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Vasileios AngelidakisView profile

Professor

• Discrete Element Modeling
• Granular Materials
• Particle Dynamics
• +3 more

Prof. Vasileios Angelidakis is a Professor at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specializing in Discrete Element Method (DEM) modeling, granular materials, and particle dynamics. His research focuses on numerical simulations of particulate systems, including particle shape characterization, DEM framework comparisons, and applications in additive manufacturing, railway ballast, and material science. He has collaborated internationally, contributing to open-source DEM software like MercuryDPM and Yade, and has published extensively on topics such as clump dynamics, thermal-particle interactions, and global benchmark studies on granular behavior. He has also worked on seismic engineering, analyzing structural responses to earthquake-induced ground motion. Education: PhD in Engineering (Newcastle University, 2022), MSc in Structural Engineering (National Technical University of Athens, 2016), Diploma in Civil Engineering (National Technical University of Athens, 2014). Research Interests: DEM modeling, particle shape effects, granular flow, computational mechanics, additive manufacturing processes, and seismic structural analysis. Publications highlight his work on open-source frameworks, particle morphology analysis, and validation studies across disciplines. His contributions include algorithms for rotational motion integration and tools like CLUMP and SHAPE for particle representation.

Bernd MeyerView profile

Professor

• Computational Chemistry
• Materials Science
• Surface Chemistry
• +6 more

Prof. Dr. Bernd Meyer is a Professor of Computational Chemistry at the Department of Chemistry and Pharmacy, Friedrich-Alexander University Erlangen-Nuremberg. His research bridges theoretical and experimental approaches to investigate nanomaterials, surface chemistry, and molecular dynamics. Computational Chemistry Materials Science Surface Stability Molecular Dynamics Nanomaterials Photovoltaics Organic-Inorganic Hybrids Recent publications focus on adsorption mechanisms of molecules on metal oxides, design of porphyrin-based hybrids with tunable optoelectronic properties, and algorithm optimizations for ab initio molecular dynamics. His work integrates first-principles simulations with experimental validation to address challenges in energy materials and surface engineering. Contact: bernd.meyer@fau.de | Room 2.308, Nägelsbachstraße 25, Erlangen | Phone: +49 9131 85-20403

• Stochastic Analysis
• Optimal Transport
• Ricci Flows
• +3 more

Eva Kopfer is an Associate Professor at the University of Bonn's Institute for Applied Mathematics, Department of Stochastic Analysis. Her research focuses on stochastic analysis, optimal transport theory, Ricci flows, and geometric analysis. She has led courses on stochastic analysis, financial mathematics, and advanced calculus. Notable contributions include work on exponential ergodicity for kinetic SDEs, stochastic homogenization of transport problems, and quantum gravity measures on manifolds. Her research interests bridge probability theory, differential geometry, and functional analysis, with applications to geometric flows and metric measure spaces. Recent work explores conformally invariant random fields, polyharmonic structures in quantum gravity, and generalized Ricci flow dynamics. She has collaborated extensively on projects involving discrete-to-continuous limits in optimal transport and Liouville quantum gravity measures. Publications highlight advancements in stochastic differential equations, ergodic theory, and geometric PDEs. Her work often integrates probabilistic methods with geometric analysis, yielding insights into transport phenomena and manifold structures. Current research themes include non-equilibrium systems, functional inequalities, and random geometric structures. Eva Kopfer's academic contributions are evident in high-impact journals like Journal of Functional Analysis and Communications in Pure and Applied Mathematics. She actively engages in seminar series and lecture series at the University of Bonn, covering topics from stochastic calculus to frontiers in economics and mathematics.

• Atomic Physics
• Quantum Optics
• Nonlinear Optics
• +3 more

Prof. Dr. Manfred Lein is a Professor at the Institute of Theoretical Physics within the Faculty of Mathematics and Physics at Leibniz University Hannover. He holds key roles including Dean of Studies in the Faculty and membership in the Executive Board of the Institute. His research focuses on ultrafast quantum phenomena, strong-field ionization, and high-order harmonic generation (HHG), with contributions to attosecond science and machine learning applications in quantum systems. His work bridges theoretical modeling and experimental techniques, including the use of bicircular attoclocks and neural networks for molecular imaging. Positions: Dean of Studies (Faculty of Mathematics and Physics), Executive Board Member (Institute of Theoretical Physics), Professor Contact: manfred.lein@itp.uni-hannover.de | +49 511 762 3291 Lab: Group website: lein group Research interests emphasize electron dynamics in strong laser fields, molecular structure retrieval via HHG, and ultrafast processes. His articles highlight advancements in attosecond timing, Coulomb effects, and quantum control using THz and bicircular fields.

• plasticity
• material damage
• multiscale simulations (MD, DDD, FEM)
• +4 more

Dr. Yi Hu is a researcher at the Max Planck Institute for Sustainable Materials , affiliated with the Department of Microstructure Physics and Alloy Design within the Theory and Simulation research group. His work focuses on computational materials science and multiscale modeling of structural materials. Research interests include: Plasticity and material damage mechanisms Multiscale simulations (Molecular Dynamics, Discrete Dislocation Dynamics, Finite Element Method) Computational methods like topology optimization, machine learning, and phase field modeling Development of DAMASK (Düsseldorf Advanced MAterial Simulation Kit) Recent publications highlight his expertise in precipitate strengthening of aluminum alloys, dislocation dynamics, and multiscale modeling. He collaborates on code development and has contributed to advancing computational frameworks for material simulations. Key affiliations: Max Planck Institute for Sustainable Materials, Düsseldorf, Germany.

Rudolf JuchelkaView profile

Professor

• Economic Geography
• Transport Geography
• Logistics
• +4 more

Prof. Dr. Rudolf Juchelka is a Professor of Economic Geography, Transport & Logistics at the Institute of Geography , University of Duisburg-Essen, Germany. He has held this position since 2001 and served as governing director of the institute. His work focuses on economic geography transport systems logistics networks urban redevelopment sustainable mobility globalization impacts Educational Background: Geography, Economics, German Studies, Education at RWTH Aachen and University of Bonn PhD in Geography (1997) from RWTH Aachen Habilitation (2004) in Geography at RWTH Aachen His research interests span economic and transport geography, with emphasis on logistics clusters, sustainable mobility, urban cable cars, airport cities, and structural change in industrial regions. His publications highlight trends in logistics networks, urban transport, and globalization’s effects on transport hubs like Dubai. Recent work includes studies on micro-mobility and urban freight optimization. Scientific Awards: Diversity Prize, UDE (2017) Teaching Award, UDE (2008) BMW Scientific Award (1995) He advises institutions on transport and logistics , including the German Savings Bank Association (DSGV) and regional governments. His lectures cover topics like urban cable cars, mobility transitions, and global logistics trends. He is involved in institutions like the Zentrum für Logistik und Verkehr (ZLV) and the Deutsche Gesellschaft für Geographie .

• Radiopharmaceutical Cancer Research
• Molecular Imaging
• Cancer Biology
• +3 more

Prof. Dr. Jens Pietzsch is the Head of the Radiopharmaceutical and Chemical Biology department at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). His research focuses on radiopharmaceutical cancer research, molecular imaging, and therapeutic targeting of cyclooxygenase (COX) pathways. His work bridges medical imaging , oncology , and pharmaceutical chemistry , with a strong emphasis on neuroendocrine tumors, melanoma, and prostate cancer. Institutional Affiliation : Helmholtz-Zentrum Dresden-Rossendorf (HZDR) Department : Radiopharmaceutical and Chemical Biology Prof. Pietzsch's research integrates radiopharmacology , bioinorganic chemistry , and biomaterials . Key areas include: Development of COX-2 inhibitors as anti-cancer agents Radiolabeled peptides for PET/SPECT imaging Design of theranostic radionuclide pairs (e.g., 133La/225Ac) Investigation of macrophage-tumor interactions in glioma progression His recent publications (2024-2026) highlight trends in carborane-based drug analogs , NO-releasing therapeutics , and multimodal imaging for tumor targeting. Articles emphasize PSMA ligands , Eph receptor imaging , and biomaterial platforms for cancer modeling.

Dörte WittenburgView profile

Research Professor

• Statistical Genetics
• Quantitative Trait Loci (QTL) Analysis
• Genomic Selection
• +3 more

Dörte Wittenburg is a Research Professor at the Research Institute for Farm Animal Biology (FBN) , leading the Working Group Statistics in Genomics since 2019 and the Focus Topic Promoting Diversity in Animal Farming . She contributes to the Master Programme Sustainable Agricultural Systems at University Rostock and has authored 15+ articles on statistical genomics. Education : Habilitation (2021), PhD in Biomathematics (2008), Diploma in Business Mathematics (2005) Research Interests include: Statistical methods for genetic effects on quantitative traits Penalized regression with genomic dependencies Population-genetic parameter estimation (linkage disequilibrium, recombination rates) Article Trends focus on: Genomic selection and QTL analysis Machine learning in agricultural genetics Sex-specific and species-specific recombination mapping Admixture and family structure modeling Scientific Awards : DGFZ Preis 2020 (Masterarbeiten) for Estimation of genetic parameters of milk urea content Advising involves offering master theses in animal breeding at University Rostock. Grants include funding for projects like Improving genome-based phenotype prediction (2013-2018) and BovIBI Bovine Integrative Bioinformatics for Genomic Selection (2008-2012).

Bianca Maria ColosimoView profile

Professor

• Metal Additive Manufacturing
• Statistical Process Control
• Image Data Analysis
• +3 more

Prof. Bianca Maria Colosimo is a faculty member at Politecnico di Milano in the Department of Mechanical Engineering. Her research focuses on in-situ sensing and monitoring of metal additive manufacturing (AM) processes, particularly Laser Powder Bed Fusion. She develops statistical data mining techniques for defect detection and process control, integrating big data streams into quality assurance systems. Her work aims to advance smart AM technologies through real-time monitoring and digital twin methodologies. Key research interests include: Metal Additive Manufacturing Statistical Process Control Image Data Analysis Laser Powder Bed Fusion In-situ Monitoring Smart Manufacturing Systems Publications highlight her contributions to layerwise imaging , plume signature analysis , and spatial statistical modeling for AM processes. Contact: Department of Mechanical Engineering, Politecnico di Milano.

André NusserView profile

Researcher

• Algorithms and Complexity
• Computational Geometry
• Dynamic Time Warping
• +4 more

André Nusser is a CNRS Researcher affiliated with the COATI group at Inria Center, Université Côte d’Azur. His work focuses on algorithms, computational geometry, and metric space analysis, particularly around the Fréchet distance, dynamic time warping, and graph hyperbolicity. Current Position: CNRS Researcher at Inria Université Côte d’Azur Primary Research Areas: Algorithms & Complexity, Computational Geometry, Metric Space Analysis Research Focus: André's research explores geometric optimization problems, trajectory analysis, and fine-grained complexity. Key contributions include advancements in dynamic time warping under translation, diameter computation for intersection graphs, and efficient algorithms for polygon partitioning. Awards & Recognition: Recipient of the Best Paper Award at VLDB 2014, Honorable Mention at AAAI 2014, and Best Poster Runner-up at SIGSPATIAL 2019. His work on Hausdorff distance and graph hyperbolicity has been invited to special issues. Academic Collaborations: Co-author on over 20 publications across conferences like STOC, SoCG, SODA, ESA, and journals including ACM Transactions on Algorithms and Discrete & Computational Geometry. Collaborates with leading researchers in computational geometry and algorithms. Software Advocacy: Actively promotes free software in research, highlighting tools like Ipe, Xournal++, Zotero, and Zulip for scientific productivity and collaboration.

Alessandro NeriView profile

Researcher

• Algebraic Coding Theory
• Finite Geometry
• Finite Fields
• +4 more

Alessandro Neri is a postdoctoral researcher in mathematics at Ghent University, Belgium, since October 2022, supported by the Research Foundation Flanders (FWO). Previously, he was a postdoctoral researcher in the Nonlinear Algebra group at the Max Planck Institute for Mathematics in the Sciences (2021–2022), and held an Early Postdoc.Mobility Fellowship from the Swiss National Science Foundation (2019–2021) at INRIA Saclay and Technical University of Munich. He earned his PhD in Mathematics from the University of Zurich in 2019 under Joachim Rosenthal. Current affiliation: Ghent University, Department of Mathematics: Analysis, Logic and Discrete Mathematics Prior affiliations: Max Planck Institute for Mathematics in the Sciences, University of Zurich, INRIA Saclay, Technical University of Munich His research focuses on Algebraic Coding Theory , particularly rank-metric codes , connections with finite geometry , finite fields , and combinatorics . His work explores algebraic structures like skew polynomial rings , evasive subspaces , and minimal codes , with applications to error correction and code design. Recent publications include studies on flag-rank metrics , symmetric rank-metric codes , and strong blocking sets , often in collaboration with leading experts in coding theory. Recent article trends highlight rank-metric and sum-rank codes (14/15), strong blocking sets (3/15), and symmetric structures (2/15). The work intersects algebraic geometry (7/15), combinatorics (6/15), and finite field theory (8/15), with applications to network coding and cryptography . Scientific Awards FWO Postdoctoral Fellowship Swiss National Science Foundation Early Postdoc.Mobility Fellowship He has no listed advisees but collaborates with 27+ researchers, including Daniel Augot, Antonia Wachter-Zeh, and Joachim Rosenthal. His work has been presented at 12+ international venues, such as the SIAM Conference on Applied Algebraic Geometry (2023) and Algebraic Methods in Coding Theory (2022). He co-organized the Coding Theory Colloquium (2023) and Algebraic Coding Theory Summer School (2022).

José Alejandro SamperView profile

Assistant Professor

• Algebraic Combinatorics
• Geometric Combinatorics
• Topological Combinatorics
• +5 more

Dr. José Alejandro Samper is an Assistant Professor of Mathematics at Pontificia Universidad Católica de Chile (PUC Chile), specializing in algebraic, geometric, and topological combinatorics. His research focuses on simplicial complexes, matroids, polytopes, and convex bodies, with a particular interest in the implications of linear orderings on matroids. Current affiliation: Mathematics Department, PUC Chile Previous positions: Postdoctoral fellow at Max Planck Institute for Mathematics in the Sciences (MPI), postdoc at ICERM and University of Miami PhD: University of Washington under Isabella Novik His research spans combinatorial structures with deep connections to algebraic geometry and topology, including studies on shellability, higher chordality, and matroidal relaxations. Recent publications highlight interactions between matroid theory, polytopes, and convex geometry, with a focus on topological constraints and Hopf algebraic structures. Dr. Samper co-organizes key mathematical events such as the Cibercoloquio Latinoamericano de Matemáticas and the Club de Matemáticas UC. He is accessible via email at jsamper@uc.cl.

Yang Shao-HornView profile

Professor

• Electrochemistry
• Catalysis
• Energy Storage
• +3 more

Yang Shao-Horn is the JR East Professor of Engineering at the Massachusetts Institute of Technology (MIT), holding appointments in the School of Engineering and Department of Materials Science and Engineering. She concurrently serves as a Hans Fischer Senior Fellow at the Technical University of Munich Institute for Advanced Study (TUM-IAS) since 2022, hosted by Professors Roland Fischer and Aliaksandr Bandarenka within the Molecular Designs of Site-Specific Activity focus group. Her educational background includes: Ph.D. in Metallurgical and Materials Engineering, Michigan Technological University Professor Shao-Horn's research pioneers the application of physical chemistry principles to engineer interfacial charge transfer and dynamics for climate-critical energy solutions. Her work spans sustainable fuel production (via water/CO 2 /nitrogen reduction) and high-energy lithium batteries, employing experimental techniques (synthesis, synchrotron X-ray, electron/light imaging) and computational methods (DFT, machine learning). Her group has developed foundational frameworks linking electronic/phononic structures to reaction kinetics and ion dynamics. Analysis of her publication record reveals dominant focus areas in electrocatalysis for renewable energy conversion, particularly oxygen evolution/reduction reactions. Her work consistently advances catalyst design (perovskites, metal-organic frameworks) and interfacial phenomena in energy storage, with increasing integration of machine learning for accelerated materials discovery across electrochemical systems. Her accolades include: Humboldt Prize in Chemistry (2020) Dr. Karl Wamsler Innovation Award (2020) Faraday Medal from Royal Society of Chemistry (2018) Battery Research Award of Electrochemistry Society (2016) She is also a National Academy of Engineering member and fellow of AAAS, Electrochemical Society, National Academy of Inventors, and International Society of Electrochemistry. Professor Shao-Horn has mentored 100+ students and postdocs at MIT, with alumni now leading research at Tesla, Amazon, Apple, national laboratories, and academic institutions worldwide (~40 faculty positions across US, Europe, and Asia). Her research program receives substantial funding from federal agencies and industry partners, supporting cutting-edge facilities for materials synthesis and characterization. Her MIT laboratory operates within the Research Laboratory of Electronics and MIT Energy Initiative, fostering global collaborations with universities and private/public sectors. Current initiatives include advanced battery systems, electrocatalysts for sustainable fuel production, and machine learning frameworks for materials design, all addressing urgent climate challenges through fundamental interfacial science.

Julian StingeleView profile

Professor

• DNA Repair
• Molecular Biology
• Genetics
• +7 more

Julian Stingele is a Professor (W2) at the Gene Center and Department of Biochemistry , Ludwig-Maximilians-Universität München, Germany. His research focuses on DNA repair mechanisms, particularly the resolution of DNA-protein crosslinks via proteases and ubiquitin signaling. PhD in Biology from Ludwig-Maximilians-Universität München (2015) Diploma in Biology from University of Konstanz (2010) His work bridges molecular and structural biology to uncover how cells maintain genome stability under DNA damage. Key areas include: DNA-protein crosslink repair Ubiquitin and SUMOylation in DNA damage response Protease functions in genome maintenance Transcription-coupled repair pathways Chemical carcinogenesis mechanisms RNA damage responses Julian's recent articles highlight advancements in DNA repair proteases (e.g., SPRTN, FANCJ), transcription-coupled repair pathways, and chemical methods for quantifying DNA lesions. His publications span high-impact journals like Cell , Nature Cell Biology , and Molecular Cell , emphasizing interdisciplinary approaches. Scientific Awards: 2023: ERC Consolidator Grant 'Deconstruct' 2021: Vallee Scholar Award 2020: EMBO Young Investigator 2019: Bayer Early Excellence in Science Award 2018: ERC Starting Grant 'DNAProteinCrosslinks' 2018: Alfried Krupp Prize for Young University Lecturers 2015: EMBO Long-Term Fellowship 2010: Max Planck Institute for Biochemistry Junior Research Award

Melanie SchmidtView profile

Professor

• Geometric Data Analysis
• k-means clustering
• Combinatorial Optimization
• +3 more

Professor Melanie Schmidt is a faculty member in the Department of Computer Science at Heinrich-Heine-Universität Düsseldorf, where she leads the Algorithms and Data Structures research group. Previously, she was affiliated with the University of Bonn's Institute of Computer Science, where she completed her PhD under Prof. Dr. Heiko Röglin and headed a subgroup on "clustering for big data" within his research group. Current Position: Professor at Heinrich-Heine-Universität Düsseldorf Previous Position: Researcher and lecturer at University of Bonn PhD Advisor: Prof. Dr. Heiko Röglin Her research focuses on geometric data analysis, particularly k-means clustering in data streams, combinatorial optimization, and approximation algorithms. Her work bridges theoretical computer science with practical applications in big data processing. She has made significant contributions to understanding the theoretical foundations of clustering algorithms while developing efficient implementations for real-world applications. Professor Schmidt's publication record shows a consistent evolution from theoretical analysis of k-means to practical implementations for big data environments. Her recent work explores fairness in clustering, privacy-preserving techniques, and efficient algorithms for high-dimensional data. She has published in top-tier conferences including SODA, ICALP, ESA, and ITCS, demonstrating both theoretical rigor and practical relevance. Best Student Paper Award at ESA 2012 (joint work with Martin Groß, Jan-Philipp W. Kappmeier, and Daniel Schmidt) She actively supervises numerous Master's and Bachelor's students, with current advisees including Lena Carta, Lukas Drexler, and Anna Arutyunova. Her research group includes members such as Anja Rey, Julian Wargalla, and Annika Hennes. She teaches advanced courses in algorithms and data structures, with a focus on randomized algorithms and efficient algorithm design for big data problems. Professor Schmidt leads the Algorithms and Data Structures research group at Heinrich-Heine-Universität Düsseldorf, which focuses on developing and analyzing efficient algorithms for fundamental computational problems, with particular emphasis on clustering, geometric data analysis, and big data applications.