Find Academic Supervisors

Carolin LiefkeView profile

Researcher

• Stellar Activity
• X-ray Astronomy
• Astronomy Education
• +2 more

Dr. Carolin Liefke serves as Deputy Head of the Haus der Astronomie (House of Astronomy) and Deputy Director of the IAU Office of Astronomy for Education at Heidelberg University. With over 20 years of experience in astronomy education and public outreach, she has been a research associate at the House of Astronomy since March 2010. She also serves as the National Outreach Coordinator for Germany of the International Astronomical Union. Dr. Liefke's research interests span stellar activity, X-ray astronomy, and innovative approaches to astronomy education. Her work focuses on developing educational resources that make astronomy accessible to diverse audiences, including the "telescope license" program for schools, the HdA partner school network, and the Pan-STARRS asteroid search project for students. She has taught numerous seminars at Heidelberg University covering astronomy topics from multi-wavelength observations to solar system studies. Her publications demonstrate consistent focus on translating complex astronomical concepts into classroom-appropriate materials. She maintains an active presence in science communication through her long-running blog "Astronomers do it at Night" and on social media as @astrophysikerin. Her approach emphasizes hands-on learning and connecting cutting-edge astronomical discoveries with school curricula. Deputy Head, Haus der Astronomie (HdA) Deputy Director, IAU Office of Astronomy for Education National Outreach Coordinator for Germany, International Astronomical Union Research Associate, House of Astronomy since 2010 Active blogger since 2009 on astronomy education

Christoph TholenView profile

Professor

• Machine Learning
• Remote Sensing
• Marine Environmental Monitoring
• +3 more

Christoph Tholen is a Professor at the German Research Center for Artificial Intelligence (DFKI) , leading the Marine Perception unit. His work focuses on applying AI to maritime challenges, with expertise in remote sensing, environmental monitoring, and machine learning for aquatic systems. Research Interests Development of AI-driven solutions for marine pollution detection Multi-platform/multi-sensor remote sensing integration Modeling photosynthetically active radiation in aquatic environments Location-independent neural network architectures Long-term monitoring of waterway pollutants Environmental data fusion techniques Projects XAI4SFAS : Intelligent assistance systems for semi-autonomous ship navigation APLASTIC-Q-Canada : Machine Learning identification of pollutants in Canadian waterways PlasticObs_plus : Airborne multi-sensor monitoring for oceanic plastic detection MATE : Maritime traffic emissions monitoring network Collaborations Works with mariNom GmbH and Jade Hochschule Wilhelmshaven/Oldenburg/Elsfleth on aquatic imaging data, plastic pollution analysis, and maritime emissions research.

Bastian WelschView profile

Professor

• Geothermal Energy
• Renewable Energy Systems
• Borehole Thermal Energy Storage
• +3 more

Prof. Dr.-Ing. Bastian Welsch serves as a Professor in the Department of Civil and Environmental Engineering at Bochum University of Applied Sciences, where he holds key leadership roles including Head of the Renewable Energy Systems program, Chairman of the Renewable Energy Systems Committee, and member of both the Departmental Council and founding board of the Energy Transition Institute (EnWI). His academic focus centers on geothermal energy systems and renewable energy integration within sustainable infrastructure frameworks. Welsch's research expertise spans medium-deep borehole thermal energy storage, geothermal probe modeling, and renewable energy system optimization. His work addresses critical challenges in seasonal heat storage, district heating integration, and groundwater interaction with geothermal systems. He has pioneered simulation tools like BASIMO for optimizing borehole heat exchanger arrays and investigated permeability changes affecting regulatory approvals. His research bridges technical engineering with environmental and economic sustainability assessments. Analysis of his 15 most recent publications (2015-2020) reveals a strong trajectory toward practical implementation of geothermal storage solutions, with increasing emphasis on economic viability, environmental impact metrics, and integration with 4th generation district heating grids. His work consistently combines numerical modeling with real-world system design, demonstrating growing sophistication in optimization algorithms and multi-system coupling approaches. As an educator, Welsch teaches across both bachelor's and master's programs, covering foundational courses like Geology and Georesources alongside specialized subjects including Geothermal Energy Systems, Renewable Energies and Energy Supply, and advanced Geothermal Systems courses focusing on heating/cooling storage and electricity generation. He maintains regular consultation hours for students during academic terms.

Kathrin M. MösleinView profile

Professor

• Strategic Innovation
• Business Information Systems
• Innovation Management
• +5 more

Professor Kathrin M. Möslein holds the Chair of Business Information Systems, specializing in Innovation and Value Creation at Friedrich-Alexander University Erlangen-Nürnberg (FAU). She has been Vice President of FAU since 2016 and has held her professorship since 2007. Previously, she served as Chair of Strategic Management and Organization at HHL Leipzig Graduate School of Management. She is an active academic leader, having served as President of the European Academy of Management (EURAM) and holding significant roles in academic governance. Her research spans strategic innovation, cooperation, leadership, and their IT support within companies, with particular emphasis on digital transformation and Industry 4.0 applications. Her work demonstrates strong interdisciplinary connections between business administration, information systems, and engineering disciplines, reflecting her dual background in computer science and economics. Professor Möslein's recent publications reveal a consistent focus on practical applications of digital technologies in business contexts, particularly examining innovation ecosystems, smart manufacturing, and service systems engineering. Her work bridges theoretical frameworks with real-world business challenges, often incorporating stakeholder perspectives and practical implementation considerations. She maintains significant academic leadership roles including membership in the permanent commission 'Transfer and Cooperation' of the German Rectors' Conference, the board of the Leipzig Foundation for Innovation and Technology Transfer, and as research professor and member of the management of the Center for Leading Innovation & Cooperation (CLIC) at HHL.

Martin SchmidtView profile

Professor

• Mathematical Optimization
• Energy Systems
• Mixed-Integer Nonlinear Optimization
• +3 more

Martin Schmidt is a Full Professor (W3) for Nonlinear Optimization at the Department of Mathematics, Trier University, since 2019. He has held leadership roles in research training groups and international committees, focusing on mathematical modeling and optimization of energy systems, gas networks, and market equilibria. His work bridges mixed-integer nonlinear optimization , bilevel optimization , and robust methods with applications to real-world energy challenges. Education: PhD in Mathematics (2013), Diplom in Mathematics (2008), both from Leibniz University Hannover. Editorial Roles: Editorial Board member of Journal of Optimization Theory and Applications and Optimization Letters , Associate Editor for OR Spectrum and EURO Journal on Computational Optimization . His research integrates complex physical systems (e.g., gas transmission networks) with game-theoretic models to analyze energy markets. Recent publications emphasize robust optimization , decomposition techniques , and machine learning integration in bilevel frameworks. Awards highlight his contributions to gas market feasibility , linear bilevel optimization , and practical applications in energy systems. Collaborations span institutions like Universidad Zaragoza, Sapienza University, and Forschungszentrum Jülich.

Cyrus ZahiriView profile

Professor

• Public Space
• Urban Planning
• Landscape Architecture
• +3 more

Prof. Dr.-Ing. Cyrus Zahiri is a faculty member at the School of Architecture Bremen , affiliated with the Hochschule Bremen – City University of Applied Sciences . His academic rank is Professor in the department of Dept. A . Research focuses on public space , urban planning , and ecological design . Current priorities include climate adaptation , non-European urban contexts , and artificial landscapes . His research spans spatial, social, and ecological dimensions of public spaces, emphasizing their role as islands , oases , and stages for urban life. Publications address topics like heterotopias , green infrastructure , and reflexive design processes . Recent articles highlight interdisciplinary approaches in architecture and landscape architecture, with a focus on case studies from São Paulo, Beijing, and Berlin. Themes include fluid spatial transformations , ecological transitions , and digital design tools . Active in lectures (2024–2010) and exhibitions (2024–2005). Engaged in jury activities , associations , and academic training .

Miryung KimView profile

Professor

• Software Engineering
• Software Engineering for Data Intensive Computing
• Automated Testing
• +7 more

Miryung Kim is a Professor and Vice Chair of Graduate Studies in UCLA's Computer Science Department, where she directs the Software Engineering and Analysis Laboratory. She is renowned for her pioneering work in software evolution, code clone management, and establishing the emerging field of Software Engineering for Data Intensive Computing (SE4DA and SE4ML). Her research focuses on automated testing and debugging for Apache Spark, developer tools for heterogeneous computing, and conducting systematic studies of refactoring practices in industry. She led the first large-scale study of data scientists in industry and developed JDebloat, a Java bytecode debloating tool that made significant tech transfer impact to the Navy. Her recent publications demonstrate strong trends in fuzz testing for big data analytics and heterogeneous computing, with a focus on natural input generation, co-dependence awareness, and leveraging hardware probes for acceleration. Her work bridges software engineering with data-intensive and heterogeneous computing paradigms. ACM SIGSOFT Influential Educator Award (2022) ICSME Most Influential Paper Award (2023 and 2020) NSF CAREER award Google Faculty Research Award Okawa Foundation Research Award Humboldt Fellow ACM Distinguished Member As an academic advisor, she has produced eight tenure-track faculty members at institutions including Columbia, Purdue, and Virginia Tech. Her research has been supported by National Science Foundation, Air Force Research Laboratory, Google, IBM, Intel, Okawa Foundation, Samsung, and Office of Naval Research. She previously served as Program Co-Chair of ESEC/FSE 2022 and has delivered keynotes at ASE 2019 and ISSTA 2022. She maintains active industry collaborations, serving as an Amazon Scholar at Amazon Web Services and having spent time as a visiting researcher at Microsoft Research.

• Bioengineering
• Microfluidics
• Organ-on-Chip Technology
• +5 more

Matthias Meier is a Full Professor at the Institute of Biochemistry, University of Leipzig, and Principal Investigator at Helmholtz Pioneer Campus, Helmholtz Zentrum München. His research focuses on advancing microfluidic organ-on-chip technology for single-cell and whole-organ disease modeling. Education: PhD in Biophysics (University of Basel, 2006) Research Interests: Dr. Meier's work bridges bioengineering and metabolic disorders, using organ-on-chip platforms to study stem cell differentiation, pancreatic/adipose tissue interactions, and dynamic microenvironmental signals. His lab integrates microfluidics with hiPSC-derived organoids for obesity and diabetes research. Publication Trends: Recent studies emphasize organ-on-chip systems, single-cell analysis , and stem cell engineering , with applications in cardiovascular disease modeling, spatial transcriptomics, and bioelectronic monitoring. Scientific Awards: Feodor-Lynen Postdoctoral Fellowship (2008) Emmy-Noether Fellowship (2012-2018) ERC Consolidator Grant (2017) Advising & Grants: He has led independent research groups with major grants, focusing on energy imbalance mechanisms and patient-specific organoid models for metabolic disease therapies. Labs & Teams: The Matthias Meier Lab develops microfluidic platforms to control chemical, architectural, and mechanical cues for hiPSC differentiation, emphasizing spatial protein profiling and organoid assembly.

• Computational Neuroscience
• Neuroscience
• Artificial Intelligence
• +3 more

Susan Fischer is a Professor in the Department of Computational Neuroscience at the Max Planck Society, serving as Coordinator of the Alexander von Humboldt Professorship. Her institutional affiliation is with the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, where she leads research activities and maintains contact via susan.fischer@tuebingen.mpg.de and phone numbers +49 7071 601 1638 / +49 7071 601 616. Her research centers on Computational Neuroscience, employing mathematical and computational frameworks to model brain function. This interdisciplinary work bridges neuroscience, computer science, and cognitive psychology, with specific focus on neural network simulations and cognitive modeling to decode information processing in biological systems. The field integrates theoretical approaches with empirical data to advance understanding of perception, learning, and decision-making mechanisms. Dr. Fischer directs an active research team within the Department of Computational Neuroscience, with laboratory facilities at Max-Planck-Ring 8, 72076 Tübingen. The group participates in the institute's well-established research ecosystem and actively recruits new members as indicated by the 'Join the lab' section on their webpage, fostering collaboration in cutting-edge neurocomputational studies.

• Wavelets and Frames
• Harmonic and Functional Analysis
• Fractal Geometry
• +3 more

Peter Massopust is a Privatdozent at the Technical University of Munich (TUM), where he is affiliated with the School of Computation, Information and Technology and the Department of Mathematics. His research spans multiple areas of mathematical analysis with a focus on fractal geometry, wavelet theory, and approximation methods. His educational background includes: Habilitation in 2011 from Technical University of Munich Ph.D. in Applied Mathematics from Georgia Institute of Technology (1986) MS in Mathematics from Georgia Institute of Technology (1985) MS in Physics from Georgia Institute of Technology (1981) Dr. Massopust's research interests primarily focus on Wavelets and Frames, Harmonic and Functional Analysis, Fractal Geometry and Fractal Interpolation Theory, and Splines and Approximation Theory. His work bridges theoretical mathematics with practical applications in signal processing, image analysis, and computational methods. His approach often combines classical mathematical techniques with innovative fractal-based methods to solve complex problems in approximation theory and functional analysis. His research has significantly contributed to the development of fractal interpolation functions, complex splines, and wavelet theory, with applications spanning from pure mathematics to engineering problems. His publication record demonstrates a consistent focus on fractal-based mathematical methods, with recent work expanding into quaternionic analysis, complex B-splines, and applications in signal processing. His research shows a clear trajectory from foundational work in fractal geometry to increasingly sophisticated applications in multidimensional signal analysis and computational mathematics. His scientific achievements have been recognized through several prestigious awards: Fulbright Scholarship (1980-1981) GIAN (Global Initiative for Academic Network) Award from the Republic of India (2016, 2017) Dr. Massopust has secured substantial research funding from various national and international sources, including the German Research Foundation (DFG), Bayerische Forschungsallianz, VolkswagenStiftung, and collaborations with Sandia National Laboratories and the National Science Foundation. His research program has consistently focused on advancing mathematical methods for signal and image processing, with particular emphasis on fractal-based approaches and wavelet theory. He has also been instrumental in fostering international collaborations, particularly through the EuroTech network and with institutions in Australia and India. Among his notable contributions is the GHM (Geronimo-Hardin-Massopust) Scaling Vector and DGHM (Donovan-Geronimo-Hardin-Massopust) Multiwavelet, developed at the Georgia Tech Research Institute in 1995. This work has had significant impact in the field of wavelet analysis and its applications.

Theresa ZügerView profile

Researcher

• Artificial Intelligence
• Public Interest AI
• Sustainability
• +5 more

Dr. Theresa Züger is an interdisciplinary researcher leading the AI & Society Lab at the Alexander von Humboldt Institute for Internet and Society (HIIG). She investigates how AI systems can be designed to serve the common good, focusing on initiatives that promote sustainability, strengthen social inclusion, and enable technology reuse through open systems. Her work addresses societal challenges associated with artificial intelligence at political, social, and cultural levels, contributing to accurate assessment of AI's societal implications. Züger received her Ph.D. in Media Studies from Humboldt University in Berlin in 2017 with her dissertation 'Reload Disobedience,' focusing on digital forms of civil disobedience. Previously, she earned an M.A. in Theatre, Film and Television Studies as well as German and Philosophy from the University of Cologne. She also headed the office responsible for the German government's Third Engagement Report on behalf of the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ). Her research centers on Public Interest AI, examining how AI development and deployment can benefit society rather than primarily maximizing profit. Current projects include 'Impact AI' (funded by Volkswagen Foundation), which develops auditing methods to assess AI projects' impact on public interest and sustainability, and 'Human in the Loop,' investigating how automated decision-making processes should be designed for successful human-machine interaction. She previously led the 'Public Interest AI' project, developing a theoretically grounded understanding of public interest AI and creating prototypes like a web accessibility tool and fact-checking application. Analysis of her recent publications reveals a consistent focus on bridging AI technology with societal values. Her work spans technical aspects of AI implementation, ethical considerations, and practical applications that serve public interests. Key trends include human-AI collaboration frameworks, accessibility enhancements, critical examination of AI hype, and theoretical foundations for public interest-oriented AI development. Züger serves as Vice-Chair of the UNESCO Commission on Communication and Information and participates in several juries including the Deep Tech Award, Digital Places – Land of Ideas, and the Civic Innovation Fund. She is also a regular event moderator for organizations like the Berlin-Brandenburg Media Authority, re:publica, and transmediale. As project leader of Impact AI and head of the AI & Society Lab, Züger directs significant research initiatives with funding from organizations like the Volkswagen Foundation. Her work involves extensive collaboration with academic and practical partners across Europe and globally, particularly through projects addressing women in tech and international AI governance. The AI & Society Lab functions as an interdisciplinary interface for new research approaches and knowledge transfer in AI, promoting inclusive, human rights-friendly, and sustainable AI strategies in Europe.

Yuhong NanView profile

Associate Professor

• Software Security
• Privacy Leakage Analysis
• IoT Security
• +3 more

Yuhong Nan is an Associate Professor in the School of Software Engineering at Sun Yat-sen University, China, specializing in software security and privacy leakage analysis for emerging platforms including IoT, mobile systems, and blockchain. Previously a Post-doctoral Research Associate at Purdue University under Prof. Dongyan Xu, she builds practical security tools to detect and mitigate vulnerabilities in real-world systems. Dr. Nan earned her PhD from Fudan University in 2018 supervised by Prof. Min Yang. Her academic journey spans rigorous research in security engineering with emphasis on empirical validation and tool development for complex platform ecosystems. Her research program focuses on uncovering systemic security flaws through innovative analysis techniques. Key contributions include vulnerability detection in smart contracts (e.g., state dependencies, reentrancy), privacy leakage analysis in mobile/IoT ecosystems, and countermeasures against deceptive UI patterns. She employs hybrid approaches combining static/dynamic analysis, machine learning, and large-scale empirical studies to develop deployable security solutions. Analysis of her 15 most recent publications (2023-2025) reveals dominant themes in blockchain security (60%), particularly smart contract/DApp vulnerabilities, with significant work in mobile privacy (30%) and cross-platform threats (10%). Her methodology consistently leverages fine-grained static analysis, semantic enrichment, and feedback-driven fuzzing, yielding tools like SmartAxe and Midas that have influenced industry practices. Dr. Nan actively mentors graduate researchers with 17 advisees including Tencent-employed graduates, and serves as a trusted reviewer for premier journals (IEEE TDSC, TMC, TOPS) and conference committees (ASIACCS, ICICS). Her leadership in security communities bridges academic research with practical defense mechanisms. At Sun Yat-sen University, she directs a high-output research group that collaborates with industry partners to address evolving threats in decentralized systems, maintaining her position among top publishing authors in USENIX Security, CCS, and NDSS venues through rigorous technical innovation.

Jinqiu YangView profile

Associate Professor

• software reliability
• quality assurance of machine learning systems
• autonomous vehicles
• +5 more

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. Her research focuses on improving software reliability and quality assurance, particularly in the context of machine learning systems and autonomous vehicles. She leads active research projects in software testing, automated program repair, and mining software repositories, with strong connections to both academic and industrial applications. Her research interests span software reliability, quality assurance of machine learning systems including autonomous vehicles, software testing, automated program repair, text analytics of software artifacts, and mining software repositories. She has developed novel approaches for testing deep learning libraries, evaluating robustness in autonomous driving systems, and tracking the evolution of static code warnings. Her work bridges traditional software engineering with emerging challenges in AI systems, addressing critical issues of reliability and safety in complex software environments. Yang's recent publications (2021-2025) demonstrate a clear trajectory toward AI/ML system reliability, with increasing focus on autonomous vehicles, concept drift detection, and security aspects of large language models. Her work spans both theoretical foundations and practical applications, often involving empirical studies of real-world systems and development of practical tools to address identified challenges. ACM SIGSOFT Distinguished Paper Award Dr. Yang actively mentors graduate students and is currently recruiting Master's and PhD candidates. She has secured significant research funding including NSERC Discovery Grants (2019-2025), Gina Cody Research and Innovation Fellowship (2024-2026), and participation in the NSERC CREATE Program SE4AI (2021-2026). Her research is supported by multiple grants including NOVA – FRQNT-NSERC PROGRAM (2024-2027) and Volt-Age Seed Grant (2024-2026). She leads research in the O-RISA Lab at Concordia University, focusing on reliability and security aspects of intelligent software systems. Her team collaborates with industry partners including IBM, where she previously worked at IBM Watson Research Lab and IBM CAS, bringing practical experience to her academic research.

• Quantum Information Theory
• Quantum Information Processing
• Entanglement
• +7 more

Géza Giedke is an Ikerbasque Research Professor at the Donostia International Physics Center (DIPC) in Donostia-San Sebastián, Spain. His research focuses on quantum information theory and its implementation in solid-state and quantum optical systems, with particular emphasis on entanglement, quantum channels, and the dynamics of open quantum systems. His educational background includes a Dr. rer. nat. (Doctor of Natural Sciences) from the University of Innsbruck, Austria. Prior to his current position, he has held research positions at the University of Innsbruck (Austria), Max Planck Institute of Quantum Optics in Garching and Technical University of Munich (Germany), and ETH Zurich (Switzerland). Dr. Giedke's research interests span multiple areas of quantum physics and quantum information science. His work explores the theoretical foundations of quantum information processing while also addressing practical implementation challenges in solid-state systems. He has made significant contributions to understanding entanglement in fermionic systems, quantum channels, and the application of quantum information concepts to condensed matter physics. His recent work has increasingly focused on quantum phenomena in graphene-based nanostructures and their potential for quantum information processing applications. His publication record demonstrates a strong trajectory from fundamental quantum information theory to more applied work connecting quantum information concepts with condensed matter physics, particularly in the realm of graphene nanostructures and quantum transport phenomena. Dr. Giedke has secured significant research funding, including the recently granted GRAFIQ project (2023-2027) on 'Harnessing quantum spin states, dynamics, and transport in graphene-based nanostructures' and the TENINT project (2023-2025) on 'Tensor network methods for interacting electrons in quasi-1d graphene nanostructures.' He actively mentors PhD students and postdoctoral researchers, currently supervising several researchers working on various aspects of quantum information in solid-state systems. Dr. Giedke also organizes major scientific events, including the Basque Quantum Science and Technology Workshops and the Nanotechnology meets Quantum Information Summerschool.

Baishakhi RayView profile

Associate Professor

• Software Engineering
• Security
• Artificial Intelligence
• +3 more

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University, working at the intersection of AI, Software Engineering, and Security. She received her Ph.D. from the University of Texas, Austin, and has established herself as a leading researcher in applying artificial intelligence to software engineering challenges. Her educational background includes a Ph.D. from the University of Texas, Austin, which provided the foundation for her research career at the forefront of AI and software engineering. Dr. Ray's research focuses on leveraging artificial intelligence to solve fundamental challenges in software engineering and security. Her work spans multiple areas including code generation with large language models, vulnerability detection, software testing, and program analysis. She has pioneered approaches that combine deep learning with traditional software engineering techniques to create more robust, secure, and efficient software development processes. Her research has practical implications for improving code quality, enhancing software security, and accelerating development cycles through AI assistance. Her recent work demonstrates a strong emphasis on semantic-aware code generation, execution reasoning, and addressing hallucinations in code language models. She has also made significant contributions to evaluating the functionality and security of AI-generated code, identifying critical challenges in the practical adoption of AI for software development. Dr. Ray has received numerous prestigious awards recognizing her contributions to the field: IEEE TCSE Rising Star NSF CAREER award IBM faculty award VMware Faculty award Distinguished Paper awards at FSE'17, ASE'22, and ISSTA'23 ICSME Most Influential Paper award Publications featured in CACM Research Highlights As an Amazon Visiting Academic and active participant in major software engineering conferences, Dr. Ray has established herself as a thought leader in AI for software engineering. Her research has been widely covered in trade media, indicating its relevance and impact on industry practices. She has mentored numerous students through their research and has been instrumental in shaping the next generation of researchers in this interdisciplinary field. Her work demonstrates a consistent focus on bridging theoretical advances with practical applications, ensuring that her research has tangible benefits for the software development community. The trajectory of her publications shows an evolving research agenda that has successfully adapted to the rapidly changing landscape of AI and its applications to software engineering.