". He has been actively involved in the software engineering research community, serving on program committees for major conferences including ICSE-SEET 2024, SANER 2024, ICSEA 2023, MSR 2023, and SCAM-NIER 2023. Additionally, he served as Social Media and Web Chair for the Third Workshop on Gender Equality, Diversity, and Inclusion in Software Engineering (GE@ICSE 2022). Stefano has developed several research tools and projects: DARTS (Detection And Refactoring of Test Smells): An IntelliJ plugin for detecting and refactoring test smells CADOCS : A conversational agent for community smell detection and refactoring in Slack Erwin Bot : A chat bot for management support built with Azure Cloud Services BiblioNet : A Spring Boot Web App for library support QuantuMoonLight : A low-code platform to experiment with quantum machine learning SENEM : A software engineering-enabled educational metaverse SERGE : A serious game for risk management education in software project management

Andrea Alexander JanesView profile

Associate Professor

• Software Engineering
• Agile Methodologies
• Empirical Software Engineering
• +4 more

Andrea Alexander Janes is an associate professor at the Free University of Bozen-Bolzano, Italy, and an adjunct professor at the University of Oulu. He previously held positions at FHV Vorarlberg University of Applied Sciences and the Free University of Bozen-Bolzano. His research focuses on software engineering methodologies, including Lean/Agile approaches, value-based software engineering, empirical studies, and technology transfer. He holds a Master's in Business Informatics from TU Vienna and a PhD in Computer Science (with distinction) from the University of Klagenfurt, followed by a habilitation in Computer Science. Education: PhD in Computer Science, University of Klagenfurt, Austria (with distinction) Master’s in Business Informatics, TU Vienna, Austria Completed habilitation in Computer Science Research interests include software development processes, quality assurance, empirical software engineering, and microservices architecture. He has organized and chaired numerous international conferences and workshops, including ECSA 2026, ICSE 2025, and ESOCC 2025. His teaching spans courses in software engineering, operating systems, and agile methodologies at both bachelor’s and master’s levels. Key research projects include TeleCareHub (2022–2026), ADVERB (2019–2022), and SQuaSME (2016–2017). He collaborates with industry partners, focusing on applications like healthcare, sports analytics, and energy-efficient systems. His work emphasizes bridging academic research with practical industry needs through technology transfer and student engagement. Labs/Teams: Active in the NOI Techpark and collaborates with local IT companies, fostering student-industry interaction through events like the Reality Check series.

Alessandro MidoloView profile

Adjunct Professor

• Code Refactoring
• Software Testing
• Parallel Computing
• +3 more

Alessandro Midolo is an Adjunct Professor of Computer Science at the Department of Mathematics and Computer Science (DMI) of the University of Catania, Italy. His research focuses on code refactoring, software testing, and parallel computing, with a particular emphasis on improving source code quality and automating robustness injections into distributed systems. Research Interests : Code Refactoring Software Testing Parallel Computing Source Code Quality Mining Software Repositories Software Maintenance Recent Publications highlight advancements in distributed application robustness, automated test generation, Java stream refactoring, and parallel code transformation. His work bridges theoretical insights with practical tools for developers. Contact : alessandro.midolo@unict.it

Emiliano Alessio TramontanaView profile

Professor

• Software Engineering
• Distributed Systems
• Design Patterns
• +10 more

Emiliano Alessio Tramontana serves as Full Professor of Computer Science (INFO-01/A) in the Department of Mathematics and Informatics at the University of Catania. He maintains active research collaborations with Osaka University, Waseda University, and Victoria University of Wellington, and has authored over 170 Scopus-indexed publications in international journals and conferences. Professor Tramontana's research focuses on innovative solutions in software engineering and distributed systems, including runtime update consistency for distributed applications, modular implementations of design patterns through aspect-oriented programming, combinatorial test case reduction techniques, automatic object distribution mechanisms, and architectural solutions for QoS parameter negotiation. His work bridges theoretical foundations with practical applications in code analysis, security scenarios, and AI-assisted development. He has served as Chief Editor of Hindawi's Scientific Programming journal until May 2024 and co-chaired international conferences including IEEE WETICE 2024 and the AI-pattern workshop at ISSRE 2024. Professor Tramontana has extensive experience as an anonymous reviewer for IEEE and ACM conferences and journals from Elsevier, IEEE, and MDPI. PO FESR Biospec3 Linea 1.1.5 della Regione Siciliana (2014-2020) POR JACOS, Javacard Global Platform Operating System (2011-2015) POR PRIME, Integrated Platform for Reasoning, Multimedia, and Expert systems (2012-2015) FIR 375E90, Organization and treatment of notes and texts in security scenarios (2015-2017) PON PRISMA project (Interoperable Cloud Platforms for Smart-government) (2012-2015) SCN CLARA project (Cloud platform and smart underground imaging for natural Risk Assessment) PTR CREAMS Department project -- Codes for Recognizing and Avoiding System Attacks and Tampering PIACERI TEAMS inter-departmental project With over 150 undergraduate and master's thesis students supervised, Professor Tramontana offers thesis opportunities in distributed programming, code analysis, data analysis, text analysis (NLP), blockchain technology, energy distribution, and advanced AI tools for design and coding assistance. His office hours are held Wednesdays from 15:30 to 17:30 via Teams platform.

• High Performance Computing
• Sparse Matrix Computations
• Parallel Computing
• +3 more

Michele Martone is a Researcher at the High Performance Systems Division of the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. His work focuses on High Performance Computing (HPC) , sparse matrix computations , and code restructuring techniques , with a strong emphasis on OpenMP/MPI parallelization and semantic patching using the Coccinelle tool. Research Interests : HPC, automated code restructuring, sparse matrix optimization, semantic patching, and free/open source software (FLOSS) development. Key Tools : Author of the librsb library for sparse matrix operations, SparseRSB for Octave, PyRSB for Python integration, and the FIM image viewer. Publications : His recent work includes semantic patching for HPC refactorings, Coccinelle-based tooling, and performance optimization of sparse linear algebra libraries. Teaching : Delivers trainings and talks on Coccinelle, OpenMP/MPI, and FLOSS at events like HIPS25 , FOSDEM , and deRSE conferences. Advocacy : Strongly promotes free software, transparency in science, and public access to code developed with taxpayer funding.