جست‌وجوی استاد و پژوهشگر

Juan Pablo Galeottiمشاهده پروفایل

استاد

• Automatic Test Generation
• Program Verification
• Specification Inference
• +۵ مورد دیگر

Juan Pablo Galeotti is a Professor at the University of Buenos Aires (UBA) in the Department of Computer Science within the Faculty of Exact and Natural Sciences . He is also a researcher at CONICET and a member of the LaFHIS and LIA-INFINIS laboratories. His research focuses on automatic test generation , program verification , specification inference , and decision procedures like SMT and SAT. Education & Background: While specific degrees are not mentioned, his PhD thesis was titled "Software Verification using Alloy" , advised by Marcelo Fabian Frias . Research Interests: His work spans: Search-based software testing REST API fuzzing and testing Smart contract verification Dynamic and static analysis Testability transformations Loop invariant inference Publications & Trends: Galeotti has published extensively in top-tier venues like ICSE, FSE, ASE, ISSTA, IEEE TSE , and ACM TOSEM . His recent work ( 2020–2025 ) focuses on tools like EvoMaster for REST API testing, EvoSuite for Java unit testing, and TACO for SAT-based verification. Awards & Service: He has served as PC Co-Chair for SBST@ICSE 2017–2018 , PC Member for ICSE, ISSTA, ICST , and reviewer for journals like TOSEM, TSE . He co-organized ISSTA 2016 and ICSE 2017 . Students & Projects: He currently supervises 3 PhD and 4 Master’s students. He has co-directed CONICET and UBA-funded projects on bounded verification and memory analysis. Labs & Collaborations: He leads research at LaFHIS and collaborates with LIA-INFINIS , working on tools like EvoMaster , DynaMate , and TACO .

Ali Dogruمشاهده پروفایل

استاد

• Software Engineering
• Component-Based Systems
• Complex Event Processing
• +۷ مورد دیگر

Ali Dogru is a Professor of Computer Science at the University of Texas at San Antonio (UTSA), affiliated with the College of Sciences. He holds a Ph.D. in Computer Science from Southern Methodist University, an M.S. in Electrical Engineering from the University of Texas at Arlington, and a B.S. in Electrical Engineering from the Technical University of Istanbul. His research focuses on software engineering methodologies, particularly component-based systems, compositional software development, complex event processing, and fault management. He explores interdisciplinary solutions through connector technologies to address IoT heterogeneity and variability modeling in microservices architecture. Dr. Dogru's work emphasizes axiomatic design theory applications in software systems, including service-oriented computing, model-driven engineering, and cloud-enabled development. His contributions span domain-specific languages for fault management, adaptive workflows in cloud environments, and synthetic medical data generation for healthcare analytics. He has published extensively on topics like UML connector enhancements, microservice interoperability, and EEG emotion recognition using wavelet transforms. His interdisciplinary research bridges theoretical concepts with practical industry applications, as evidenced by his work on legacy system migration and mashup strategies in service-oriented computing. While no advising or grant details are explicitly mentioned, his academic profile reflects a strong focus on innovation in software development practices. His involvement in conferences such as the Turkish National Software Architecture Conference highlights his role in advancing software engineering standards and methodologies. Dr. Dogru's research lab (if applicable) is not explicitly detailed in the provided texts, but his publications indicate sustained engagement with cutting-edge computational challenges in software systems.

Ralph Müller-Pfefferkornمشاهده پروفایل

پژوهشگر

• Data Management
• Research Data Infrastructure
• High Performance Computing
• +۴ مورد دیگر

Ralph Müller-Pfefferkorn is Head of the Department of Distributed and Data Intensive Computing at the Center for Information Services and High Performance Computing, Technische Universität Dresden. His work focuses on data management, metadata systems, and high-performance computing infrastructure. He holds a PhD in Physics from TU Dresden (2001) and has extensive experience in research data infrastructure development, spanning roles from 1996 to present across physics and computational science domains. Education: 2001: Dr. rer. nat., Physics, TU Dresden (Thesis on BABAR detector calibration) 1996: Diploma in Physics, TU Dresden 1992–1996: Studies in Physics at TU Dresden 1990–1992: Studies at TU Chemnitz Research interests emphasize distributed data management, long-term archiving, and FAIR data principles. He contributes to initiatives like the Research Data Alliance (IG Co-Chair) and UNICORE Forum board. His publications address challenges in big data workflows, metadata standards, and interdisciplinary infrastructure integration. Labs/Teams: Leads the Distributed and Data Intensive Computing team within TU Dresden's HPC center, collaborating on projects like MoSGrid and MASi repository systems.

Salman Ahmedمشاهده پروفایل

پژوهشگر ارشد

• Data Analytics
• Natural Language Processing (NLP)
• AIops
• +۷ مورد دیگر

Salmans is a Research Fellow at the DigiTech Centre within the Digital Futures Institute at the University of Suffolk, affiliated with the Research Directorate. His work bridges academia and industry through consultancies, training, and knowledge dissemination. He holds a PhD in Data Analytics (specializing in NLP) from Ulster University, along with Master's and Bachelor's degrees in Software Engineering and IT. Education: PhD in Data Analytics (NLP specialization), Ulster University (2020) MSc Software Engineering, Alhamd Islamic University (Pakistan) BSc Information Technology, Alhamd Islamic University (Pakistan) Research focuses on NLP, AIops, and applied data analytics with industry collaboration. Key areas include transformer models (BERT/ERNIE/RoBERTa), IT incident prediction, and agritech AI. His work is funded by UKRI, EPSRC, and the Turing AI Fellowship. Recent publications explore cybersecurity in WordPress (2024), AIops frameworks (2023), and neural POS tagging (2023). His research demonstrates a strong focus on practical applications across IT, agriculture, and language processing. Received the FHEA fellowship (2023) for teaching contributions. Secured £350k UKRI grants for agritech projects, including 'Agri-KG' and 'Agri-F2P', advancing AI-driven agricultural decision-making. Previously managed a £1M EPSRC-funded project with AllState for infrastructure incident prediction. Lab/Team Affiliations: Lead researcher in the DigiTech Centre's NLP group and collaborator in Ulster University's Intelligent Systems Research Centre.

Jefferson Mollériمشاهده پروفایل

دانشیار

• Software Engineering
• Computer Science
• Empirical Research Methods
• +۱۰ مورد دیگر

Jefferson Molléri is an Associate Professor at Kristiania University College's School of Economics, Innovation and Technology. He specializes in evidence-based software engineering and empirical research methods, focusing on software process improvement, AI applications in software engineering, and human factors in technology development. PhD in Software Engineering (Blekinge Institute of Technology, 2019) Postdoctoral research at Simula Metropolitan Centre for Digital Engineering Academic experience since 2014 His research emphasizes methodological rigor, ethical considerations, and participatory approaches in software engineering. He has developed empirical standards and checklists for survey research validation. Recent publications focus on DataOps integration, hybrid workplace transformations, and research quality frameworks. Jefferson teaches software engineering, information technology, and computer science courses. He advocates for critical appraisal of scientific literature and has extensive experience supervising students across undergraduate, graduate, and doctoral programs.

• Information Systems & Technology
• Information Systems Management
• Technology-Enhanced Learning & Pedagogy
• +۵ مورد دیگر

LAU Yi Meng is a Full-time Lecturer of Information Systems at the School of Computing and Information Systems , Singapore Management University (SMU). He holds a Master of Information Technology in Business from SMU (2012). His research focuses on Information Systems Management, Technology-Enhanced Learning, and Digital Transformation. He teaches courses such as Digital Payments & Innovation, Web Application Development, and Digital Business Transformation. His recent work explores microservices in software development, Web3/NFT market dynamics, and pedagogical innovations like VR labs and gamified learning platforms. Research Interests: Information Systems & Technology Technology-Enhanced Learning (e.g., VR classrooms, flipped learning) Future of Work (e.g., digital transformation challenges in retail/hawker sectors) Web3/NFT markets (e.g., identity verification frameworks, usability vs. collectibility) Articles Trends: Recent publications (2023–2025) analyze Web3/NFT ecosystems, software development methodologies, and digital adoption challenges in traditional industries. His 2025 work on hawkers' resistance to digitalisation highlights critical barriers in small business transformation. The VR Computing Lab (2022) demonstrates his commitment to immersive educational technologies. Labs/Teams: Involved in developing the VR Computing Lab for immersive learning experiences and gamified platforms for foundational computing skills.

Braulio Alexandre Barreiraمشاهده پروفایل

دانشیار

• Digital Marketing
• Social Media
• Electronic Commerce
• +۳ مورد دیگر

Braulio Alexandre Barreira is an Associate Professor at the Department of Information Science and Technology at ISCTE - University Institute of Lisbon. He holds a PhD in Business Management and Organization (2005), a Master's in Management Information Systems (1995), and a Bachelor's in Business Management (1989), all from ISCTE. In 2023, he obtained habilitation in Information Sciences and Technologies. His research focuses on digital marketing, social media, information systems, and technology acceptance. He coordinates curricular units in Computer Science Applied to Management and Social Sciences, teaches in Master's and Postgraduate programs, and is affiliated with ISTAR-Iscte research center. Education: PhD in Business Management and Organization (ISCTE, 2005) Master's in Business Sciences (ISCTE, 1995) Bachelor's in Business Management (ISCTE, 1989) Research interests include digital transformation in healthcare, mobile application evaluation (ISO standards), and technology adoption in diverse sectors. His work spans articles on telemedicine apps, banking digitalization during the pandemic, and metaverse adoption. He collaborates with industry and academic partners, emphasizing practical solutions in information systems. Teaching roles include courses in Management, Computer Science in Business, Marketing Management, and Finance. He advises on organizational learning in hotels and agile IT service management using DevOps. His hobbies include tropical fish breeding, swimming, and diving.

Ladan Tahvildariمشاهده پروفایل

استاد

• Software Engineering
• Cloud Computing
• Self-Adaptive Systems
• +۵ مورد دیگر

Ladan Tahvildari is a Full-time Professor in the David R. Cheriton School of Computer Science at the University of Waterloo. Her research focuses on software engineering, self-adaptive systems, cloud computing, and test case prioritization. She leads the Software Technologies Applied Research Laboratory (STAR Lab), emphasizing hands-on industry collaboration and practical software solutions. Her work spans over two decades, with notable contributions to adaptive software systems, runtime adaptation frameworks (GRAF), and cloud modeling (StratusML/Adoop). She has pioneered techniques for flaky test detection (FlaKat), spatiotemporal auto-scaling (STaleX), and POMDP-based uncertainty management for security systems. Key research areas include: Self-protecting software systems Component-based software evolution Defect detection and prioritization Autonomic computing decision models Cloud infrastructure optimization Her recent work bridges academia and industry through hands-on learning approaches and frameworks like Semeru Cloud Compiler for performance enhancement. She has served as workshop chair for ACSOS 2023 and contributed to IBM tool integration in educational curricula. Her lab focuses on transforming theoretical concepts into practical tools like StarMX for self-managing systems and ReLACK for VoIP steganography. Current efforts emphasize adaptive machine learning frameworks and scalable microservice architectures.

Gabriele Bavotaمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Data Mining
• +۷ مورد دیگر

Gabriele Bavota is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a Laurea (cum laude) and PhD in Computer Science from the University of Salerno (2013). Before joining USI in 2016, he was an Assistant Professor at the Free University of Bolzano-Bozen (2014–2016) and a research fellow at the University of Sannio (2013–2014). Research Focus: Software maintenance, mining software repositories, empirical software engineering, and AI-driven code analysis. Awarded the 2018 ACM Sigsoft Early Career Researcher Award and leads the ERC Starting Grant project DEVINTA, exploring deep learning applications in software engineering. Authored over 180 publications in top venues like ICSE, FSE, and TOSEM, with multiple best/distinguished paper awards. His work bridges empirical studies, AI tools, and developer-centric solutions, addressing challenges in code quality, refactoring, and automated testing. He has served as program chair for ICPC 2016, SANER 2017, and ICSME 2023, and holds editorial roles in TSE, EMSE, and JSS. Labs/Teams: Principal Investigator of the DEVINTA project and part of the Software Institute at USI, fostering collaborations in AI, software engineering, and empirical research.

Taolue Chenمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Taolue Chen is a Senior Lecturer in the School of Computing and Mathematical Sciences at Birkbeck, University of London. He holds a PhD from Vrije Universiteit Amsterdam and MSc/BSc degrees from Nanjing University, China. His research focuses on neuro-symbolic software engineering, combining AI (Machine Learning/NLP) with formal methods in software engineering, program analysis, and verification. He has published extensively in top conferences like POPL, OOPSLA, and NeurIPS, and has received multiple awards including the ACM SIGSOFT Distinguished Paper Award (2024). Education: PhD: Centrum Wiskunde & Informatica (CWI) and Vrije Universiteit Amsterdam (2010s) MSc: Computer Science, Nanjing University (China) BSc: Computer Science, Nanjing University (China) Research Interests: Taolue's work bridges AI and traditional software engineering, with a focus on neuro-symbolic systems, code generation, adversarial robustness, and formal verification of cryptographic programs. He explores synergies between statistical (deep learning) and logical (constraint solving) methods to address challenges in software verification and cybersecurity. Articles Overview: His recent work emphasizes code generation improvements, adversarial defense mechanisms, and formal verification of secure cryptographic implementations. Key themes include enhancing model robustness, optimizing documentation in code generation, and applying large language models to symbolic reasoning tasks. Awards: Best Paper Award at SETTA’20 (2020) 1st Prize in CCF Software Prototype Competition (2022) QF Strings Competition Win (2023) ACM SIGSOFT Distinguished Paper Award (2024) Advising & Grants: Advises PhD student JEFERSON DORNELLES SCHNEIDER. His work is supported by grants focusing on neuro-symbolic systems, cybersecurity, and formal methods for software engineering. Labs/Teams: Leads research groups in neuro-symbolic software engineering and cryptographic verification at Birkbeck, collaborating with institutions like University of Oxford and University of Twente.

• Organization Development
• Quality Management
• Action Research
• +۲ مورد دیگر

Telmo Antonio Henriques is an Invited Assistant Professor at ISCTE-University Institute of Lisbon and a Research Associate at ISTAR-IUL. His academic work focuses on organization development, quality management, and methodologies like Action Research and Design Science Research within information systems. PhD : Information Science and Technology, ISCTE-IUL (2015) MSc : Business Management, Universidade Autónoma de Lisboa (2012) Research Interests He investigates organizational development, quality management, and action/design research methodologies, emphasizing employee engagement, leadership development, and IT organizational excellence. Publications Trends His work spans information systems, organizational behavior, and software engineering, with recent focus on DevOps maturity models, action research frameworks, and human-centric approaches to IT quality. Editorial Roles He serves as Associate Editor for the Journal of Global Information Management (since 2016) and Information Resources Management Journal (since 2016), and is on the editorial board of SAGE Open . Teaching & Advising As an Invited Assistant Professor, he teaches courses like Benefits Management and Information & Knowledge Technology Management , guiding Master's theses on topics including DevOps and systemic problem definition.

• Information Systems
• Data Science
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Sabrina Šuman is a Professor of Professional Studies at the University of Rijeka, Croatia. She teaches courses including Information Systems for Management, Decision Support Systems, Programming Basics, and IoT-related subjects. Her research focuses on Data Science, Artificial Intelligence, Cloud Computing, and Quality Management, with a strong emphasis on practical applications in education and business. She actively contributes to the development of IoT educational programs and cloud migration strategies. Her work spans database systems, sentiment analysis, and propaganda detection in digital contexts. She is affiliated with the Veleri-OI IoT School and has advised numerous projects in her field. Office hours are held on Monday and Thursday, and she coordinates student internships and professional practices. Her research interests include leveraging graph databases (Neo4j), analyzing customer behavior in travel agencies, and improving educational outcomes through IoT integration. She has published extensively on topics such as hierarchical clustering in education, cloud platform comparisons (AWS vs. OpenShift), and standards compliance in database systems. Her work often bridges theoretical models with real-world implementations, such as the Veleri-OI Meteo System web application. Key contributions include frameworks for knowledge-based data modeling, NLP-driven solutions for entity-relationship modeling, and methodologies for evaluating hotel reviews using sentiment analysis. She emphasizes practical educational tools and cloud migration guidelines for businesses, reflecting her dual focus on academic research and industrial application.

• Enterprise Systems Implementation
• Stakeholder Engagement
• Control Balancing
• +۴ مورد دیگر

Dr. Zafor Ahmed serves as an Assistant Professor of Information Systems Management within the Department of Finance, Information Systems, Economics, and Risk Management at the Marilyn Davies College of Business, University of Houston-Downtown. His expertise spans enterprise systems implementation, machine learning applications, and agile transformations in information systems. His educational qualifications include: Ph.D. in Management from Carleton University M.S. in Computer Science from Brock University B.S. in Computing and Business from Brock University Dr. Ahmed's research examines stakeholder engagement dynamics, control balancing mechanisms in offshore IS development, and machine learning applications for text classification in academic contexts. His work bridges theoretical frameworks with practical implementations, particularly in enterprise systems adoption and learning community analytics. He teaches core courses including Management of Information Systems, Project Management, and Python programming, emphasizing real-world applications of emerging technologies. Analysis of his publication trajectory reveals a consistent focus on integrating machine learning with information systems theory, particularly in analyzing online learning communities and agile transformations. His recent work demonstrates increasing sophistication in text mining methodologies applied to academic discussions and stakeholder communication patterns. His scientific recognition includes: MDCOB Research Award 2024 Dr. Ahmed actively mentors students through directed research projects, including supervision of Rahul Gopalan, Nehaa Balaji, and Krishnaraj Narayanan for the UH System Data Science and AI Showcase. He secured $5,569 in research funding as supporting investigator for an ORCA grant focused on organized research activities. His departmental leadership includes serving as Assistant Department Chair while maintaining active roles in curriculum development and faculty recruitment committees across multiple academic years. He maintains strong institutional engagement through continuous service on accreditation committees (including AACSB maintenance), scholarship boards, and research ethics oversight, demonstrating commitment to both academic excellence and institutional advancement.

• Artificial Intelligence in Education
• Data Governance
• Cybersecurity
• +۹ مورد دیگر

Syed Ali is a Senior Lecturer at the University of Houston-Downtown (UHD) College of Business, Department of Finance, Information Systems, Economics, and Risk Management. With over 30 years of experience in IT, criminal justice, and academia, his expertise spans leadership, data governance, ERP systems, cybersecurity, and generative AI applications in education. He has taught courses in Enterprise Architecture , Systems Analysis & Design , and Organizational Cybersecurity , emphasizing practical application and student-centered learning. Educational Background : MS in Computer Science (Pratt Institute), MS in Statistics (University of Sindh), BS in Math & Physics (University of Sindh) Ali’s research focuses on Artificial Intelligence in education , Data Privacy , and emerging technologies like Blockchain and Edge Computing . His recent publications highlight Generative AI’s impact on pedagogy , time management strategies , and data governance challenges . He actively participates in academic service, including committee roles on the Honors Committee and Wellness Committee , and professional development workshops on Generative AI and Cloud Security . Ali has received multiple awards for teaching excellence, including the 20 Years of Service Award and recognition for Active Learning and Inclusive Technology from UHD. His presentations at conferences like SWBATC and ICMLB explore the intersection of AI ethics , business intelligence , and student success through technology. Scientific Awards : 20 Years of Service Award, ACUE certifications for inclusive teaching, Best Lecturer Award nomination Ali’s work bridges academia and industry through consulting roles at Southwest Medical Services and Houston Police Department, focusing on IT strategy and data security. He continues to innovate with courses like Organizational Cybersecurity and Enterprise Architecture , while mentoring students in the MIS Tutoring Center and SOMIS organization.

Shekoufeh Kolahdouz Rahimiمشاهده پروفایل

پژوهشگر

• Software Engineering
• Model-Driven Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Shekoufeh Kolahdouz Rahimi is a researcher affiliated with the Centre for Research in Arts and Creative Exchange under the School of Arts, Humanities, and Social Sciences . Her work bridges academic disciplines through innovative research collaborations and publications. Research Focus: Integration of Large Language Models (LLMs) into software engineering practices, including Agile methodologies, Model-Driven Engineering (MDE), and formal verification of BPMN models. Conference Contributions: Active participation and organization in workshops like Agile MDE 2024 and Agile MDE 2025, with peer-reviewed publications in CEUR Workshop Proceedings. Academic Leadership: Peer-review roles for journals like Frontiers in Computer Science , and supervision of PhD research initiatives. Publication Trends: Recent work highlights the application of LLMs to automate tasks in software requirement engineering, game development, and MDE workflows. Her research emphasizes interdisciplinary collaboration, combining computational methods with creative arts frameworks.