Find Academic Supervisors

Tatjana HildebrandtView profile

Professor

• Plant Biochemistry
• Amino Acid Metabolism
• Plant Stress Response
• +5 more

Professor Tatjana Hildebrandt leads the Plant Metabolic Biochemistry Lab at the Institute for Plant Sciences, University of Cologne, where she serves as Principal Investigator within the Cluster of Excellence on Plant Sciences (CEPLAS) and TRR 341 "Plant Ecological Genetics." Her research group investigates plant amino acid metabolism with particular focus on cysteine pathways, mitochondrial function, and metabolic adaptations to environmental stress. Her research program spans four main areas: (1) Amino acid metabolic pathways with emphasis on catabolic processes; (2) Metabolic plasticity during abiotic stress conditions including drought, hypoxia, and energy deficiency; (3) Metabolic interactions between plants and microbes; and (4) Amino acid sensing mechanisms including post-translational modifications like persulfidation. Her group employs biochemical, proteomic, and metabolomic approaches to unravel these complex processes. Analysis of her recent publications reveals a strong focus on cysteine metabolism, mitochondrial function during germination, and the role of amino acids in stress signaling. Her work bridges fundamental plant biochemistry with potential applications in improving crop resilience. Her research consistently appears in high-impact journals including Plant Physiology, Journal of Experimental Botany, and Trends in Biochemical Sciences. Her laboratory currently includes multiple PhD students and postdoctoral researchers working on projects related to amino acid metabolism in Arabidopsis and Lupinus albus. She actively collaborates with researchers across Europe through CEPLAS and the International Max Planck Research School (IMPRS).

• Neuroimmunology
• Microglial Biology
• Neurodegenerative Diseases
• +5 more

Dr. Róisín McManus serves as a Group Leader within the Career Development Fellow Programme at the German Center for Neurodegenerative Diseases (DZNE) and is associated with the Institute of Innate Immunity at the University of Bonn's Medical Faculty. Her research focuses on understanding how microglial metabolic changes and immune signaling converge to alter disease progression in neurodegenerative conditions. Dr. McManus's research program investigates the role of microglia as the brain's resident immune cells, particularly examining their innate immune responses in neurodegenerative disease development. Her laboratory explores microglial immunometabolism in cellular function regulation and how environmental factors like Western diet drive neuroinflammation. Using transgenic animal models, primary cultures, human iPSCs, and clinical samples, her multi-omic approach addresses critical gaps in understanding how impaired microglial signaling in aging leads to chronic inflammation that accelerates neurodegenerative diseases. Based on her published work, Dr. McManus's research demonstrates a strong emphasis on NLRP3 inflammasome pathways in Alzheimer's disease pathology. Her 2024 publication with Latz provides a schematic representation of this activation process, indicating her contributions to mapping key immune mechanisms in neurodegeneration. This work is particularly significant given the current lack of preventive treatments for neurodegenerative conditions. Dr. McManus leads an active research laboratory investigating how microglial dysfunction affects neighboring neurons and astrocytes in the central nervous system. Her team's experimental approach aims to identify novel immune-targeted therapies that could provide better, patient-specific treatment options for individuals with inflammatory or neurodegenerative conditions.

• Neurodegenerative Diseases
• Extracellular Vesicles
• Biomarker Discovery
• +3 more

Prof. Dr. Anja Schneider serves as a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany. Her research program bridges fundamental neurobiology with clinical applications in neurodegenerative disorders, focusing on extracellular vesicle mechanisms and early biomarker development. Her work investigates extracellular vesicle (EV)-mediated release of toxic proteins like α-synuclein in Parkinson's disease, determinants of pathological protein sorting into EVs, and EV contributions to neurodegeneration spread. She explores physiological EV functions—particularly oligodendroglial EVs—using primary cell cultures and mouse models, while concurrently developing blood and CSF biomarkers for prodromal-stage diagnosis of Alzheimer's and Parkinson's diseases. This dual focus enables direct translation from bench to bedside. Dr. Schneider leads a Phase 1b clinical trial testing Vorinostat's safety in mild Alzheimer's patients, directly implementing preclinical findings from DZNE Göttingen that demonstrated memory restoration in mouse models. Her team actively collaborates across DZNE sites to accelerate therapeutic development. Her laboratory at DZNE Bonn integrates cellular neuroscience, animal modeling, and clinical sample analysis to dissect EV biology in neurodegeneration, maintaining close ties with clinical neurology for rapid validation of biomarker candidates.

• Surface Science
• Catalysis
• Metal-Organic Frameworks
• +5 more

Professor Christof Wöll is a leading researcher at Karlsruhe Institute of Technology (KIT), where he heads the Institute of Functional Interfaces (IFG). His work bridges fundamental surface science with practical applications in catalysis and materials engineering. His research spans several key areas including the structure-activity relationships of oxide catalysts, metal-organic frameworks (MOFs), and surface phenomena at functional interfaces. He specializes in advanced characterization techniques such as scanning tunneling microscopy, helium atom beam scattering, and X-ray photoelectron spectroscopy. Professor Wöll has led or participated in numerous major research initiatives including Collaborative Research Centers (SFB 558), Priority Programs (SPP 1121), and Clusters of Excellence (CFN, 3D Designer Materials). His current projects focus on in situ/operando characterization of catalytic systems, defect engineering of MOFs, and developing advanced instrumentation for surface analysis. His leadership extends to serving as speaker for major research programs and as co-speaker for the FAIRmat data infrastructure initiative, demonstrating his influence in shaping research directions in materials science. Professor Wöll's work shows consistent emphasis on bridging fundamental understanding with practical applications, particularly in energy-related catalytic processes and advanced materials design.

Zhe LiuView profile

Assistant Professor

• Software Engineering
• Mobile Testing
• Deep Learning
• +5 more

Zhe Liu is an Assistant Scientist at the Institute of Software, Chinese Academy of Sciences, and is affiliated with the University of Chinese Academy of Sciences. With a PhD from the University of Chinese Academy of Sciences, Liu focuses on innovative research at the intersection of software engineering, mobile testing, and artificial intelligence. Liu's research interests span multiple areas including: Software Engineering Mobile Testing Deep Learning Human-Computer Interaction Machine Learning Computer Vision UI Testing Crowd Testing Liu applies AI and lightweight program analysis technology in several key directions: AI/LLM-assisted automated mobile app development (requirement elicitation, app GUI testing, usability, bug replay) Human-machine collaborative testing (testing guides for testers) AI-empowered mining of software repositories (issue report mining) Liu has published 15 papers at top international Software Engineering and Human-Computer Interaction conferences/journals (CCF-A) with over 1,300 Google Scholar citations. The research shows a strong trend toward leveraging large language models for mobile app testing, with significant contributions in automated GUI testing, crash reproduction, and text input generation. Notable scientific achievements include: ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category Best Paper Honourable Mention in CHI'24 ACM Student Research Competition (SRC) at ICSE 2022, 1st Place ACM Student Research Competition (SRC) at ASE 2020, 1st Place Excellent Doctoral Dissertation of Chinese Academy of Sciences in 2024 Liu has served as a program committee member for ASE 2025 and has been involved in multiple research projects funded by the National Key Research and Development Program of China, National Natural Science Foundation of China, and Populus Innovation Research Funding. Current research focuses on advancing the integration of large language models with mobile application testing frameworks to improve app quality and user experience.

Xiang ChenView profile

Associate Professor

• Empirical Software Engineering
• Mining Software Repositories
• Software Testing and Maintenance
• +5 more

Xiang Chen is an Associate Professor at the Department of Software Engineering, School of Artificial Intelligence and Computer Science, Nantong University, China. He received his B.Sc. degree from Xi'an Jiaotong University in 2002 and his M.Sc. and Ph.D. degrees in computer software and theory from Nanjing University in 2008 and 2011 respectively. He is an editorial board member of Information and Software Technology and serves as a program committee member for prestigious conferences including FSE 2026 and ASE 2025. Chen is also a senior member of the China Computer Federation (CCF) and active in various academic committees. Chen's research focuses on empirical software engineering, mining software repositories, and software testing and maintenance, with particular emphasis on applying AI techniques to software engineering problems. His work spans large language models for software engineering, security vulnerability analysis, code change representation, and regression testing. He has published over 110 papers in top-tier journals and conferences including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. His recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models, with traditional software engineering practices. The research spans code generation evaluation, deep learning framework testing, vulnerability detection, and automated program repair, showing a consistent focus on improving software quality through innovative testing and analysis techniques. ACM SIGSOFT Distinguished Paper Award (ICSE 2021) ACM SIGSOFT Distinguished Paper Award (ICPC 2023) Top 1% CNKI Highly Cited Scholar (2024) Top 2% Scientist by Stanford University (2023-2025) NASAC 2019 Prototype Competition First Prize Chen has successfully advised numerous graduate and undergraduate students who have gone on to prestigious institutions including Nanjing University, Tsinghua University, and Zhejiang University. Many of his students have won national programming competitions and received scholarships. His research group, smartSE, actively works on projects funded by the Natural Science Foundation of China and various provincial research programs. Chen also serves as a reviewer for top journals including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology.

Fang LiuView profile

Assistant Professor

• Software Engineering
• Artificial Intelligence for Software Engineering
• Program Understanding
• +3 more

Fang Liu is an Assistant Professor at the School of Computer Science & Engineering, Beihang University, China. She has made significant contributions to the field of software engineering, particularly in the intersection of artificial intelligence and software development practices. Dr. Liu received her Ph.D. in Computer Science from Peking University (Sep. 2017 - Jul. 2022), supervised by Prof. Zhi Jin and Prof. Ge Li. Prior to that, she earned her B.S. in Computer Science from Chongqing University (Sep. 2013 - Jul. 2017). Her research interests focus on AI for Software Engineering, including program understanding and generation, program repair, and applications of Large Language Models to software development tasks. Dr. Liu teaches Compiler Technology as a compulsory course at Beihang University (Fall 2024) and Programming in Cangjie Language as an elective course (Spring 2025). Her recent publications demonstrate a clear trend toward leveraging large language models for various software engineering tasks, with a particular emphasis on code editing, program repair, and code translation. Her research spans both theoretical advancements in model architectures and practical applications to real-world software development challenges, with numerous publications in top-tier venues like ASE, ICSE, and FSE. Distinguished Paper Award at ICPC'20 for "A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning" Dr. Liu actively participates in the software engineering research community as a program committee member for major conferences including ASE, FSE, and ICSE. Her work has significant implications for improving developer productivity, software quality, and the integration of AI technologies into the software development lifecycle.

Steffen GoebbelsView profile

Professor

• 3D City Modeling
• Computer Graphics
• Numerical Analysis
• +5 more

Prof. Dr. Steffen Goebbels is a Professor of Mathematics and Computer Science at Niederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science in Krefeld, Germany. He maintains an office in room F 202 and is actively involved in teaching and research. His academic work spans multiple disciplines with a strong focus on applied mathematics and computer science. His research interests center around 3D city modeling, mathematical optimization, and computer graphics. He has made significant contributions to the field of CityGML data processing and has developed algorithms for calculating 3D building models from land registry data and laser scan data. His work with the iPattern Institute has led to practical applications in cities like Krefeld, Leverkusen, and Dortmund. He has also contributed to neural network approximation theory and various optimization problems. Prof. Goebbels has published extensively in recent years, with publications spanning computer graphics, mathematical optimization, and machine learning. His research shows a consistent pattern of applying mathematical techniques to solve practical problems in 3D modeling and computer vision. He has also co-authored several influential textbooks on mathematics for computer science students. He has received recognition for his work through publications in reputable journals and conference proceedings, though specific awards are not mentioned in the available information. His research has practical applications in urban planning, architectural visualization, and manufacturing processes. Prof. Goebbels is actively involved in teaching mathematics courses (Mathematics 1-3), Numerical Analysis, Logic Programming, Functional Programming, and Scientific Computing. He has developed teaching materials including online courses and textbooks that are widely used in his institution.

Chunyang ChenView profile

Professor

• Software Engineering
• Applied Data Analysis
• Deep Learning
• +5 more

Chunyang Chen is a Professor at the School of CIT, Technical University of Munich (TUM), Germany. He maintains an active research profile in software engineering with a focus on applying data analysis and artificial intelligence techniques to software development processes. His primary research interests include Software Engineering , Applied Data Analysis , Deep Learning , and Human-Computer Interaction . Dr. Chen is particularly known for his work in applying data analysis to automated software development and mining software repositories, with significant contributions in mobile application testing, GUI testing, and leveraging Large Language Models for software engineering tasks. His recent publications (2024-2026) demonstrate a strong focus on integrating Large Language Models with software testing methodologies, particularly for mobile applications. The research trends show increasing sophistication in using multimodal LLMs, dynamic memory techniques, and retrieval augmentation to improve automated testing capabilities. Dr. Chen maintains an active presence in the software engineering research community, serving on program committees for major conferences including ASE, ICSE, and ESEC/FSE. He has also delivered keynote speeches on mobile application testing with Large Language Models, highlighting his thought leadership in this emerging area.

Mingwei LiuView profile

Associate Professor

• Software Engineering
• Artificial Intelligence
• AI4SE
• +4 more

Dr. Mingwei Liu is an Associate Professor at the School of Software Engineering, Sun Yat-Sen University, China. Previously, he completed postdoctoral research at Fudan University in 2024 and received both his Ph.D. (2022) and B.E. (2017) in Software Engineering from Fudan University under the mentorship of Xin Peng. Dr. Liu's research focuses on the intersection of Software Engineering (SE) and Artificial Intelligence (AI), specifically in the domains of AI4SE (AI for Software Engineering) and SE4AI (Software Engineering for AI). His primary interest lies in leveraging advanced AI technologies, particularly large language models (LLMs) and knowledge graphs (KGs), to address complex software engineering challenges and tackle system engineering problems in AI applications. His research portfolio demonstrates a strong focus on practical applications of AI in software development, with particular emphasis on code generation, vulnerability detection, test generation, and knowledge representation for software artifacts. Through his work, Dr. Liu has contributed significantly to understanding how LLMs perform in realistic software development scenarios beyond simple function-level code generation. Dr. Liu has published over twenty papers in top international journals and conferences including TSE, TOSEM, ICSE, FSE, and ASE. His research has been recognized with prestigious awards including the IEEE TCSE Distinguished Paper Award (ICSME 2018) and the ACM SIGSOFT Distinguished Paper Award (FSE 2023). IEEE TCSE Distinguished Paper Award (ICSME 2018) ACM SIGSOFT Distinguished Paper Award (FSE 2023) Dr. Liu actively contributes to the academic community as a program committee member for major conferences including ASE, ESEC/FSE, ICSME, and SANER. He leads the SYSUSELab research group, which has developed notable resources including the ClassEval benchmark for evaluating LLMs on class-level code generation tasks.

Yulei SuiView profile

Associate Professor

• Program Analysis
• Software Engineering
• Machine Learning
• +7 more

Yulei Sui is an Associate Professor at the School of Computer Science and Engineering, University of New South Wales (UNSW), where he conducts research at the intersection of programming languages, software engineering, and machine learning. His work focuses on developing open-source frameworks for static analysis and verification to enhance software reliability and quality. He currently serves as Program Chair for LCTES 2024, SAS 2025, and ISSRE 2025, and is a program committee member for numerous top-tier conferences including PLDI, OOPSLA, and ICSE. His educational background includes a PhD from UNSW, where he has been a faculty member since completing his studies. His research interests span program analysis, software verification, machine learning applications in software engineering, and the intersection of programming languages with natural language processing and code LLMs. He leads the development of SVF (Static Value-Flow), an open-source framework for code analysis and verification, which has gained significant traction in both academic and industrial settings. His recent publications demonstrate a strong focus on improving the precision and efficiency of static analysis techniques, particularly in areas like context-free language reachability, pointer analysis, typestate analysis, and vulnerability detection. His work often bridges theoretical advances with practical applications, resulting in tools that address real-world software reliability and security challenges. Several of his papers have received distinguished paper awards at top conferences including ICSE and FSE. ICSE Distinguished Paper Award (2025) FSE Distinguished Paper Award (2024) OOPSLA 2022 Distinguished Artifact Award Australian Research Council Future Fellowship Fellow of Engineers Australia (FIEAust) Professor Sui actively mentors PhD students and undergraduate thesis candidates, with numerous students having completed their research under his supervision. He has secured significant research funding including ARC Discovery Projects and an ARC Future Fellowship. His community service includes editorial roles for IEEE Transactions on Software Engineering and IEEE Transactions on Reliability, demonstrating his standing as a leader in the software engineering research community.

Hamid BagheriView profile

Associate Professor

• Software Engineering
• Security of Mobile Devices and IoT Systems
• Formal Methods
• +4 more

Hamid Bagheri is an Associate Professor in the School of Computing at the University of Nebraska-Lincoln, where he conducts cutting-edge research at the intersection of software engineering, security, and formal methods. He also serves as a faculty associate of the Institute for Software Research (ISR) at the University of California, Irvine, and co-directs the ESQuaReD Lab (Engineering Software Quality and Reliability through Deductive methods), which focuses on ensuring software quality through rigorous engineering approaches. Dr. Bagheri's research spans several critical areas including security of mobile devices and IoT systems, scaling formal verification with machine learning, software analysis and testing, dependable cyber-physical systems, and automated program repair and fault localization. His work combines theoretical rigor with practical applications, addressing real-world challenges in software security and reliability through publications in top venues like ICSE, FSE, ASE, and IEEE/ACM Transactions journals. His recent publications demonstrate a strong trend toward integrating machine learning techniques with formal methods to enhance software analysis capabilities. This includes leveraging transformers for database design optimization, neuro-symbolic approaches for certified software synthesis, and large language models for repairing formal specifications, reflecting his ability to adapt to emerging technologies while maintaining a strong theoretical foundation. Dr. Bagheri has received numerous prestigious awards including the EPSCoR FIRST Award, the NSF CISE Career Research Initiation Initiative Award, multiple Distinguished Paper Awards from top conferences, and teaching honors such as the SoC Student Choice Outstanding Teaching Award (2023-2024) and the CSE Outstanding Teaching Award (2020-2021). As an advisor, Dr. Bagheri has mentored several successful PhD students including Mohannad Alhanahnah (who joined Chalmers University as a tenure-track faculty member in Fall 2024) and Clay Stevens (who joined Iowa State University as a tenure-track faculty member in Fall 2023). His research has been supported by significant grants from NSF and other funding agencies, with recent work focusing on automated specification repair, security analysis of IoT systems, and verification of network protocols. The ESQuaReD Lab, which Dr. Bagheri co-directs, brings together a multidisciplinary team focused on addressing critical challenges in software quality and reliability through innovative engineering approaches and formal analysis techniques, with applications spanning mobile security, IoT systems, and cyber-physical systems.

Abhishek TiwariView profile

Associate Professor

• Static Program Analysis
• Android Security
• Language-Based Security
• +4 more

Abhishek Tiwari is an Associate Professor of Software Engineering at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark, where he was promoted from Assistant Professor in September 2025. His academic journey includes positions as Senior Researcher at Software Institute, USI Lugano (2024), Senior Researcher at University of Passau (2022-2023), and Research Fellow at National University of Singapore (2020-2021). He completed his PhD in Software Engineering at University of Potsdam, Germany in 2019 under supervision of Prof. Dr.-Ing Christian Hammer. His research focuses on the intersection of programming languages and software engineering, with particular expertise in static program analysis, language-based security, information flow control, and automated program repair. His work has significant practical applications in Android security and privacy, addressing critical challenges in information flow analysis, vulnerability detection, and program repair. His research has evolved from foundational work on Android security mechanisms like PendingIntent analysis and anti-theft frameworks to more recent sophisticated approaches for information flow security repair and multilingual program analysis. Trends in his publication record show a consistent focus on Android security challenges, with increasing sophistication in analysis techniques from 2017 through 2025. His work spans theoretical foundations of program analysis while maintaining strong practical relevance to real-world Android security issues. Recent publications demonstrate growing interest in multilingual program analysis and formal specification challenges. ACM SIGSOFT Distinguished Paper Award (MOBILESoft 2023) Dr. Tiwari actively contributes to the academic community through program committee service for major conferences including ASE (2024, 2025), ICSE (2025), and ISSTA (2022-2024). His teaching portfolio includes Advanced Software Engineering Methodologies (2024), Automated Program Repair (2022-2023), and Mobile Security (2022) courses. He has received research funding from prestigious sources including Deutsche Forschungsgemeinschaft (DFG), German Federal Ministry of Education and Research, and EIT Digital for projects related to programming principles for privacy, SmartPriv, and SMAPPER.

René PeinlView profile

Professor

• Multimodal Artificial Intelligence
• Resource-efficient AI
• Speech Recognition
• +7 more

René Peinl is a Professor of Business Informatics at the Institute for Information Systems (iisys) within the Faculty of Computer Science at Hof University of Applied Sciences. He serves as the Institute Director and leads the research group on Multimodal Artificial Intelligence. His academic career spans over 15 years of teaching in master's programs including 'Master Informatik' and 'Master Applied Research in Computer Science', with a focus on resource-efficient AI for text understanding since 2021. Dr. Peinl's research spans multiple cutting-edge domains in AI and information systems. His primary focus is on multimodal artificial intelligence systems that integrate various data modalities. He specializes in resource-efficient AI models that can operate without cloud resources, with particular emphasis on German language processing for speech recognition, text understanding, and speech synthesis. His work extends to practical applications in Industry 4.0 through customizable manufacturing execution systems (HiCuMES) and immersive learning applications using virtual reality technology for fields like electrical engineering and healthcare training. Analysis of his recent publications reveals a strong trend toward practical, efficient AI implementations with a focus on German language processing and multimodal systems. His work addresses critical challenges in model compression, bias mitigation in generative AI, and multimodal integration of text and image understanding. A significant portion of his research focuses on making AI more accessible and practical for small and medium enterprises through resource-efficient implementations that don't require cloud infrastructure. Professor Peinl actively participates in academic service and industry collaboration. He serves as a member of Hof University's senate and supervisory board. His research is supported through EFRE projects including 'Wirtschaft im Mittelstand 4.0' and 'Digitale Transformation des Mittelstands mit KI'. He frequently engages with industry through speaking engagements, consulting, and collaborative projects with companies across various sectors. At Hof University, Peinl leads the Institute for Information Systems and the Multimodal Artificial Intelligence research group. His team works on developing privacy-friendly speech assistance systems that function without cloud resources, highly customizable manufacturing execution systems for Industry 4.0, and immersive VR learning applications for domains that are expensive, dangerous, or difficult to replicate in physical reality.

Brigitte KauerView profile

Lecturer

• Business Administration
• Engineering Management
• Business Planning
• +2 more

Brigitte Kauer MA serves as Faculty Representative at the Faculty of Architecture of Regensburg University of Applied Sciences (OTH Regensburg), where she teaches Business Administration for Engineers. Her role connects administrative functions with academic instruction within the architecture faculty. Her teaching focuses on business management fundamentals, business plan writing, business models, and classic communication - essential skills for architecture and engineering students navigating professional practice. As Faculty Representative, she likely serves as a liaison between students, faculty, and administration. At OTH Regensburg's Faculty of Architecture, which comprises 18 professors and over 10 employees across 6 study programs (3 bachelor's and 3 master's degrees), Kauer's business expertise complements the design and technical curriculum. The faculty is highly ranked in Germany, particularly in areas like studio workspaces, design projects, and study support. Room: L 405 Phone: 0941 943-9815 Appointments by arrangement via email