جست‌وجوی استاد و پژوهشگر

Willi Rathمشاهده پروفایل

پژوهشگر

• Ocean Dynamics
• Marine Data Science
• Lagrangian Methods
• +۷ مورد دیگر

Willi Rath is a Data Scientist at the GEOMAR Helmholtz Centre for Ocean Research in Kiel, Germany, with a focus on Ocean Dynamics. His research bridges marine science and data science, emphasizing Lagrangian methods, air-sea interactions, and biophysical simulations. Rath holds a PhD in Oceanography from Christian-Albrechts-Universität Kiel (2013) and a Diploma in Physics from Humboldt-Universität Berlin (2009). His work spans interdisciplinary collaborations, leveraging machine learning and geospatial analysis to address climate dynamics, disease dispersal in marine ecosystems, and oceanic current variability. Key projects include WarmWorld ELPHE , MarDATA , and OceanParcels , which integrate data science with ocean modeling for climate prediction and marine resource management. Rath’s recent publications highlight his contributions to understanding the Atlantic Meridional Overturning Circulation (AMOC), tropical Atlantic wind forcing, and deep-sea larval connectivity. His methodology incorporates advanced computational tools like echo state networks and metamorphic testing to enhance model transparency and reliability in climate research.

Miguel Andradeمشاهده پروفایل

استاد

• Bioinformatics
• Protein Sequence Analysis
• Tandem Repeats
• +۳ مورد دیگر

Miguel Andrade is a Professor in the Faculty of Biology at the University of Mainz and serves as Adjunct Director at the Institute of Molecular Biology (IMB) since 2014. Previously, he was a Group Leader at the Max Delbrück Center for Molecular Medicine (2007-2014) and Assistant Professor at the University of Ottawa (2003-2007). His research focuses on computational analysis of protein sequences, particularly tandem repeats and low complexity regions, with applications in neurodegenerative diseases like Huntington's. His educational background includes: PhD in Biochemistry from Universidad Complutense de Madrid (1994) Professor Andrade's research spans bioinformatics and computational biology with emphasis on protein sequence evolution, structural implications of repetitive elements, and development of analytical tools. He investigates how tandem repeats and low complexity regions influence protein folding, aggregation, and interactions in diseases, while exploring evolutionary conservation across species. His work bridges computational methodologies with experimental validation in neurodegenerative contexts. Recent publications (2023-2025) demonstrate consistent innovation in protein sequence analysis, featuring computational tools for homorepeat detection, machine learning applications in proteomics, and multi-omics integration. Key themes include neurodegenerative disease mechanisms, immune system regulation, and evolutionary adaptations, with significant contributions to databases like RepeatsDB and tools such as REP2 and seqQscorer. No scientific awards were documented in the source materials. While specific student names and grant details are unlisted, his leadership at IMB indicates supervision of graduate researchers and postdoctoral fellows. His collaborative network spans immunology, cancer research, and neuroscience, evidenced by co-authorship on diverse projects from lipid-disease associations to T-cell differentiation studies. He directs a research group at IMB Mainz focused on computational genomics, developing algorithms for protein sequence analysis and maintaining community resources. The team actively investigates polyglutamine dynamics in neurodegeneration and applies machine learning to proteome-wide challenges, maintaining strong ties with experimental laboratories for biological validation.

• Database Systems
• In-Database Machine Learning
• GPU Acceleration for Databases
• +۳ مورد دیگر

Maximilian Schüle serves as Assistant Professor in the Department of Data Engineering at the University of Bamberg's Faculty of Information Systems and Applied Computer Sciences since October 2022. Previously, he held research positions at Technical University of Munich (2017-2022). His research bridges database systems and machine learning through compiler-based approaches. His research focuses on in-database machine learning , GPU-accelerated query processing , and recursive SQL extensions . Key contributions include: Developing MLIR-based compilers for automatic differentiation in SQL (DuoLingo-AutoDiff) Creating GPU code generators for database kernels using NVRTC Designing higher-order lambda functions for expressive query languages Implementing end-to-end neural network training within database engines His recent publications (2023-2025) demonstrate consistent output in top venues including ICDE, VLDB workshops, and BTW conferences, with growing emphasis on hardware-aware optimization and compiler techniques for analytical workloads. He currently leads a DFG-funded project on elastic memory hierarchies for memory-intensive applications (2025-2028), supporting multiple PhD researchers. His supervision emphasizes open-source contributions to database systems like Umbra and practical implementation skills alongside theoretical foundations. As an active member of the database community, he serves as workshop chair for BTW 2025 and regularly reviews for ACM TODS, VLDB Journal, and Information Systems. His work on public transport analytics demonstrates real-world impact through collaborations with urban mobility initiatives in Bamberg.

• Chemical Engineering
• Reaction Engineering
• Olefin Oligomerization
• +۳ مورد دیگر

Steffen Cramer is a Research Associate at the Chair of Reaction Engineering within the Institute of Energy Process Engineering and Chemical Engineering at TU Bergakademie Freiberg, where he has worked since 2022. He holds a Master of Science in Chemistry from Carl von Ossietzky University of Oldenburg, completed in 2022. His research focuses on: Olefin oligomerization for alternative fuel production Deactivation mechanisms of heterogeneous catalysts Analytical methods including gas chromatography No awards, student advisements, or publications are detailed in the source material. He can be contacted at steffen.cramer@iec.tu-freiberg.de .

Klaus Chantelauمشاهده پروفایل

استاد

• Image Processing
• Video Analysis
• Digital Media Standards
• +۳ مورد دیگر

Professor Klaus Chantelau is a faculty member at Schmalkalden University of Applied Sciences, specializing in Applied Digital Image Processing within the Faculty of Computer Science. He maintains his office in Building F, Room 0205, with office hours held every Thursday from 12:00-13:00. Professor Chantelau teaches a diverse range of courses including Peripheral Systems, Digital Media Standards, Image Processing, Selected Chapters of Image Processing, Image Search Engines, and Model-Based Coding for Computer Science students, while also teaching Modeling, Simulation and Visualization for Business Informatics students. His research primarily focuses on image and video analysis, with his current project GraVis (Graph-based descriptors for describing people in videos) representing cutting-edge work in video analytics. Professor Chantelau leads the Video, Audio and Graphics Laboratory (F 0206), providing essential facilities for practical work in digital media processing. He also serves as Program Coordinator for the Master's program in Applied Media Informatics, demonstrating his leadership within the academic community. With a strong academic foundation including a Diploma in Physics (1988) and Doctorate in Mathematics (1991) from TU Berlin, followed by seven years as a Research Associate at the Heinrich Hertz Institute for Communications Technology Berlin GmbH, Professor Chantelau brings substantial expertise to his teaching and research activities.

Robert Haaseمشاهده پروفایل

مدرس

• Bioimage Analysis
• Medical Informatics
• GPU-Accelerated Image Processing
• +۶ مورد دیگر

Dr. Robert Haase is a Lecturer and Training Coordinator at the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) under Leipzig University , with prior leadership roles at the DFG Cluster of Excellence 'Physics of Life' at TU Dresden . He specializes in Bioimage Analysis , GPU-Accelerated Image Processing , and Large Language Models (LLMs) for life sciences. His research focuses on democratizing bioimage analysis through open-source tools like CLIJ , clesperanto , and bia-bob , aiming to bridge microscopy with data science . Recent projects explore LLM-driven code generation for image analysis and interactive workflow design in platforms like napari . He leads initiatives such as the NFDI4BioImage consortium for research data management in Germany and GloBIAS , a global society for bioimage analysts. Funded by organizations including the Chan Zuckerberg Initiative (CZI) and DFG , his work emphasizes reproducibility , open science , and interdisciplinary collaboration in bioimaging. As an educator, he conducts training programs like "Large Language Models for Bioimage Analysis" and "Collaborative Working with Git" , and contributes to workshops at institutions such as EMBO , Institut Pasteur , and ScaDS.AI Summer Schools .

Sridhar Chimalakondaمشاهده پروفایل

دانشیار

• Software Engineering
• Educational Technologies
• Human Computer Interaction
• +۱۱ مورد دیگر

Dr. Sridhar Chimalakonda serves as Associate Professor and Head of the Department of Computer Science & Engineering at the Indian Institute of Technology Tirupati, with an adjunct appointment as Associate Professor at the University of Waterloo. His academic leadership spans software engineering research and educational innovation. His educational qualifications include: Ph.D. from International Institute of Information Technology Hyderabad, India MS by Research from International Institute of Information Technology Hyderabad, India Research expertise encompasses: Software Engineering : Empirical studies, quality assurance, reuse methodologies, product lines, architecture, ontologies, and gamification Educational Technologies : Instructional design optimization, personalized learning systems, and VR/AR applications for educational storytelling and laboratories Human Computer Interaction : User-centered design in educational and software development contexts Publication analysis (2021-2024) reveals a strategic evolution from foundational software engineering research toward integrated educational applications, particularly in gamified machine learning education for K-12 audiences and sustainable software practices. His work demonstrates consistent methodological rigor in empirical studies while expanding into cross-disciplinary educational technology innovation.

Eunjong Choiمشاهده پروفایل

دانشیار

• Software Engineering
• Software Maintenance/Evolution
• Program Comprehension
• +۴ مورد دیگر

Eunjong Choi is an Associate Professor at the Faculty of Information and Human Sciences, Kyoto Institute of Technology in Japan. She joined Kyoto Institute of Technology as a tenure-track assistant professor in 2019 and was promoted to associate professor in March 2024. Prior to this position, she served as an assistant professor at Nara Institute of Science and Technology (April 2016-March 2019) and at Osaka School of International Public Policy, Osaka University (April 2015-March 2016). Kyoto Institute of Technology (2019-Present) Nara Institute of Science and Technology (2016-2019) Osaka University (2015-2016) Dr. Choi's research focuses on software engineering with particular emphasis on software maintenance and evolution, program comprehension, software analytics, reused code management and detection, refactoring support, and test code generation. Her work bridges theoretical software engineering concepts with practical applications in industrial settings. She has investigated topics such as token-level SZZ algorithms, deep learning-based clone detectors, and modernization of large-scale industrial systems. Dr. Choi has held significant leadership roles in major software engineering conferences including serving as General Chair for ICPC 2020 and IWESEP 2017, Publicity Co-Chair for ICSE 2020, and Local Arrangement Co-Chair for SANER 2016. She has been actively involved in the IEEE Kansai Section Woman in Engineering Affinity Group, serving as Secretary (2016-2017) and Vice-Chair (2018-2021). Her teaching portfolio includes Software Mining and Analysis, Software Metrics, and Software Engineering courses at Kyoto Institute of Technology; Software Design and related courses at Nara Institute of Science and Technology; and Basic Information Literacy at Osaka University. Dr. Choi earned her Ph.D. in Information Science and Technology from Osaka University in 2015 and maintains an active research profile in the software engineering community.

Andrew Begelمشاهده پروفایل

دانشیار

• Software Engineering
• Human-Computer Interaction
• Accessibility
• +۳ مورد دیگر

Andrew Begel is an Associate Professor in the Software and Societal Systems Department at Carnegie Mellon University's School of Computer Science. Previously, he was a Principal Researcher at Microsoft Research from 2006 to 2022. He received his Ph.D. in Computer Science from the University of California at Berkeley and holds a Master of Engineering from MIT. Dr. Begel is internationally recognized for his pioneering research on cooperative and human aspects of software engineering, combining empirical studies of professional software engineers with organizational behavior. His work focuses on accessibility, neurodiversity, and human-computer interaction, with particular emphasis on creating more inclusive technology workplaces. He was the first to study emotions in software engineering and conducted groundbreaking research on autistic software developers, identifying their unique strengths and challenges. His research portfolio shows a clear trajectory toward understanding human factors in software development, with increasing focus on neurodiversity and accessibility. Early work examined code comprehension through eye tracking and fMRI studies, while recent publications focus on creating inclusive environments for autistic software engineers and developing tools that support mixed-ability collaboration. His work spans empirical software engineering, human-computer interaction, and accessibility research, often bridging these domains to address real-world challenges in software development environments. Best Paper Award — SIGCSE (2021) ACM Distinguished Member (2019) Best Paper Honorable Mention Award — CSCW (2019) Best Paper Award — ICSE, Software Engineering In Practice (2019) Most Influential Paper Award (10 Years) — ICER (2019) Best Paper Honorable Mention Award — CHI (2017) Dr. Begel has been deeply involved in academic service, organizing and serving on program committees for top software engineering conferences. He has run FSE and ICSE's ACM Student Research Competitions and ICSME's Doctoral Symposium. He created the Autism at Work Research Workshop series, bringing together researchers, practitioners, and autism self-advocates to help autistic engineers find and keep jobs. As a member of Microsoft's AI Ethics Board, he contributed to disseminating best practices for responsible AI engineering. His teaching includes courses at the University of Washington's iSchool and coding camps for autistic youth. Dr. Begel leads the Autism at Work Research Workshop series and has established himself as a prominent figure in creating more inclusive environments for neurodiverse software engineers. His work bridges academic research with practical applications in industry settings, particularly through his collaborations with Microsoft and other technology companies.

Amiangshu Bosuمشاهده پروفایل

دانشیار

• Empirical Software Engineering
• Code Reviews
• Software Security
• +۸ مورد دیگر

Amiangshu Bosu is a tenured Associate Professor in the Department of Computer Science at Wayne State University's College of Engineering. Previously, he served as a tenure-track Assistant Professor at Southern Illinois University Carbondale from 2016-2018. His academic journey includes completing his Ph.D. at the University of Alabama in 2015 under Professor Jeffrey Carver, followed by postdoctoral research with Dr. Danfeng Yao at Virginia Tech. His educational background reflects a strong foundation in software engineering research, with his doctoral work focusing on empirical approaches to software development practices. This foundation has enabled his current research trajectory examining human aspects of software engineering. Bosu's research program centers on empirical software engineering with particular emphasis on code review dynamics, toxicity detection in developer communications, and diversity issues in open source communities. His work bridges technical analysis with social science perspectives, investigating how communication patterns affect participation, especially regarding gender dynamics in OSS projects. Recent work increasingly incorporates natural language processing and machine learning techniques to build tools like ToxiCR for automated toxicity detection in code reviews. Analysis of his publication record reveals a clear evolution toward examining social dynamics in software development, with growing emphasis on gender bias, toxicity, and diversity issues. His research consistently applies empirical methods to understand real-world developer experiences while developing practical tools to improve code review processes and community health. His scientific recognition includes the prestigious NSF CAREER award (2024), NSF CRII award (2019), and Wayne State University's College of Engineering Research Excellence award (2025). He maintains senior membership status in both ACM and IEEE, reflecting his standing in the computing community. NSF CRII award (2019) NSF CAREER award (2024) College of Engineering Research Excellence award (2025) Senior Member of ACM Senior Member of IEEE Bosu actively contributes to the software engineering research community through service on program committees for major conferences including ICSE, ASE, ESEC/FSE, and ESEM. His GitHub presence (amiangshu.me) demonstrates active engagement with research tools and datasets, particularly those related to code review analysis and toxicity detection. While specific lab structure isn't detailed in the provided materials, his research group appears focused on empirical studies of software development practices with strong connections to industry through collaborations on projects like Chromium OS security analysis.

Yu Fengمشاهده پروفایل

دانشیار

• Programming Languages
• Program Synthesis
• Program Analysis
• +۳ مورد دیگر

Yu Feng is an Associate Professor in the Computer Science Department at the University of California, Santa Barbara. He received his Ph.D. in Computer Science from the University of Texas at Austin in 2018 and his MS in Computer Science from Beihang University in 2008. His research focuses on programming languages, program analysis and verification, program synthesis, and security. Specifically, he aims to build automated tools that guarantee the desired behavior of systems in a sound, precise, and scalable way. He is particularly interested in applying program synthesis and analysis to tackle security and performance problems in mobile devices and blockchain applications. Professor Feng's recent publications demonstrate a strong focus on program synthesis for security applications, particularly in blockchain and zero-knowledge proofs. His work spans multiple top-tier conferences including PLDI, POPL, ASE, and CCS, showing consistent contributions to both programming languages and security communities. His research often combines logical reasoning with machine learning techniques to develop innovative solutions for complex problems in program analysis and synthesis. Ethereum Academic Award (2025, 2024, 2023) ACM SIGPLAN Distinguished Paper Award, PLDI 2022 ACM SIGCHI Best Paper Award, CHI 2021 Google Faculty Research Award (Security), 2021 ACM SIGSOFT Distinguished Paper Award, ASE 2020 DARPA HARDEN grant (2022-2025) NSF-SaTC grant (2019-2022) ACM SIGPLAN Distinguished Paper Award, PLDI 2018 Professor Feng actively mentors students in his research group, currently advising several PhD students including Yanju Chen, Junrui Liu, Hongbo Wen, and Hanzhi Liu. He has served on program committees for numerous top conferences including CCS, PLDI, OOPSLA, ICSE, ASPLOS, and POPL. His research is supported by prestigious grants including DARPA HARDEN and NSF-SaTC. His laboratory focuses on developing cutting-edge program synthesis and analysis frameworks that combine logical reasoning with machine learning. The team works on applications in blockchain security, zero-knowledge proofs, and secure protocol implementation.

Yun Linمشاهده پروفایل

دانشیار

• Automatic programming
• Software debugging
• Software testing
• +۸ مورد دیگر

Yun Lin is an Associate Professor and Deputy Head of the Department of Computer Science and Technology at Shanghai Jiao Tong University's School of Computer Science. Prior to joining SJTU, Lin served as a Research Assistant Professor at the National University of Singapore working with Prof. Dong Jin Song. Lin leads the CoPhi ("Code Philia") research group, which focuses on the intersection of Software Engineering, AI, and Security. Lin's research spans three major areas: Automatic Programming (including code editing, software testing, and debugging), Explainable AI (focusing on representation interpretation and training data attribution), and Web Misinformation (particularly phishing and scam detection). The research has resulted in numerous tools including CoEdPilot for code editing recommendation, DeepDebugger for interactive debugging of deep classifiers, and Phishpedia for phishing webpage detection. Lin's recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models and vision language models, with traditional software engineering and security tasks. The work shows increasing sophistication in understanding project context, handling interactive nature of programming tasks, and addressing security challenges in the age of generative AI. Key themes include consistency-based approaches for anomaly detection, agent-based frameworks for complex tasks, and hybrid models that combine symbolic reasoning with neural approaches. ACM Distinguished Paper Award in ICSE'18 for "Towards Optimal Concolic Testing" Distinguished Reviewer Award in FSE'25 2nd prize Research Prototype Award in ChinaSoft'24 Lin advises a large team of PhD, Master's, and undergraduate students, with several publications co-authored with students appearing in top venues. Current research is supported by collaborations with National University of Singapore, particularly with Prof. Dong Jin Song, and includes projects on code editing, GUI testing, and phishing detection. The CoPhi group maintains active development of multiple research tools and datasets. The CoPhi research group under Lin's leadership focuses on building practical tools that bridge the gap between theoretical advances and real-world programming and security challenges. The group's work spans from fundamental program analysis techniques to applied security solutions, with an increasing emphasis on leveraging AI capabilities while maintaining explainability and reliability.

• Reconstructive Approaches in Social Work
• Ethnography and Qualitative Research Methods
• Biography and Interaction Analysis
• +۷ مورد دیگر

Professor Michael Appel serves as a Professor of Theories, Action Concepts and Methods of Social Work at the Evangelische Hochschule Nürnberg since October 2009. His academic career bridges practical social work experience with rigorous research methodologies, having previously worked as Scientific Coordinator of Teaching-Learning Research at the University of Siegen until September 2009. Professor Appel maintains strong connections to both academic research and practical social work settings through his methodological expertise and applied research projects. Professor Appel's research focuses on reconstructive approaches in Social Work, with particular emphasis on ethnography, biography analysis, and qualitative research methods. His work explores intercultural Social Work, integration processes of unaccompanied refugee minors, and cultural change studies. He has developed innovative approaches to research-based, discovery learning that integrate theory, practice, and reflection in social work education. His methodological contributions span narrative interviewing techniques, ethnographic field research, and biographical analysis frameworks. Professor Appel's publication record demonstrates consistent scholarly output across two decades, with recent work concentrating on refugee integration processes and methodological innovations in qualitative social work research. His 2021-2019 publications address critical issues in biographical work with refugee minors and the challenges faced by refugees aging out of youth care systems. His research shows a clear trajectory from earlier work on youth work quality management to current focus areas in refugee integration, maintaining consistent methodological rigor throughout. Professor Appel's advising approach emphasizes reconstructive knowledge building through ethnographic approaches in case-based learning contexts. His research projects often involve collaborative work with students and practitioners, creating opportunities for hands-on research experience. His work on the WANJA project and current refugee integration studies demonstrate his commitment to research that directly informs and improves social work practice. He has developed frameworks for effectiveness dialogue in youth work and quality management systems that have practical applications in social service settings. Professor Appel leads research initiatives focused on integration processes of unaccompanied refugee minors, employing biographical analytical methods and ethnographic approaches. His work combines academic rigor with practical relevance, maintaining strong connections to social work practice settings while advancing methodological approaches in qualitative social research. His research group collaborates with youth welfare services and refugee support organizations to ensure practical applicability of research findings.

Hung Hoang Viet Nguyenمشاهده پروفایل

پژوهشگر

• Computational Social Science
• Political Methodology
• Comparative Politics
• +۷ مورد دیگر

Hung Hoang Viet Nguyen is a Researcher at the Deutsches Institut für Erwachsenenbildung (DIE) in the department of Organization and program planning , where he has worked since 2024. Concurrently, he is completing his Doctorate in Political Science at the Bremen International Graduate School of Social Sciences (2019–2025). Education: Doctorate of Philosophy in Political Science, Bremen International Graduate School of Social Sciences (2019–2025) Master of Arts/Social Sciences in European Studies, University of Flensburg/University of Southern Denmark (2016–2018, double degree) Bachelor in International Relations, Ho Chi Minh City University of Social Sciences and Humanities (2011–2015) Research Focus: Nguyen specializes in computational approaches to political science, including text analysis, NLP, and machine learning. His work examines party systems, welfare policies, and methodological innovations in social science research. Key domains include: Quantitative analysis of political representation and social policies Machine learning applications for party positioning Cross-national studies of pandemic policy feedback Reproducibility frameworks for social sciences Publications: His recent articles demonstrate strong emphasis on computational reproducibility, political heuristics, and pandemic policy analysis, frequently employing advanced statistical modeling and cross-national datasets.

Philipp Bruneمشاهده پروفایل

استاد

• Artificial Intelligence
• Facial Emotion Recognition
• Cybersecurity
• +۵ مورد دیگر

Professor Dr. Philipp Brune serves as a prominent academic leader at Neu-Ulm University of Applied Sciences (HNU), holding multiple key positions including Academic Head of TTZ Günzburg, Head of the Master of Artificial Intelligence and Data Analytics program, Head of the Centre for Secure IT Applications and Infrastructures, and Head of the Institute of Agile Product and System Development within the Faculty of Information Management. His career demonstrates a notable transition from physics research (evident in his early 2000-2004 publications) to his current focus on cutting-edge information systems and artificial intelligence. Dr. Brune's research program spans several interconnected domains with particular emphasis on facial emotion recognition systems, legacy system modernization, and secure IT infrastructure development. His work investigates fundamental challenges in AI interpretability, data quality for emotion recognition, and practical approaches to modernizing legacy applications. He has made substantial contributions to understanding the limitations of current facial expression recognition technologies and developing more robust, trustworthy alternatives. Analysis of his recent publications reveals a clear research trajectory toward explainable and trustworthy AI systems, with increasing sophistication in addressing data quality issues and model interpretability challenges. His work bridges theoretical computer science with practical applications across healthcare, marketing, and smart city technologies, demonstrating strong translational research capabilities. As an educator, Dr. Brune has developed innovative pedagogical approaches specifically tailored for non-computer science majors, with research examining student motivation in programming courses and effective methods for teaching cybersecurity concepts. His leadership in the Master of Artificial Intelligence and Data Analytics program shapes curriculum development for next-generation AI professionals. Dr. Brune directs multiple research initiatives including the Centre for Secure IT Applications and Infrastructures, which addresses critical cybersecurity challenges in modern IT environments, and the Institute of Agile Product and System Development, which explores innovative software development methodologies. His collaborative research approach is evident through extensive co-authorship networks spanning multiple institutions and disciplines.