جست‌وجوی استاد و پژوهشگر

Alessandra Gorlaمشاهده پروفایل

دانشیار

• Malware detection for mobile applications
• Automatic software repair
• Software testing
• +۴ مورد دیگر

Alessandra Gorla is an associate researcher professor at IMDEA Software Institute in Madrid, Spain, with a strong background in software engineering research. She previously worked as a postdoctoral researcher with Andreas Zeller at Saarland University in Germany and completed her PhD under Mauro Pezzè at the University of Lugano in Switzerland. Her research bridges theoretical foundations with practical applications in mobile software systems. Her research focuses on malware detection for mobile applications, automatic software repair, software testing and analysis. She has developed techniques for detecting behavior anomalies in graphical user interfaces, identifying third-party libraries in mobile apps, and leveraging intrinsic software redundancy for reliability. Her work spans both Android and iOS ecosystems, with particular attention to permission systems, release practices, and security implications. Analysis of her recent publications reveals a strong trend toward mobile application security and analysis, with increasing focus on iOS systems alongside traditional Android research. Her work combines static and dynamic analysis techniques, often incorporating natural language processing for comment analysis and test generation. There's a clear progression from foundational work on intrinsic software redundancy to more applied research on mobile security and testing. FRITZ-KUTTER AWARD! for PhD thesis on Automatic Workarounds BEST PAPER AWARD! for Search-based Security Testing of Web Applications BEST STUDENT POSTER AWARD! for Automatic Workarounds as Failure Recoveries Dr. Gorla actively mentors students and seeks motivated individuals for internship and PhD opportunities in software engineering. She has served in various organizational roles including Tool Demonstrations co-chair for FSE 2016, Artifact Evaluation co-chair for ESSoS 2016 and ISSTA 2016, and multiple program committee positions at top software engineering conferences. Her work has been supported through collaborations with major research institutions and industry partners. At IMDEA Software Institute, Dr. Gorla leads research on mobile application analysis, particularly focusing on behavioral analysis of Android and iOS applications. Her CHABADA prototype for clustering Android apps by description topics and identifying API usage outliers demonstrates her practical approach to malware detection. She also investigates intrinsic software redundancy for building more resilient systems.

Jemily Rimeمشاهده پروفایل

پژوهشگر ارشد

• Audio and Music Production
• Immersive Media and Technologies
• Podcasting
• +۲ مورد دیگر

Jemily Rime is a Research Fellow in Creative Technologies and Immersive Storytelling at Anglia Ruskin University's StoryLab within the Faculty of Arts, Humanities, Education and Social Sciences, and concurrently serves as Professor of Electronic and Produced Music at the Guildhall School of Music and Drama. Her interdisciplinary work bridges audio innovation, immersive media, and creative coding through participatory design methodologies. Her academic foundation includes a BSc in Physics from King's College London (2018) where she simultaneously developed her debut album 'Otters Mate For Life', and a 2024 PhD from the University of York focused on AI-driven tools for personalised podcasting developed in partnership with XR Stories and BBC R&D. Rime's research explores audio production, immersive technologies, and storytelling through human-centered approaches. She investigates how digital tools can enhance creative processes, particularly in podcasting and music production, with strong emphasis on user agency and co-creation. Her work consistently integrates technical innovation with artistic expression, examining both practical applications and ethical implications of emerging technologies. Analysis of her publications reveals a cohesive trajectory in redefining audio media through computational methods. Early work established frameworks for podcast production workflows, while recent research expands into VR narratives and AI voice cloning, demonstrating increasing sophistication in human-AI collaboration for creative output. This evolution highlights her commitment to developing tools that empower creators rather than replace human agency. Her scientific recognition includes: Best Paper Award at CHIRA 2024 for 'Interviewing ChatGPT-Generated Personas to Inform Design Decisions' Rime mentors students in creative coding projects showcased through The_Coding_Choir, with notable collaborations including BBC R&D and XR Stories. Current initiatives encompass The Navigator oral history archive for Cambridge's Kite neighborhood and Resonance Kernow's spatial audio exploration in Cornwall, reflecting her dedication to community-engaged research. She leads The_Coding_Choir research group which develops tools like pod-CLIPR for podcast chapterisation while maintaining an active performance career. Her artistic practice as a jazz-pop singer-songwriter directly informs her academic work, creating a virtuous cycle between theoretical research and practical musical innovation.

Ying Zouمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence for Software Engineering
• Software Evolution
• +۲ مورد دیگر

Dr. Ying Zou is a Professor in the Department of Electrical and Computer Engineering at Queen's University's Smith Engineering faculty in Kingston, Ontario, Canada. With an extensive publication record spanning from 2018 through 2025, Dr. Zou has established herself as a leading researcher in empirical software engineering with a growing focus on AI integration. Dr. Zou's research focuses on Software Engineering , Artificial Intelligence for Software Engineering (AI4SE) , Software Evolution , Software Analytics , and Empirical Software Engineering . Her work bridges theoretical approaches with practical applications, examining developer behavior, code quality improvement, and AI techniques for software engineering tasks. Recent publications demonstrate a clear progression from traditional empirical studies toward more AI-centric approaches, particularly in code refactoring, type inference, and performance analysis. Analysis of Dr. Zou's publication trends reveals a strategic evolution in her research focus. Early work centered on empirical studies of Stack Overflow and GitHub, while recent publications increasingly integrate large language models and AI techniques for software engineering tasks. Her research spans multiple dimensions including code quality, developer productivity, open source community dynamics, and performance optimization, with consistent methodological rigor in empirical validation. Dr. Zou has served in numerous leadership roles across major software engineering conferences including ASE, ICSE, and ESEC/FSE. She has been a Program Committee member for multiple tracks and conferences, and notably served as New Faculty Mentoring Co-Chair for ESEC/FSE 2026. Her service to the community extends to organizing conference tracks, chairing sessions, and mentoring new researchers in the field.

• Hardware Security
• Cryptography
• Side-Channel Attacks
• +۳ مورد دیگر

Elena Dubrova is a Professor at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology. She specializes in hardware security, cryptography, and embedded systems security. Her roles include examiner and course responsible for advanced degree projects in Computer Engineering, Communication Systems, Embedded Systems, and Machine Learning. She also teaches courses such as Design of Fault-Tolerant Systems, Hardware Security, and Internet Security and Privacy. Her research focuses on side-channel attacks, cryptographic algorithm vulnerabilities, and FPGA security. Notable work includes analyzing hardware security flaws in cryptographic implementations (e.g., CRYSTALS-Kyber, AES), RF signal leakage in chips, and mitigating threats in FPGA-based systems. Her contributions span both theoretical advancements and practical countermeasure development. Dr. Dubrova’s articles highlight trends in post-quantum cryptography vulnerabilities, machine learning-assisted security analysis, and the integration of physical unclonable functions (PUFs) for secure authentication. She emphasizes hardware-software co-design for robust security solutions. No scientific awards are explicitly listed in the provided information. Her work involves collaborative projects on cryptographic protocol design and secure embedded system architecture, though specific grants or lab affiliations are not detailed here.

• Software Engineering
• Source Code Analysis
• Software Clone Detection
• +۱۲ مورد دیگر

James R. Cordy is a Professor in the School of Computing at Queen's University, Faculty of Engineering and Applied Science, Kingston, Canada. He is a leading researcher in software engineering, with a focus on source code analysis, software clone detection, model-driven engineering, and program transformation. He has been actively publishing since 1977, with a sustained record of contributions in top-tier venues such as ICSE, MoDELS, and WCRE. His research interests include software clone detection, model transformation, Simulink models, source transformation, software maintenance, and grammatical inference. He has developed and contributed to influential tools such as TXL and NiCad, and his work often involves empirical studies and tool evaluation in real-world software systems. The most recent articles highlight trends in model transformation, clone detection, verification of state machines, and migration of legacy systems. His work increasingly integrates formal methods and empirical validation, particularly in automotive and safety-critical domains. He has also explored applications in healthcare software, such as artificial pancreas systems. Most Influential Paper Award, SCAM 2001 (awarded in 2019) He has advised numerous students, including Manar H. Alalfi, Matthew Stephan, and Chanchal K. Roy, who have co-authored multiple publications with him. His research is often collaborative, involving teams from Queen's University and other institutions. He has also contributed to workshops and special issues, demonstrating leadership in the software engineering community.

Thomas Leichمشاهده پروفایل

استاد

• Software Product Line Engineering
• Requirements Engineering
• IT Security
• +۱۱ مورد دیگر

Prof. Dr.-Ing. Thomas Leich holds the Volkswagen Financial Services Endowed Professorship for Business Informatics, specifically Requirements Engineering, at Harz University of Applied Sciences. He is affiliated with the Faculty of Automation and Information, focusing on software variability and configurable systems. University: Harz University of Applied Sciences School: Faculty of Automation and Information Academic Rank: Professor Research Interests span software product line engineering, IT security, Industry 4.0, and feature-oriented programming. His work bridges academic innovation with industrial applications, particularly in secure and scalable systems for automotive and enterprise contexts. Recent Publications emphasize security in configurable systems, empirical software engineering studies, and automotive platform management. Articles often involve collaborations with teams at Otto von Guericke University and international institutions. Scientific Awards include the Hugo Junkers Research Award (2013), the Wissenschaftspreis der Wernigeröder Stadtwerkestiftung (2017), and the 2012 Faculty Research Award from the University of Magdeburg. Supervision of over 20 theses since 2008, spanning topics in ERP security, program comprehension, and embedded systems. He leads the EXPLANT project, funded by DFG, and contributes to FeatureIDE , an extensible framework for feature-oriented development.

Nathan Dahlinمشاهده پروفایل

استادیار

• Machine Learning
• Stochastic Control
• Optimization
• +۲ مورد دیگر

Nathan Dahlin is an Assistant Professor in the Department of Electrical and Computer Engineering at the University at Albany's College of Nanotechnology, Science, and Engineering. He holds a BS, MS, and PhD in Electrical Engineering and an MA in Applied Mathematics from the University of Southern California. Prior to joining UAlbany, he was a Postdoctoral Research Associate at the University of Illinois Urbana-Champaign and a senior audio DSP research engineer at Audyssey Laboratories. Dr. Dahlin's research focuses on fundamental problems in machine learning, stochastic control, optimization, and microeconomics, with applications in developing computationally efficient decision-making approaches for smart energy systems. His work emphasizes reliability in uncertain environments and risk management. His recent publications demonstrate strong focus on machine learning applications in control systems, energy management, and algorithm design. Articles frequently address topics like imitation learning, economic dispatch optimization, neural network transformation, and kernel-based learning methods, often with practical implementations in energy systems and smart grids. Dr. Dahlin is active in professional organizations including the Institute of Electrical and Electronics Engineers (IEEE) and the Association for the Advancement of Artificial Intelligence (AAAI). He serves as a reviewer for leading conferences and journals including AAAI Conference on Artificial Intelligence, IEEE Transactions on Control of Network Systems, IEEE Transactions on Power Systems, and IEEE Transactions on Smart Grid.

• Software Engineering
• Cybersecurity
• Behavioral Biometrics
• +۳ مورد دیگر

Dr. Daqing Hou is a Professor at Clarkson University's Coulter School of Engineering & Applied Sciences, affiliated with the Department of Electrical & Computer Engineering and Computer Science. His research bridges software engineering, cybersecurity, behavioral biometrics, and education research. He earned his Ph.D. in Computing Science from the University of Alberta, and M.S./B.S. in Computer Science from Peking University. Research focuses on improving software development efficiency through project-based learning (PjBL), empirical studies, and human factors. Key areas include behavioral biometrics (keystroke/mouse dynamics), smart housing/energy systems, and cybersecurity solutions. He has pioneered tools like CReN for managing code clones and has contributed to Eclipse/UIMA frameworks. Recent publications emphasize behavioral authentication methods, mobile biometrics evaluation, and framework design recommendations. His work has been recognized with awards including IEEE ICSME 2014 Best Paper Nomination and IBM Innovation Awards (2005/2007). Teaching spans software engineering, GUI design, databases, machine learning, and compilers. He advises students on topics like API usability, security systems, and programming language tools.

Pawel Mordakaمشاهده پروفایل

پژوهشگر

• Plant Metabolism
• Synthetic Biology
• Chloroplast Engineering
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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 Vriesمشاهده پروفایل

مدرس ارشد

• Law and Artificial Intelligence
• AI Policy
• Synthetic Data
• +۶ مورد دیگر

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 Lopesمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +۵ مورد دیگر

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
• +۳ مورد دیگر

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 Heicklenمشاهده پروفایل

مدرس ارشد

• Developmental Biology
• Cardiovascular Biology
• Molecular Biology
• +۲ مورد دیگر

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
• +۷ مورد دیگر

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.