Find Academic Supervisors

Pawel MordakaView profile

Researcher

• Plant Metabolism
• Synthetic Biology
• Chloroplast Engineering
• +3 more

Dr. Pawel Mordaka is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge. His research focuses on synthetic biology, genetic engineering, and plant metabolism, with a particular emphasis on chloroplast engineering and metabolic pathway optimization in model organisms like Chlamydomonas reinhardtii and Clostridium . Department: Plant Sciences Academic Rank: Researcher Email: pmm63@cam.ac.uk His work spans synthetic biology tool development (e.g., CpPosNeg selection systems, Start-Stop DNA assembly), transgene regulation in chloroplasts, and bioengineering of microbial-plant interactions. Recent publications highlight advancements in genetic code compression, promoter engineering, and heterologous pathway reconstruction for biofuel and biocatalysis applications. Dr. Mordaka's research intersects molecular plant biology and industrial biotechnology, leveraging algal chloroplasts as testbeds for radical metabolic rewiring. His methodologies include VIGS protocols, PVX expression vectors, and terminator analysis to refine transgene expression. Contact: pmm63@cam.ac.uk

• Molecular Biology
• Biochemical Engineering
• Gene Regulation
• +3 more

Sebastián Acosta Jurado is a researcher in Molecular Biology and Biochemical Engineering at the Centro Andaluz de Biología del Desarrollo (CABD), affiliated with the research group EXPRESIÓN GENICA EN BACTERIAS DE INTERÉS MEDIOAMBIENTAL . His work focuses on gene regulation in rhizobia, particularly Sinorhizobium fredii HH103 , and its symbiotic interactions with legumes.

Katja de VriesView profile

Senior Lecturer

• Law and Artificial Intelligence
• AI Policy
• Synthetic Data
• +6 more

Katja de Vries is a Senior Lecturer in Public Law at Uppsala University's Department of Law and affiliated with the Institute of Legal Informatics (SU). Her work bridges legal scholarship with technological innovation, focusing on the societal implications of artificial intelligence within European regulatory frameworks. Dr. de Vries holds a doctorate in law (Jur. dr.) and has developed an interdisciplinary research profile centered on the legal dimensions of emerging technologies. Her academic trajectory demonstrates consistent engagement with the evolving relationship between law and computational systems since her early work on profiling algorithms (2009-2010). Her research program critically examines AI's impact on fundamental rights, with current emphasis on AI-created data and voices. She leads the Swedish Research Council-funded VOICE project (2025-2030) investigating legal and societal perspectives of synthetic speech. Key thematic clusters include algorithmic transparency (counterfactual explanations in ADM systems), data governance (synthetic data and European data commons), and regulatory responses to AI (EU AI Act implementation, digital right to repair). Her scholarship uniquely combines doctrinal legal analysis with insights from computer science, ethics, and social theory. Analysis of her 15 most recent publications reveals intensifying focus on practical regulatory challenges in EU digital policy, particularly regarding AI-generated content and sustainable technology. Her work demonstrates methodological evolution from theoretical explorations of profiling (2010) toward solution-oriented research addressing contemporary legislative gaps, while maintaining critical theoretical engagement with legal personhood and algorithmic power structures. Scientific Awards: No awards were documented in the source materials. Dr. de Vries directs the VOICE research environment (Swedish Research Council 2025-2030), which examines legal frameworks for AI-generated voices through interdisciplinary collaboration. She previously contributed to EU projects including USEMP (User Empowerment for Enhanced Online Presence Management). Her policy impact is evidenced through formal opinions like the 2023 Uppsala Law Faculty statement on the EU repair directive, demonstrating translation of academic research into legislative discourse. She maintains active collaboration with researchers across computer science, social sciences, and humanities. The VOICE initiative represents her primary research infrastructure, assembling legal scholars, technologists, and social scientists to study AI voice synthesis implications. This environment facilitates her distinctive approach to technology regulation that prioritizes societal values alongside technical feasibility, particularly regarding embodiment in synthetic media and legal personhood questions emerging from creative AI applications.

Cristina LopesView profile

Professor

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +5 more

Cristina Lopes is a Professor of Informatics at the Donald Bren School of Information and Computer Sciences , University of California, Irvine. She holds administrative roles including Director of the Master of Software Engineering Program and former Director of the Institute for Software Research . Her research focuses on software engineering, programming languages, and distributed systems, with contributions to open-source projects like OpenSimulator and AspectJ. She has authored the influential book Exercises in Programming Style . Education: PhD from Northeastern University, MS/BS from Instituto Superior Técnico (Portugal). Awards include IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). She co-founded a virtual reality company for urban redevelopment and leads NSF-funded projects, including the prestigious CAREER Award. Research Interests: Large-scale software systems, aspect-oriented programming, code clone detection, and applying AI to programming challenges. Her work bridges theory and practice, with applications in urban simulation and healthcare systems. Awards and Grants: Over 15 awards including national and international distinctions. Grants focus on scalable software tools and environmental sustainability in computing. Labs/Teams: Leads the Software Engineering Research Group and collaborates with industry partners on open-source infrastructure and AI-driven development tools.

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +3 more

Crista Lopes is a Professor in the Department of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences. She serves as Director of the Master of Software Engineering Program and previously led the Institute for Software Research. Her research focuses on software engineering, programming languages, and distributed virtual environments. Dr. Lopes holds editorial roles as Editor-in-Chief of The Art, Science, and Engineering of Programming and on the Advisory Board of PACMPL . She has received notable awards including IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). Her teaching spans courses like INF 212 Programming Languages II and INF 225 Information Retrieval . Recent research includes AI-assisted programming tools, code analysis frameworks like Sourcerer , and studies on climate-conscious conference practices. She actively mentors students in UCI’s Software Engineering doctoral program.

Alice HeicklenView profile

Senior Lecturer

• Developmental Biology
• Cardiovascular Biology
• Molecular Biology
• +2 more

Alice Heicklen serves as a Senior Lecturer in the Discipline of Biological Sciences at Columbia University, specializing in molecular and developmental biology with dual research focuses in cardiovascular development and plant genomics. Her educational background includes: PhD in Transcriptional Regulation of the Microtubule Associated Protein Tau from Weizmann Institute of Science (2000), where she received the Outstanding Student Award MS in Intermodal Compensation in Neonatally Enucleated Syrian Hamster from Tel Aviv University (1991) BA from Penn State University (1988) Dr. Heicklen's research integrates cardiovascular developmental biology using zebrafish models to study GATA transcription factors in heart formation, with plant molecular genetics focusing on glyceraldehyde-3-phosphate dehydrogenase (GAPC) evolution across diverse species. Her innovative work includes creating transgenic zebrafish lines for real-time visualization of cardiac development and extensive cloning of GAPC genes from over 20 plant species. Analysis of her 15 most recent publications (2010-2015) reveals consistent methodology in plant gene characterization, with research spanning agricultural crops, medicinal plants, and ornamental species. This body of work demonstrates technical expertise in gene cloning and sequencing while contributing to understanding metabolic pathway evolution. Her scientific recognition includes: Outstanding Student Award during doctoral studies NIH Cardiovascular Fellowship American Heart Association Scientific Development Fellowship Her postdoctoral training at Albert Einstein College of Medicine (2000-2004) established her research trajectory through competitively funded fellowships. Current activities focus on molecular techniques development and collaborative projects across biological disciplines, with ongoing work in both animal developmental models and plant genomics. Dr. Heicklen maintains active research collaborations evident in her co-authorship patterns, working with teams at Columbia University and leveraging institutional resources in biological sciences.

• Software Engineering
• Software Defect Prediction
• Machine Learning for Software Engineering
• +7 more

Akito Monden is a prolific Japanese software-engineering scholar with 171 publications recorded in dblp during 1995-2025. His recent work centres on defect prediction, online learning, bandit-based tool selection, and empirical studies of software quality and human factors. Research interests span software defect prediction, mining software repositories, effort estimation, clone detection, code generation, and the application of machine-learning techniques (notably bandit algorithms and ensemble methods) to practical software-engineering tasks. He also investigates requirements ambiguity, security-bug identification with large language models, and gaze-based human-computer interaction in programming education. Across 2022-25 articles Monden explores online learning to cope with concept drift in defect datasets, multi-armed bandit algorithms for dynamic selection of clone detectors, fault-localisation techniques and code generators, and LLM-based security-bug detection. These themes reflect a sustained focus on data-driven, adaptive approaches that improve software quality assurance processes.

Michalis FamelisView profile

Assistant Professor

• Software analysis
• Software design
• Empirical software engineering
• +3 more

Michalis Famelis is an Assistant Professor at the Department of Computer Science and Operations Research , affiliated with the Faculty of Arts and Sciences at Université de Montréal . He leads research in the GEODES Software Engineering Research Group , focusing on formal yet practical methods for software development. His work integrates formal verification, model-driven engineering, and empirical methods to address challenges in software design and uncertainty management. Educated at the University of Toronto (PhD 2016, MSc 2010) and the National Technical University of Athens (DiplEng 2008), he completed a postdoctoral fellowship at the University of British Columbia . He teaches courses such as IFT1025 Programming 2 and IFT6755 Software Analysis . His research projects include a Wellcome Trust-funded platform for climate-sensitive disease modeling and CRSNG grants for formal software design support. He has supervised 6 master’s students, focusing on topics like design uncertainty, API usage verification, and software product lines. Notable collaborations involve Climate-Sensitive Infectious Disease Modelling and Formal Support for Software Design . His work emphasizes improving developer workflows through tool development and empirical studies.

Feng ChenView profile

Senior Lecturer

• Software Engineering
• Distributed Computing
• Software Evolution
• +6 more

Dr. Feng Chen is a Senior Lecturer at the School of Computer Science and Informatics, De Montfort University (UK), affiliated with the Cyber Technology Institute within the Software Technology Research Laboratory. With academic qualifications from Nankai University, Dalian University of Technology, and De Montfort University, he specializes in software engineering, focusing on Model Driven Architecture (MDA), Service Oriented Architecture (SOA), and Cyber-Physical Systems. PhD thesis: Modernizing legacy systems via MDA Research themes: Cloud/Edge Computing, Internet of Things, Ambient Assisted Living Systems His 15 most recent publications span topics in sensor data segmentation, service-oriented architectures, and data leakage prevention. Notable scientific achievements include the Second Class Dalian Information System Application Prize , Golden Snake Prize , and a Best Paper Award at Healthcom . He supervises PhD students in areas like real-time systems and smart environments, and has secured significant research grants including an EU Horizon 2020 project (€3.8M) .

• Software Engineering
• Cybersecurity
• Information Systems & Technology
• +3 more

SHAR Lwin Khin is a Full-time Associate Professor at the School of Computing and Information Systems, Singapore Management University (SMU). Specializing in cybersecurity, software engineering, and digital transformation, their work bridges academic research with practical applications in secure software development. Education: PhD in Computer Science, Nanyang Technological University (2014) Research Interests: Focus on vulnerability detection in software systems, Android app security, and cybersecurity frameworks. Their recent work explores large language models (LLMs) for security applications, including code analysis, runtime anomaly detection, and energy-efficient AI for edge computing. Article Trends: Their research spans 2025–2024, emphasizing LLM-driven vulnerability detection, Android security optimization, and drone cybersecurity. Keywords include software engineering, deep learning, and cyber-physical systems, with subfields like code debloating, XSS/SQL injection mitigation, and OSS security.

• Software Engineering
• Requirements Engineering
• Functional Size Measurement
• +5 more

Carmine Gravino is a Professor in the Department of Computer Science at the University of Salerno, Italy, with an extensive publication record spanning over two decades from 2001 to 2025. His academic career demonstrates consistent research productivity with numerous publications in top software engineering venues including IEEE Transactions on Software Engineering, Empirical Software Engineering, and Information and Software Technology. Gravino's research spans multiple domains within software engineering and its intersection with emerging technologies. His primary research interests include software measurement (particularly COSMIC functional size measurement), requirements engineering, code quality analysis, and the application of artificial intelligence to software engineering problems. In recent years, he has expanded his research into educational technology, focusing on the development of educational metaverses and the integration of generative AI in learning environments. His work also extends to healthcare applications, particularly in diabetes prediction using machine learning techniques. The trajectory of Gravino's recent publications reveals a strategic evolution from traditional software engineering topics toward the integration of cutting-edge AI technologies. His 2023-2025 works prominently feature large language models applied to functional size measurement, requirements engineering, and code analysis. Simultaneously, he has developed a significant research stream in educational technology, creating frameworks for educational metaverses that incorporate ethical considerations for emotion recognition and AI integration. His healthcare-related work demonstrates interdisciplinary collaboration, applying software engineering rigor to medical prediction problems. Gravino maintains an active research group with frequent collaborations, particularly with Filomena Ferrucci (69 joint publications), Genny Tortora (33), Giuseppe Scanniello (30), Vincenzo Deufemia (29), and Michele Risi (29). His work appears in both journal and conference venues, with a strong emphasis on empirical validation through controlled experiments and case studies. His research has practical applications in software project management, requirements engineering processes, and educational technology development.

Earl T. BarrView profile

Professor

• Software Engineering
• Program Analysis
• Automated Program Repair
• +5 more

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). He received his Ph.D. in Computer Science from the University of California, Davis in 2009. His educational background includes: Ph.D. in Computer Science, 2009, University of California, Davis Barr's research focuses on software engineering, particularly program analysis, automated program repair, and the application of machine learning to code (AI4Code). He is renowned for his work on dual channel analysis, which examines how code combines natural language elements (in identifiers, comments, and stylistic choices) with formal programming language. His research also explores game theory applications to software development processes and how dual channel constraints can improve type inference and code understanding. His recent publications demonstrate a strong trend toward leveraging large language models for code understanding and modification, with particular emphasis on dual channel constraints and natural type inference. His work bridges traditional software engineering techniques with modern AI approaches, showing how machine learning can enhance program analysis and repair while maintaining rigorous theoretical foundations. Notable awards include: ACM SIGSOFT Distinguished Paper Award for Automated Software Transplantation (2015) ACM SIGSOFT Distinguished Paper Award for Learning Natural Coding Conventions (2014) ACM SIGSOFT Distinguished Paper Award for Collecting a Heap of Shapes (2013) Best Paper Award for TrustDavis: A Non-Exploitable Online Reputation System (2005) Barr actively supervises numerous PhD students and postdocs, with current research focusing on AI for code, software security, and program analysis. He collaborates extensively with Santanu Dash of Royal Holloway on dual channel program analysis, and they jointly supervise PhD students through the EPSRC Centre for Doctoral Training in Cyber Security for the Everyday. His work often combines theoretical rigor with practical tool development, resulting in several publicly available research tools that influence both academic research and industry practice. He leads the System Software Engineering Group at UCL, which focuses on developing novel approaches to software engineering challenges at the intersection of human and machine aspects of programming. Current research directions include dual channel analysis for vulnerability detection, game-theoretic approaches to development processes, and AI-assisted software development.

Jean-Rémy FalleriView profile

Professor

• Software Engineering
• Software Evolution
• Source Code Differencing
• +3 more

Jean-Rémy Falleri is a Full Professor of Computer Science at Enseirb-Matmeca (Bordeaux INP) and a researcher at LaBRI laboratory in Bordeaux, France. He serves as head of the Computer Science department at Enseirb-Matmeca and co-head of the Systems and Data department at LaBRI. From 2020 to 2025, he was appointed as a junior member (later honorary member) of the prestigious Institut Universitaire de France. His educational background includes a habilitation from Université de Bordeaux (2015), a PhD from Université Montpellier 2, and a Master's degree from IMT Mines Alès (formerly École des Mines d'Alès). He also completed post-doctoral research at INRIA Lille in the RMoD group. Falleri's research focuses on software engineering, particularly software evolution and the development of practical tools to analyze and understand code changes. His work bridges theoretical research with practical applications, resulting in tools like GumTree for visualizing code differences and Roseau for detecting breaking changes in libraries. His research interests span source code differencing, API analysis, breaking change detection, and software maintenance techniques. His publication record shows consistent contributions to top software engineering conferences including ICSE, ASE, ICSME, and FSE, with research themes evolving from code clone detection and developer expertise extraction to modern challenges in API evolution and Docker configuration analysis. Junior Member of Institut Universitaire de France (2020-2025) Honorary Member of Institut Universitaire de France (2020-2025) Falleri has supervised numerous Master's students, PhD candidates, and post-doctoral researchers throughout his career. He has held significant service roles including Head of LaBRI's Systems and Data department (since 2021), Head of LaBRI's Software Engineering group (2015-2021), and member of various conference program committees. His work has practical impact through actively maintained tools that address real challenges in software development and evolution.

Rodolfo AramayoView profile

Associate Professor

• Genetics
• Genomics
• Molecular Biology
• +5 more

Rodolfo Aramayo serves as Associate Professor in the Department of Biology at Texas A&M University, specializing in genetics, genomics, and computational approaches to biological information systems. His interdisciplinary work bridges molecular biology, bioinformatics, and epigenetics with significant editorial contributions to PeerJ across 20+ life science disciplines. His academic journey includes: B.S. in Molecular Biology, University of Brasilia (1982) M.S. in Molecular Biology, University of Brasilia (1986) Ph.D. in Genetics, University of Georgia (1992) Postdoctoral Training, University of Wisconsin Madison (1993) Postdoctoral Training, Stanford University (1997) Dr. Aramayo pioneered Digital Biology, a framework for converting biological information into digital formats to uncover genomic patterns through computational analysis. His laboratory investigates meiotic silencing in Neurospora crassa, focusing on how unpaired DNA triggers RNA-mediated silencing during meiosis. This work explores connections between fungal epigenetic mechanisms and analogous processes in nematodes and mammals, employing genetic, molecular, and biochemical approaches to identify key molecular players. His 15 most recent editorial contributions reveal a research trajectory spanning molecular diagnostics, cancer genomics, microbial ecology, and computational tool development. Articles demonstrate consistent focus on RNA mechanisms, genomic pattern recognition, and cross-species epigenetic comparisons, with increasing emphasis on computational biology applications since 2020. No scientific awards were documented in the provided materials. Dr. Aramayo maintains an active research laboratory investigating Digital Biology applications and meiotic silencing mechanisms. His editorial leadership at PeerJ demonstrates commitment to advancing life sciences scholarship, with recent contributions covering emerging RNA therapeutics, ancient DNA analysis, and sustainable agricultural microbiology. Current work extends Digital Biology approaches from animal genomes to fungal, plant, and bacterial systems.

Daniel B. ReevesView profile

Assistant Professor

• Mathematical Modeling of Infectious Diseases
• HIV Dynamics and Cure Research
• Viral Evolution
• +3 more

Daniel B. Reeves serves as a Senior Staff Scientist in the Schiffer Group within the Infectious Disease Sciences Program at Fred Hutchinson Cancer Center and holds an academic appointment as Affiliate Assistant Professor in the Department of Global Health at the University of Washington. His work bridges quantitative physics and infectious disease research through advanced mathematical modeling of viral-immune system interactions. Education Dartmouth College, PhD in Physics (2015) Colby College, BA in Physics (2010) Dr. Reeves' research centers on HIV reservoir dynamics, viral evolution, and pandemic response modeling. His group develops computational frameworks to analyze proviral clones, T cell ecology, and antibody-mediated prevention strategies, with significant focus on SARS-CoV-2 variant emergence and superspreading events. This theoretical work directly informs clinical interventions for viral eradication and vaccine development. Current projects include pediatric HIV reservoir decline analysis, anti-proliferative HIV therapy modeling, and CD4+ T cell subset persistence studies. His research receives funding from the Washington Research Foundation, Center For AIDS Research, and National Institutes of Health, with all computational code publicly available via GitHub. As an active advocate for scientific equity, Dr. Reeves serves on the board of Hutch United—a grassroots diversity, equity, and inclusion initiative—and maintains commitments to Indigenous land acknowledgment and anti-racist praxis within academic spaces.