Component-Based Software Professors and Supervisors | ApplySharif

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Yongjie ZhengView profile

Associate Professor

University of Southern MississippiUnited States

Yongjie Zheng is an Associate Professor at California State University, San Marcos (CSUSM) within the College of Science, Technology, Engineering and Mathematics (CSTEM). He earned his Ph.D. from the School of Information and Computer Sciences at the University of California, Irvine, under the mentorship of Professor Richard N. Taylor, and holds a Master's and Bachelor's in Computer Science from Hong Kong Polytechnic University and Tsinghua University, respectively. Education: Ph.D., University of California, Irvine (2012) M.S., Hong Kong Polytechnic University B.S., Tsinghua University His research focuses on software architecture , emphasizing architecture-implementation mapping for maintaining conformance during system evolution. He pioneered the 1.x-way mapping and 1.x-line mapping techniques, addressing challenges in single-system and product-line software development. Tools like xMapper and xLineMapper were developed to realize these approaches, applied to systems such as Apache Solr. His recent publications (2021–2004) span software conformance , product line engineering , mobile middleware , and automated mapping techniques , reflecting expertise in integrating broad disciplines like model-driven engineering and self-adaptive systems . Scientific Awards: SEKE 2020 Best Demo Award for xLineMapper Prof. Zheng mentors students across projects like Summer Scholars , engaging them in architecture-focused development and tool creation. His work bridges academic research and practical software solutions, emphasizing scalability and variability management in modern systems.

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Duncan WattsView profile

Researcher

University of OsloNorway

Duncan Watts is a Researcher at the University of Oslo’s Department of Astrophysics within the Faculty of Mathematics and Natural Sciences. He holds a PhD in Physics and Astronomy from Johns Hopkins University (2018) and a BA in Physics and Astronomy from Harvard College (2012). His primary research focuses on cosmology, the cosmic microwave background (CMB), and analyzing microwave emissions from the Milky Way to address fundamental questions about the universe. Watts is a key contributor to the Cosmoglobe project and the CMB&CO group, advancing Bayesian statistical methods for CMB analysis and end-to-end error propagation. He has also worked on the Cosmology Large Angular Scale Surveyor (CLASS) experiment, focusing on instrument calibration, polarization measurements, and foreground separation. His affiliations include the University of Oslo (2020–present) and Johns Hopkins University (2018–2020). Research interests span cosmological parameter estimation, CMB polarization, instrument design, and open science practices. Notable projects include reprocessing WMAP/Planck data for synchrotron emission models and constraining cosmic birefringence. Watts collaborates on initiatives like BeyondPlanck and LiteBIRD, emphasizing reproducible methodologies and data longevity. Publications emphasize CMB instrumentation, data pipelines, and Bayesian analysis, with recent works addressing atmospheric cloud polarization, bolometer performance optimization, and full-sky synchrotron modeling. His work bridges observational cosmology with computational techniques, aiming to refine CMB data interpretation and cosmological inference. Labs/teams: COSMOGLOBE, CMB&CO group, BeyondPlanck collaboration, and the COMAP project. Active in developing tools like ZodiPy for simulating zodiacal emission and improving CMB mapmaking algorithms through Gibbs sampling.

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Annabelle KlarlView profile

Researcher

Ludwig Maximilian University of MunichGermany

Annabelle Klarl is a Researcher in the Department of Computer Science at Ludwig-Maximilians-Universität München (LMU Munich). Her research focuses on ensemble-based software engineering, formal methods, and autonomous systems, particularly through the Helena framework. She is part of the Software and Computational Systems Lab (SoSy), contributing to modeling and verifying distributed systems. Her work emphasizes rigorous ensemble architectures, dynamic component collaboration, and executable code generation. Key projects include ASCENS (Autonomic Service-Component Ensembles) and the Helena framework, which enables formal modeling and verification of ensemble systems. She has published extensively on topics like ensemble specifications, model-checking, and distributed system design. Her research bridges theoretical foundations with practical tools, such as the jHelena execution framework and HelenaText domain-specific language. Collaborations with Prof. Rolf Hennicker and others highlight her role in advancing ensemble-based software engineering.

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Andrew HillsView profile

Research Fellow

University of SheffieldUnited Kingdom

Dr Andrew Hills is a Research Fellow in the School of Electrical and Electronic Engineering at the University of Sheffield. His work spans interdisciplinary research areas including aerospace engineering, biomedical engineering, and data analytics. He specializes in developing innovative solutions for health monitoring, predictive maintenance, and medical decision support systems. Key research interests include: Wireless sensor networks for industrial applications Ultrasonic testing of infrastructure materials Machine learning-driven risk prediction models in healthcare Condition monitoring of gas turbine and wind turbine components His recent articles highlight contributions to personalized joint replacement decision tools (JointCalc), survival analysis methodologies in orthopaedic surgery, and advanced diagnostic systems for aerospace propulsion systems. These works demonstrate his ability to bridge engineering and medical domains. Dr Hills' research has been applied to critical infrastructure sectors including aerospace propulsion systems, civil engineering pipelines, and orthopaedic healthcare. He collaborates across disciplines to address real-world challenges in both technical and clinical contexts.

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Ivan KurtevView profile

Associate Professor

Eindhoven University of TechnologyNetherlands

Ivan Kurtev is an Associate Professor in Mathematics and Computer Science at Eindhoven University of Technology, specializing in software engineering and model-driven technologies. His research develops formal methods for software interface specification, component-based systems, and domain-specific languages. Recent work (2022-2024) focuses on adaptable runtime monitoring and robotics controller synthesis. Earlier contributions established foundations for model transformation languages (ATL/QVT) and requirements change management. He leads research on the INTERSECT project integrating formal methods for IoT systems.

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Jan BroeninkView profile

Associate Professor

University of TwenteNetherlands

Jan Broenink is an Associate Professor at the University of Twente, affiliated with the Robotics and Mechatronics group within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). He serves as Programme Director of the MSc Robotics programme since July 2021 and previously chaired the Robotics and Mechatronics group (2017–2021). He holds a PhD and MSc in Electrical Engineering (EE) and biomedical degrees from the University of Twente. His research focuses on Cyber-Physical Systems, Systems Engineering, Robot Software Architectures, and Tools Development. Key interests include model-driven design, meta-modelling, simulation, co-simulation, and concurrent engineering. He develops software tools for robotics, emphasizing real-time computing and embedded control systems. Teaching encompasses Robot Software Design using Model-Driven approaches, Systems Engineering, and project supervision for MSc/BSc students. His work contributes to UN SDGs related to Industry and Future of Work, and Social and Daily Life. Broenink has supervised 9 student works and is active in conferences, presenting on topics like co-design methodologies and bond graph frameworks. His 162+ research outputs span embedded systems, robotics, and simulation tools.

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Sue ChngView profile

Academic

University of SydneyAustralia

Dr. Sue Chng is an Associate Lecturer at the School of Computer Science, The University of Sydney. Her research focuses on computer science education, e-learning technologies, artificial intelligence, and computer vision. She has contributed to improving teaching methodologies through reflective practices, chatbot integration in courses, and hybrid learning models for large undergraduate classes. Her work also spans algorithm design for route optimization, sensor networks, and face recognition systems. Research Interests: Educational Technology: Developing innovative tools like chatbots for FAQ systems and hybrid learning frameworks. Computer Vision: Advancing face recognition algorithms and super-resolution imaging techniques. Algorithm Design: Optimizing pathfinding and route planning under constraints. Publications Overview: Dr. Chng has published in venues such as IEEE conferences and journals like Reflective Practice . Her recent work emphasizes the intersection of education and technology, alongside technical advancements in image processing and algorithmic efficiency. Awards: None listed. Advising & Grants: No advising records or grants mentioned. Her contributions are primarily through publications and teaching innovations. Labs/Teams: No specific lab affiliations noted in the provided text.

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Stephan KleukerView profile

Professor

Osnabrück University of Applied SciencesGermany

Prof. Dr. Stephan Kleuker is a faculty member at Osnabrück University of Applied Sciences , specifically within the Faculty of Engineering and Computer Science . He focuses on Software Development , Quality Assurance , and Theoretical Computer Science , with a particular interest in formal methods and practical software engineering education. Role: Chair of Software Development Contact: s.kleuker@hs-osnabrueck.de | Phone: 0541 969 3884 Research Interests Quality Assurance through Testing and Model Checking Formal Methods in Software Development Model-Driven Development and UML Business Process Modeling and Optimization Integration of Requirements Analysis with Quality Measures Teaching Current courses: Object-Oriented Analysis and Design, Software Quality Management, Theoretical Computer Science Focus on practical software development education with tools like Eclipse, Netbeans, and Apache Derby Projects Developed environments for teaching (e.g., 2 GB SEU package) Research on test automation, requirements modeling, and distributed Java programs Tools & Publications: Creator of tools like Interaction Board for Java beginners, and author of textbooks on Software Engineering with UML and Quality Assurance through Software Testing .

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Alexander WiebelView profile

Professor

Worms University of Applied SciencesGermany

Dr. Alexander Wiebel is a Professor of Visual Computing at Hochschule Worms University of Applied Sciences, where he also serves as Scientific Director of the Center for Technology and Transfer (ZTT). He co-founded the User Experience & Visualization (UX-Vis) research group and the Interdisciplinary Center for Digital Experience Design (IZEd). His expertise spans visual data analysis, AR/VR systems, and medical visualization. Education: PhD in Computer Science (2008) from University of Leipzig, Diplom-Informatik (2004) from TU Kaiserslautern, and secondary education at Gymnasium am Römerkastell, Alzey. Research focuses on interactive visualization systems, machine learning integration in visualization, and applications in healthcare and education. He has over 75 publications, including work on proton CT systems, motor skill training via AR, and modular educational resources for computer graphics. Leadership roles include membership in GI, Hlb, and Chaos Computer Club. Active in program committees for EuroVis, BioVis, and IEEE Visualization conferences. Supervised over 60 bachelor's, 20 master's, and multiple PhD students. Labs include the Visual Computing Lab (N-144) and contributions to OpenWalnut visualization software. Projects include SkillXR (AR-based physiotherapy), SIVERT (medical imaging tech), and ExGOER (OERs in computer graphics).

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Jigish ZaveriView profile

Professor

Morgan State UniversityUnited States

Dr. Jigish Zaveri is a Professor and Interim Department Chair in the Information Science & Systems Department at Morgan State University's Earl Graves School of Business and Management. He holds a Ph.D. in Management Information Systems from the University of Kentucky and degrees in Chemical Engineering from the University of Kentucky and Indian Institute of Technology. His research focuses on information systems security, healthcare informatics, decision support systems, and pedagogical strategies in IT education. Education: Ph.D. Management Information Systems (1992), University of Kentucky M.S. Chemical Engineering (1988), University of Kentucky B.Tech. Chemical Engineering (1985), Indian Institute of Technology Research Interests: Information Systems Security & Assurance Healthcare Information Systems Knowledge Management Decision Science & Artificial Intelligence IT Governance & Regulatory Compliance Pedagogy in STEM Education His recent work explores cyber risk assessment frameworks, SOX Act implications on IT governance, and gender diversity in technology sectors. He has secured grants from agencies like the Department of Homeland Security and National Security Agency, contributing to projects such as emergency management systems and transportation cybersecurity. Advising & Grants: Served as dissertation committee chair/coordinator Lead researcher on over $15M Homeland Security grant (2009) Collaborated with Johns Hopkins Applied Physics Lab on emergency response systems

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Md Tajmilur RahmanView profile

Assistant Professor

Gannon UniversityUnited States

Md Tajmilur Rahman is an Assistant Professor in the Department of Computer and Information Science at Gannon University , Erie, Pennsylvania, USA. His research focuses on software maintenance, evolution, architecture , and the application of AI and Large Language Models to improve software development practices. He has contributed to understanding feature toggle architectures and their impact on software systems. Education : PhD in Software Engineering from Concordia University (2018), supervised by Dr. Peter Rigby. Research Interests : Software Maintenance, Feature Toggles, Release Engineering, Software Architecture, AI in Software Engineering. Teaching : Courses include Software Testing, Software Maintenance, Software Architecture, Data Analysis, and Mobile Application Development at both undergraduate and graduate levels. Professional Service : Organizing Co-Chair for ACM Student Research Competition at ICSE 2025, Program Committee member for ESEC/FSE 2022, and Chair of IEEE Erie Section (2022-2024). Community Involvement : Strategic Planning Committee member at L’Arche Erie. Publications highlight empirical studies on feature toggles in Google Chromium, predictive analysis of software quality, and tool development for automated user story generation. His work bridges academic research with industry practices, particularly in release engineering and architectural growth control. Industry Experience includes senior software engineering roles at Morgan Stanley and PBSC Urban Solutions, focusing on back-end development, CI/CD implementation, and architectural decision-making.

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Panagiotis KotsampopoulosView profile

Lecturer

National Technical University of AthensGreece

Panagiotis Kotsampopoulos is a Principal Researcher at the Institute of Communication and Computer Systems (ICCS) and an Adjunct Lecturer at the School of Electrical and Computer Engineering (ECE-NTUA), National Technical University of Athens (NTUA). He leads the Smart RUE research group at ICCS-NTUA since 2009 and is a founding member of the international DERlab association. His work focuses on smart grids, distributed energy resources (DER), and microgrid technologies, with significant contributions to hardware-in-the-loop (PHIL) laboratory development and real-time simulation methodologies. Education includes a Diploma (2010) and PhD (2017) in Electrical and Computer Engineering from NTUA, and a graduate degree in Education from the University of Athens (2020). He has coordinated major EU projects like RE-EMPOWERED (H2020) and APEX, securing over €10M in research funding. His teaching roles include lecturing on power system analysis and developing hands-on laboratory exercises for ECE-NTUA courses. Research interests span power system dynamics, microgrid control, and engineering education innovation. He chairs the IEEE PES Task Force on 'Innovative Teaching Methods' and contributes to IEEE standards development (e.g., P2004). He has authored 36 journal articles, 9 book chapters, and over 37 conference papers, delivering 50+ invited lectures globally. Professional activities include membership in CIGRE, IEEE (Senior Member), and the Technical Chamber of Greece. He co-founded the energy community 'Collective Energy' (COEN) and leads initiatives promoting energy communities and green transitions in EU geographical islands.

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Derek CovillView profile

Senior Lecturer

University of BrightonUnited Kingdom

Dr. Derek Covill is a Senior Lecturer at the University of Brighton, affiliated with the School of Architecture, Technology and Engineering and the Advanced Engineering department. He holds roles as Principal Lecturer and serves as an External Examiner for multiple universities, including Robert Gordon University and Sheffield Hallam University. His academic journey includes a BEng in Medical Engineering from Queensland University of Technology and a PhD in Engineering from the University of Brighton. Dr. Covill’s research spans sports engineering, additive manufacturing for medical devices, digital fabrication tools, and engineering education. Notable projects include the Steel Bicycle Project exploring frame design and the development of electrochemical sensors for biomedical applications. He has collaborated with industries like Clarks International and OSET Bikes through Knowledge Transfer Partnerships (KTPs). His recent publications focus on dyslexic student support in design education, bicycle dynamics optimization, and learning analytics tools. Dr. Covill has advanced degrees in Data Analytics (MSc, 2026), an MBA (2023), and a Postgraduate Certificate in Teaching and Learning in Higher Education (2007). His external roles include examiner positions across product design and engineering programs.

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Sanjay ChaudhuriView profile

Associate Professor

University of Nebraska-LincolnUnited States

Sanjay Chaudhuri is an Associate Professor in the Department of Statistics at the University of Nebraska-Lincoln (UNL). He previously held positions at the National University of Singapore (2005–2023) and earned his Ph.D. from the University of Washington (2005), under Professors Michael D. Perlman and Thomas S. Richardson. His research focuses on empirical likelihood, Bayesian methods, high-dimensional data analysis, and applications in demography, network data, and machine learning. Education: B.Stat and M.Stat from the Indian Statistical Institute (1998–2000), Ph.D. in Statistics from the University of Washington (2005). Research Interests: Empirical likelihood, statistical data integration, Bayesian empirical likelihood, graphical Markov models, covariance estimation, causality, approximate Bayesian computation (ABC), and applications in natural, engineering, and marketing sciences. Teaching: Advanced Topics in Applied Statistics, Statistical Models, Applied Regression Analysis, Design of Experiments, and courses on graphical models, data science, and linear models. Software Contributions: Developer of R packages glmc (combining sample/population data), ES (edge selection), elhmc (Hamiltonian Monte Carlo sampling), and Anhysnuc (analyzing nucleic acid thermal curves). Grants & Collaborations: Active in interdisciplinary projects involving statistical methods for complex data, including pandemic dynamics, thermal curve analysis, and environmental statistics. Labs/Teams: Leads the development of Anhysnuc , a web-based tool for analyzing irreversible thermal curves from nucleic acid hybridization experiments.

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Philip FergusonView profile

Associate Professor

University of ManitobaCanada

Dr. Philip Ferguson is an Associate Professor of Mechanical Engineering and Magellan Industrial Research Chair at the University of Manitoba's Price Faculty of Engineering. He leads the Space Technology and Advanced Research Laboratory (STARLab) and collaborates with the Centre for Earth Observation Science (CEOS). His work focuses on making aerospace technology accessible through low-cost, reliable solutions for Arctic communities and search-and-rescue operations. Dr. Ferguson holds a PhD from MIT and has industry experience with Magellan Aerospace and PrecisionHawk Inc. Education: PhD in Aerospace Engineering, MIT (2006) SM in Aerospace Engineering, MIT (2003) B.A.Sc. in Engineering Science (Aerospace Option), University of Toronto (2000) Dr. Ferguson's research spans satellite guidance, drone navigation, Arctic remote sensing, and machine learning. His projects include CubeSats for climate change monitoring, drones for search-and-rescue, and airships for Arctic communications. He emphasizes interdisciplinary collaboration to address challenges in Northern Canada and Indigenous communities. His recent articles explore fault detection in spacecraft systems, drone-based payload control, and innovative navigation algorithms. He actively recruits graduate students interested in advancing aerospace accessibility. Labs/Teams: STARLab (founded 2014), CEOS collaborations, and industry partnerships with Magellan Aerospace.

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