جست‌وجوی استاد و پژوهشگر

Ignasi Sau Vallsمشاهده پروفایل

پژوهشگر

• Graph Theory
• Parameterized Complexity
• Algorithmic Graph Theory
• +۵ مورد دیگر

Ignasi Sau Valls is a Directeur de Recherche (DR2) at CNRS, affiliated with the LIRMM laboratory at Université de Montpellier, France. He is a member of the AlGCo team, focusing on algorithms for graphs and combinatorics. His academic background includes dual degrees in Mathematics and Telecommunications Engineering from UPC (Barcelona), a PhD in joint supervision between UPC and Projet Mascotte (Sophia Antipolis), and a postdoctoral position at the Technion (Israel). He has been with CNRS since 2010 and was promoted to his current role in October 2024. He also served as a Visiting Professor at UFC (Brazil) from 2016–2017. His research interests lie primarily in Graph Theory and Parameterized Complexity , with a focus on structural graph properties, kernelization, and algorithm design. He has made significant contributions to problems involving minor-closed graph classes, treewidth, and graph modification. His work bridges theoretical foundations with algorithmic applications, particularly in discrete optimization and network problems. The recent articles highlight a strong trend in parameterized algorithms, especially for graph modification, kernelization, and structural graph problems. Topics such as hitting minors, dynamic programming on tree decompositions, and edge contractions reflect a deep engagement with structural parameterizations and fixed-parameter tractability. His publications frequently appear in top-tier journals like SIAM Journal on Computing, Journal of Combinatorial Theory, and Algorithmica, as well as major conferences such as ICALP, SODA, and IPEC. Best paper award of Track C of ICALP'10 Best student paper award of WG'09 Ignasi Sau has been a principal investigator of the ANR JCJC project ELIT (ANR-20-CE48-0008-01), funded with 169k€ from 2021 to 2026. He serves as an editor for DMTCS and Information and Computation , and has held significant organizational roles, including PC member of numerous conferences (MFCS, WG, IPEC, COCOON) and as co-chair and main organizer of WG 2019, ICGT 2022, and JCALM 2023. He has delivered invited courses at international schools in France, Argentina, and Brazil. He is actively involved in the research community through editorial duties, conference organization, and collaborative research. His lab affiliation is the AlGCo team at LIRMM, a leading group in algorithmic graph theory and combinatorics.

Frank-Martin Belzمشاهده پروفایل

استاد

• Sustainable Entrepreneurship
• Sustainability Marketing
• Corporate Sustainability
• +۳ مورد دیگر

Prof. Dr. Frank-Martin Belz is a full professor of corporate sustainability at the TUM School of Management and Director of the TUM SEED Center, a global interdisciplinary research hub. His career includes studies in business administration at the University of Mannheim (1990), followed by doctoral and post-doctoral research at the University of St. Gallen in Switzerland. He has conducted extensive research stays in Sweden, the USA, Canada, and Finland. His research focuses on sustainable entrepreneurship, sustainability marketing, and community-based enterprise creation. He emphasizes integrating social identity theory and structuration theory into entrepreneurial processes, particularly in environmental and social contexts. His work bridges academic theory with practical applications, including innovative approaches to consumer integration in product development and sustainability-driven marketing strategies. Key achievements include the award-winning textbook "Sustainability Marketing: A Global Perspective" (2010) and influential publications on sustainable entrepreneurship models and community-based enterprises. He actively promotes cross-sector collaboration through his leadership at the TUM SEED Center, fostering global partnerships in sustainability research and education.

• Artificial Intelligence
• Battery Technology
• Digitalization
• +۷ مورد دیگر

Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.

Aliaksandr Bandarenkaمشاهده پروفایل

استاد

• Electrocatalysis
• Energy Conversion
• Energy Storage
• +۵ مورد دیگر

Prof. Dr. Aliaksandr Bandarenka is a Professor at the Technical University of Munich (TUM) in the TUM School of Natural Sciences , leading the Assistant Professorship of Physics of Energy Conversion and Storage . His research focuses on electrochemical surface science and energy materials development. Education: PhD in Chemistry from Belarusian State University (2005) Key Collaborations: Ruhr University Bochum, University of Twente, Technical University of Denmark Prof. Bandarenka's research explores: Design of electrocatalytic materials via bottom-up approaches Characterization of electrified interfaces Development of sustainable energy conversion/storage systems Surface structure-activity relationships in catalysis Recent article trends (2024) include: ORR electrocatalyst optimization using ZIF-8 templating Advanced impedance spectroscopy for battery/electrolyzer diagnostics Mesoporous oxide materials for energy applications Surface structure effects on double layer capacitance Scientific Recognition: Ernst Haage-Prize (2016) Hans-Jürgen Engell Award (2013) He teaches graduate courses on: Electrified interfaces Energy materials science Electrocatalysis fundamentals Hands-on experiments in battery technology

Carsten Nowakمشاهده پروفایل

استاد پژوهشی

• Conservation Genetics
• Wildlife Monitoring
• Environmental DNA (eDNA) Analysis
• +۵ مورد دیگر

Dr. Carsten Nowak serves as Head of Conservation Genetics at the Senckenberg Research Institute and Natural History Museum Frankfurt, where he leads the national reference center for genetic analyses of wolves and lynx. His work bridges cutting-edge molecular methods with practical conservation applications, focusing on wildlife monitoring and species preservation. Since 2010, his laboratory has been responsible for central examination of all samples collected through Germany's nationwide wolf and lynx monitoring programs. Nowak's research interests center on developing highly sensitive molecular marker systems for wildlife monitoring, with particular expertise in environmental DNA (eDNA) methods and SNP chips optimized for genotyping forensic and non-invasively collected environmental samples. His work addresses critical questions in conservation biology, including inbreeding, genetic impoverishment, population origins, and human environmental impacts on genetic population structures of native species. He investigates how genetic methods can clarify previously unanswered questions in nature conservation, where data limitations often hinder efficient and targeted conservation measures. His extensive publication record (2023-2025) reveals a strong focus on wolf population dynamics across Europe, hybridization detection methodologies, and conservation genomics of endangered species like the garden dormouse. Nowak's research demonstrates sophisticated approaches to tracking animal movements across national borders, assessing genetic diversity in recovering populations, and developing practical tools for non-invasive wildlife monitoring. His work on wolf-dog hybridization has particular policy relevance as wolf populations expand across Europe. As a public-facing scientist, Nowak regularly engages with policymakers and the public through presentations, media appearances, and citizen science projects. He has participated in high-profile events including briefings for Federal Environment Minister Svenja Schulze and numerous public lectures on wildlife conservation topics. His leadership extends to coordinating international research collaborations, including the CEwolf Consortium and various transboundary monitoring networks. Nowak directs the Center for Wildlife Genetics in Gelnhausen, where his team conducts DNA-based analyses of predator-prey interactions, livestock depredation incidents, and wildlife population monitoring. His laboratory serves as the national reference center for genetic analyses of wolves and lynx in Germany, processing samples from across the country to distinguish individuals, determine relatedness, and monitor population health. The center also develops molecular methods for detecting wolf-dog hybrids and other conservation genetics applications.

Viktor Leisمشاهده پروفایل

استاد

• Database Systems
• Cloud Computing
• Data Management
• +۳ مورد دیگر

Prof. Dr. Viktor Leis is a Professor in the Department of Computer Science at the Technical University of Munich (TUM), leading the Chair for Decentralized Information Systems and Data Management. His research focuses on cost-efficient data systems, particularly in cloud environments, with expertise in core database topics like query processing, transaction management, and storage optimization. He earned his PhD from TUM in 2016 and previously held professorships at Friedrich Schiller University Jena and Friedrich-Alexander-Universität Erlangen-Nürnberg before returning to TUM in 2022. His work has been recognized with prestigious awards, including the ACM SIGMOD Dissertation Award, VLDB Early Career Research Contribution Award, and an ERC Starting Grant. Research Interests: Cloud computing, database systems, query optimization, storage engines, transaction processing, and NVMe-optimized systems. Key Projects: Developed the LeanStore storage engine and contributed to the Hyper database system. His recent publications emphasize cloud-native architectures, high-performance storage solutions, and hybrid transactional/analytical processing. He actively teaches courses on distributed systems, cloud databases, and blockchain technologies.

Nicola Breugstمشاهده پروفایل

استاد

• Entrepreneurship
• Psychology of Entrepreneurship
• Entrepreneurial Teams
• +۳ مورد دیگر

Prof. Nicola Breugst is a Professor of Entrepreneurial Behavior at the TUM School of Management, Technical University of Munich. Her research focuses on the psychological dimensions of entrepreneurship, particularly the interplay between founders' thought processes, emotions, and their social/environmental contexts. She explores how entrepreneurial teams influence decision-making, employee motivation, and venture success. Her work challenges the 'lone entrepreneur' myth, emphasizing systemic interactions between founders and their ecosystems. Education: B.A. in Psychology from Ludwig Maximilian University of Munich; Ph.D. in Entrepreneurship from Friedrich Schiller University Jena. Professional Experience: Held academic roles at the University of Duisburg-Essen, Max Planck Institute for Economics, Indiana University Kelley School of Business, and National University of Singapore. Research Interests: Entrepreneurial cognition, team dynamics, equity distribution, founder relationships, and the socio-economic factors shaping new ventures. Notable contributions include studies on trust in teams, envy's role in performance, and pivoting strategies in uncertain markets. Awards: 2022 Teaching Excellence Award (TUM School of Management), 2020 Best Paper in Entrepreneurial Cognition (Academy of Management), and multiple recognitions for mentorship and scholarly contributions. Grants/Advising: Extensive supervision of doctoral students (2018 award), with research supported by international collaborations. Active in entrepreneurial education and cross-cultural studies.

Christian Mayerمشاهده پروفایل

استاد

• Origin of life
• Nanocapsules
• NMR spectroscopy
• +۵ مورد دیگر

Prof. Dr. Christian Mayer is a Professor in Physical Chemistry at the Faculty of Chemistry, University of Duisburg-Essen. He serves as Head of the working group focusing on origin of life research, nanocapsules, and NMR spectroscopy techniques. His research group is located at Universitätsstraße 5, D-45141 Essen, Germany, with contact information including phone number +49 201 183-2570. Prof. Mayer's research interests primarily focus on the origin of life in deep tectonic fault zones of the first continental fragments, where he collaborates with Prof. Dr. Ulrich Schreiber from the Faculty of Biology and Prof. Dr. Oliver Schmitz from Applied Analytical Chemistry. His work investigates how vesicle formation occurs in tectonic fault systems through cyclic phase transitions of carbon dioxide, creating ideal conditions for molecular evolution. He specializes in pulsed field gradient NMR (PFG-NMR), high-resolution NMR, and solid-state NMR techniques to characterize nanoscale systems including nanocapsules, vesicles, and microemulsions. His recent publication trends reveal a strong interdisciplinary focus spanning physical chemistry, prebiotic chemistry, and astrobiology. The articles demonstrate increasing integration of computational methods with experimental approaches, particularly in analyzing molecular structures and dynamics. His research has evolved from fundamental studies of nanocapsule systems to broader investigations of protocell formation mechanisms under early Earth conditions, with recent work extending to astrobiological contexts including potential life formation on Titan. Prof. Mayer has established significant collaborations across multiple disciplines, particularly with geologists and biologists, to investigate the physical chemical processes that could have led to the emergence of life. His work bridges fundamental physical chemistry with practical applications in nanomedicine, particularly in developing artificial oxygen carriers based on nanocapsule technology. His laboratory utilizes high-pressure facilities to simulate early Earth crust conditions, with a particular focus on supercritical CO 2 environments. The working group combines experimental approaches with theoretical modeling to understand vesicle formation processes and their implications for the origin of cellular life.

Ohad Friedمشاهده پروفایل

دانشیار

• Computer Graphics
• Computer Vision
• Generative AI (GenAI)
• +۵ مورد دیگر

Ohad Fried is an Associate Professor of Computer Science at Reichman University. He was previously a postdoctoral research scholar at Stanford University under Prof. Maneesh Agrawala and completed his PhD with Prof. Adam Finkelstein as part of the Princeton Graphics group. He holds an M.Sc. in Computer Science and a B.Sc. in Computational Biology from The Hebrew University. His research lies at the intersection of computer graphics, computer vision, and Generative AI , focusing on tools, algorithms, and paradigms for photo and video editing and synthesis . His work has been widely recognized in top conferences including CVPR, SIGGRAPH, and ECCV, with recent contributions to tiled diffusion models, expressive 4D facial motion generation, and synthetic image detection. Ohad has received numerous awards, including the Israel Science Foundation personal research grant (2021) , the Outstanding faculty researcher at Reichman University (2022) , and the Siebel Scholar award (2017) . He has advised multiple students in research projects, and his work is covered by media outlets like Wired , The Washington Post , and CNN . Teaching roles include courses at Reichman University such as "GenAI for Games & Entertainment" and "Synthetic Media Detection", and at Stanford University "Computational Video Manipulation". Key Research Themes: Neural Rendering Diffusion Models 3D Facial Animation Image/Video Editing Media Forensics Scientific Awards: ISF Personal Grant (2021) Siebel Scholar (2017) Google PhD Fellowship (2014-2016) Gordon Y.S. Wu Fellowship (2012-2013) Excellence Scholarships

• Membrane Proteins
• Structural Biology
• Biochemistry
• +۵ مورد دیگر

Hartmut Michel is a Scientific Member and Director at the Max Planck Institute of Biophysics in Frankfurt, Germany, where he leads the Department of Molecular Membrane Biology. He has held this position since 1987 and has also served as an Adjunct Professor at the University of Frankfurt since 1989. Michel received his PhD in Biochemistry from the University of Wuerzburg in 1977 and completed postdoctoral work there before joining the Max Planck Institute of Biochemistry as a research associate. Michel's research focuses on membrane proteins, particularly in the areas of structural biology, biochemistry, photosynthesis, and respiratory complexes. His work has centered on understanding the structure and function of membrane proteins, especially cytochrome c oxidase and photosynthetic reaction centers. He pioneered techniques for membrane protein crystallization and has made significant contributions to understanding electron transfer processes and proton pumping mechanisms in respiratory enzymes. His publication record spans over four decades, with recent work focusing on cryo-EM structural analysis of membrane proteins including cytochrome bd oxidases, ABC transporters, and photosynthetic complexes. The research demonstrates a consistent trajectory from fundamental structural studies toward understanding functional mechanisms and applications in areas like antibiotic development and bioenergetics. Scientific Awards 1986 Leibniz Prize of the German Research Foundation 1988 Otto Bayer Prize (with Johann Deisenhofer) 1988 Nobel Prize in Chemistry (with Johann Deisenhofer and Robert Huber) 2008 Keilin Medal of the British Biochemical Society Honorary doctorates from the Universities of Wuerzburg and Bologna Michel has maintained an active research program with numerous collaborations across Europe and internationally. His laboratory has developed innovative approaches for membrane protein expression, purification, and structural characterization. The team has made significant contributions to understanding the structure-function relationships in respiratory chain components and photosynthetic apparatus. His department at the Max Planck Institute serves as a leading center for membrane protein research, with specialized facilities for protein crystallization, cryo-electron microscopy, and functional characterization of membrane proteins. The research has implications for understanding fundamental biological energy conversion processes and developing new therapeutic approaches targeting membrane proteins.

Carolin Vollenbergمشاهده پروفایل

پژوهشگر ارشد

• Business Process Management
• Digital Transformation
• Process Mining
• +۳ مورد دیگر

Dr. Carolin Vollenberg serves as a Post-Doctoral Researcher at the Chair of Information Systems & Transformation Management within the Faculty of Computer Science at the University of Duisburg-Essen (UDE). Her academic journey includes a PhD from the University of Muenster (2021-2025), an M.Sc. in Technical Consulting and Management from Hochschule Hamm-Lippstadt (2018-2020), and a B.Eng. in Biomedical Technology from the same institution (2014-2018). Prior to her current position, she worked as a Research Assistant at South Westphalia University of Applied Sciences and gained industry experience at Zapp Systems GmbH. PhD in Business Informatics (2021-2025), University of Muenster M.Sc. Technical Consulting and Management (2018-2020), Hochschule Hamm-Lippstadt B.Eng. Biomedical Technology (2014-2018), Hochschule Hamm-Lippstadt Research Focus: Vollenberg specializes in the governance of lightweight IT systems, digital transformation in public and healthcare sectors, and process mining applications. Her work bridges technical implementation with organizational behavior, particularly examining resistance to automation in sensitive domains like healthcare. She investigates how organizations navigate unintended consequences of technology adoption, with emphasis on RPA (Robotic Process Automation), omnichannel transformation, and data-driven process optimization. Her research methodology combines ethnographic field studies with quantitative process analysis. Publication Trends: Analysis of her 16 publications (2020-2025) reveals strong focus on healthcare IT (45% of works), public sector digitalization (30%), and foundational process management (25%). Recent output shows increasing emphasis on ethical dimensions of process mining and sustainability applications. Her collaborative work spans multiple European institutions with consistent publication in top IS conferences (ICIS, ECIS, HICSS). Best Paper nomination at HICSS-55 (2022) Associate Editor for General Track at Internationale Tagung Wirtschaftsinformatik (WI) 2025 Professional Engagement: Vollenberg actively contributes to academic discourse through editorial roles and peer review. Her industry collaborations with healthcare providers and public sector entities demonstrate applied research impact. Current projects examine virtual nursing transformations and crisis-responsive RPA implementations, reflecting her commitment to solving real-world operational challenges through information systems innovation.

• Precision Psychiatry
• Machine Learning in Psychiatry
• Psychosis Prediction
• +۵ مورد دیگر

Nikolaos Koutsouleris serves as a Research Professor leading the Precision Psychiatry team at the Max Planck Institute of Psychiatry in Munich, Germany. He directs the KOUTSOULERIS LAB, which focuses on developing advanced machine learning methodologies for clinical psychiatry applications. His work bridges computational neuroscience, clinical psychology, and precision medicine approaches to transform psychiatric diagnosis and treatment. Dr. Koutsouleris's research program centers on precision psychiatry, with particular emphasis on multimodal data integration for predicting psychiatric outcomes. His laboratory develops sophisticated machine learning workflows that combine neuroimaging, clinical assessments, genetic information, and biomarker data to create personalized prediction models. This approach enables more accurate identification of individuals at risk for psychosis and other psychiatric disorders, facilitating earlier intervention and tailored treatment strategies. Analysis of Dr. Koutsouleris's publication record reveals a consistent trajectory toward increasingly sophisticated applications of artificial intelligence in psychiatry. His recent work demonstrates a shift from single-modality prediction to complex multimodal frameworks that capture the heterogeneous nature of psychiatric conditions. Key themes include addressing methodological challenges in clinical prediction generalizability, exploring neurobiological underpinnings of mental illness through advanced analytics, and translating computational findings into clinically actionable tools. As leader of the KOUTSOULERIS LAB at the Max Planck Institute of Psychiatry, Dr. Koutsouleris oversees a multidisciplinary research environment that brings together computational scientists, clinicians, neuroscientists, and data analysts. His team collaborates extensively with international consortia to validate prediction models across diverse populations, ensuring robustness and clinical applicability of their findings. The laboratory serves as a nexus for innovation in computational psychiatry, driving methodological advances while maintaining strong connections to clinical practice.

Niels Dingemanseمشاهده پروفایل

استاد

• Behavioural Ecology
• Evolutionary Ecology
• Animal Personality
• +۴ مورد دیگر

Niels Dingemanse is a tenured Professor of Behavioural Ecology at Ludwig Maximilians University (LMU) in Munich, Germany, and leads the Evolutionary Ecology of Variation research group at the Max Planck Institute for Ornithology. His academic journey includes roles as a Postdoctoral Research Fellow at the University of Groningen and the University of Wales, Bangor. He holds a PhD in natural sciences from Utrecht University (2003) and an M.Sc. in Ecology from the University of Groningen (1997). His research focuses on evolutionary and behavioural ecology, particularly the ecological and evolutionary significance of individual variation in behaviour, physiology, and life-history traits. Key themes include personality evolution, indirect genetic effects, and the integration of genomic approaches with ecological field studies. Dingemanse has contributed to projects like the Great Tit HapMap initiative, exploring genomic variation across continental scales. Publications emphasize interdisciplinary methods, combining field experiments with genomic and statistical tools. His work addresses topics such as mate choice evolution, the role of environmental fluctuations in shaping social plasticity, and the genetic basis of vocal rhythms in birds. Grants and fellowships include the Veni Innovational Research Incentives Scheme (Netherlands Organisation for Scientific Research) and ALW open competition grants. He has advised numerous postdoctoral researchers and leads collaborative projects across Europe.

Stephan A. Sieberمشاهده پروفایل

استاد

• Bioorganic Chemistry
• Antibiotic Development
• Chemical Proteomics
• +۵ مورد دیگر

Professor Stephan A. Sieber is a leading researcher in bioorganic chemistry at the Technical University of Munich (TUM), where he holds the Chair of Organic Chemistry II within the TUM School of Natural Sciences. His research program focuses on developing new drugs against multidrug-resistant bacteria through a multi-disciplinary approach that integrates synthetic chemistry, functional proteomics, microbiology, and protein biochemistry. His laboratory has made significant contributions to identifying unprecedented antibacterial targets beyond the scope of current antibiotics and exploiting these for chemical manipulation. Recent work has increasingly incorporated machine learning approaches to accelerate antibiotic discovery, with notable publications on AI-guided pipelines, drug-target interaction prediction, and high-throughput screening optimization. Sieber's research has resulted in the discovery of new active substances, some of which are currently being optimized for medical applications. His group's publications reveal a strong focus on chemical proteome mining, natural product mode of action studies, and novel antibacterial target identification. The lab has published extensively in top journals including Nature Chemistry, Nature Communications, and ACS Central Science. Inhoffen Medal (2024) Max Bergmann Medal (2023) ERC Advanced Grant (2023) Merck Future Insight Prize (2020) Klaus Grohe Prize (2020) ERC Consolidator Grant (2016) Professor Sieber leads an active research group that maintains a strong presence in the scientific community through regular publications, conference presentations, and collaborations. His laboratory website and BlueSky presence (@sieberlab.bsky.social) demonstrate ongoing research activities and engagement with the broader scientific community. He has successfully secured significant research funding including multiple ERC grants that have supported his innovative work in antibiotic discovery.

• Bioorganic Chemistry
• Chemical Biology
• Organic Chemistry
• +۵ مورد دیگر

Prof. Dr. Norbert Sewald, Chair of Organic and Bioorganic Chemistry at Bielefeld University, is a leading figure in Bioorganic Chemistry , Chemical Biology , and Enzymatic Halogenation . As head of the Organic and Bioorganic Chemistry Group at the Center for Biotechnology (CeBiTec), he drives research on natural products and drug conjugates. Full Professor, Bielefeld University (since 1999) Founding Coordinator, International Graduate School of Chemistry and Biochemistry (2001-2003) Chairman, Institute of Biochemistry and Bioengineering at CeBiTec (2006-2008) Dean, Department of Chemistry (2008-2011) Chairman, Max-Bergmann-Kreis e.V. (since 2010) Coordinator, Marie Skłodowska-Curie Training Networks (MAGICBULLET, 2015-2018; Magicbullet::reloaded, 2020-2023) His research focuses on halogenases for mild peptide bromination, cryptophycin-based tumor targeting , and bioactive natural products from African flora. Collaborative projects span antiplasmodial agents , antibacterial compounds , and neurodegenerative disease inhibitors . Recent work highlights include: Enzymatic halogenation cascades Click-to-release drug conjugates Fluorescent probes for amyloid detection Key affiliations: Faculty of Chemistry Center for Biotechnology (CeBiTec) European Peptide Society (Scientific Affairs Officer, 2016-) Leibniz Institute of Plant Biochemistry (Scientific Advisory Board, 2010-2017)