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Researcher
PD Dr. Heike Böhm is a Group Leader in the Department of Cellular Biophysics at the University Heidelberg, specializing in glycosaminoglycan (GAG) interactions and their role in cellular behavior. She leads cross-disciplinary research integrating chemistry, biophysics, and materials science to study hyaluronan-rich cell coats and synthetic hydrogels.
Research Fellow
Dr. Hanieh Mianehrow is a postdoctoral researcher and Maria Skłodowska-Curie postdoctoral fellow at the Max Planck Institute of Colloids and Interfaces. She focuses on molecular dynamics simulations and experimental studies of cellulose-hemicellulose interactions, structural coloration in plants, and bio-inspired nanocomposite materials within the Department of Sustainable and Bio-inspired Materials led by Prof. Silvia Vignolini. Bachelor’s/Master’s in Polymer Engineering, Tehran, Iran PhD in Fiber and Polymer Science, KTH Royal Institute of Technology, Stockholm Her research explores the molecular mechanisms behind structural colors in fruits like Margaritaria nobilis, using molecular dynamics (MD) simulations to analyze xylan-cellulose interactions. She also investigates bio-nanocomposites of cellulose and graphene oxide, with applications in sustainable materials and mechanical reinforcement. Dr. Mianehrow’s publications focus on moisture effects in cellulose-graphene nanocomposites, interface engineering, and structural coloration. These works span nanotechnology, materials science, and computational modeling. Maria Skłodowska-Curie Postdoctoral Fellowship At the Max Planck Institute, she integrates advanced simulation techniques with experimental characterization to unravel the self-assembly processes in plant cell walls, aiming to develop novel bio-inspired materials with tailored optical and mechanical properties.
Researcher
Dr. Michael Goepel serves as a Researcher at the Institute of Technical Chemistry, University of Leipzig, specializing in sustainable catalytic processes for bioeconomy and CO 2 utilization. His work bridges chemical engineering and environmental science to develop innovative solutions for green chemistry applications. His research centers on Heterogeneous Catalysis , CO 2 Conversion , and Biomass Valorization , with emphasis on designing bifunctional catalysts for hydrodeoxygenation, hydrogenation, and dry reforming reactions. Key methodologies include nanomaterial synthesis (e.g., chitosan-derived carbons, Pd-nanomaterials), mechanochemical preparation techniques, and pore-structure optimization in catalyst supports to enhance mass transfer and reaction efficiency. Analysis of his 2015-2020 publications reveals a consistent focus on sustainable feedstocks (furfural, bio-oils, CO 2 ) and renewable energy carriers. His work integrates materials science with reaction engineering to address challenges in bioeconomy, particularly in converting waste streams into value-added chemicals through solar-driven and catalytic processes. Dr. Goepel has secured significant EU ERDF funding for projects including "New concepts of integrative bioeconomy" (2017-2020) on CO 2 upgrading with sunlight, and "Green biofilms for chemical catalysis" (2017-2020), collaborating with Heterogeneous Catalysis and Biology units. His research directly supports Leipzig's sustainability initiatives through technology development for circular chemical production.
Professor
Zhen Kan is a Professor in the Mechanical and Aerospace Engineering Department at the University of Florida's College of Engineering, with previous affiliations at the University of Iowa and the Air Force Research Laboratory (AFRL). His extensive publication record spans over 15 years with significant output in recent years, indicating an active research career in robotics and control systems. Dr. Kan's research focuses on advanced robotics systems with expertise in temporal logic motion planning, reinforcement learning, and human-robot interaction. His work bridges theoretical control systems with practical robotics applications, particularly in multi-robot coordination, autonomous systems, and wearable robotics. The research demonstrates a strong emphasis on formal methods for ensuring safety and correctness in complex robotic systems. Analysis of recent publications reveals a consistent research trajectory centered around temporal logic specifications for robotic systems, with increasing integration of machine learning techniques. His work shows progression from theoretical control frameworks to practical implementations in quadruped robots, exoskeletons, and multi-robot systems operating in dynamic environments. Dr. Kan has established significant collaborations with researchers across multiple institutions, particularly with Warren E. Dixon (35 co-authored papers), Zhijun Li (23 papers), and Mingyu Cai (22 papers), indicating leadership in collaborative research projects. His publications appear in top-tier venues including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, and International Journal of Robotics Research. While specific grant information isn't visible in the provided text, the volume and quality of publications suggest substantial research funding. Dr. Kan's work has practical applications in autonomous systems, human-robot collaboration, and assistive technologies, with potential impact in defense, healthcare, and industrial automation sectors.
Researcher
Arya Mazaheri is a Research Leader at PanocularAI, affiliated with the Technische Universität Darmstadt. His work bridges high-performance computing (HPC) and machine learning, focusing on optimizing large-scale computational systems. Based at Hochschulstr. 10, Darmstadt, Germany, he contributes to GPU acceleration, neural network pruning, and parallel processing. PhD in Performance Engineering of Data-Intensive Applications (2022) Key areas: HPC, Machine Learning, GPU Computing, Neural Network Pruning Research Trends: Mazaheri's publications from 2015-2024 reveal expertise in: Accelerating LLM inference through pipelined speculation Topology-aware network pruning with reinforcement learning GPU-based spacecraft trajectory simulations Performance portability in tensor operations Hardware-independent communication metrics for parallel systems
Researcher
Alexander Perzylo is a Researcher at fortiss , an affiliated institute of the Technical University of Munich (TUM) . He has been with fortiss since 2013 and previously worked as a Research Associate/Doctoral Student at TUM's Chair of Computer Science VI (Real-Time Systems and Robotics) from 2010 to 2013. He holds an M.Sc. and B.Sc. in Computer Science from TUM (2009 and 2005). Education B.Sc. in Computer Science, TUM (2005) M.Sc. in Computer Science, TUM (2009) His research focuses on robotics , semantic systems , Industry 4.0 , CAD analysis , and sustainability reporting ontologies . He specializes in knowledge representation, geometric constraints, and intuitive robot programming frameworks. Recent publications highlight trends in ontology-based CAD analysis , LLMs for geometric reasoning , semantic manufacturing processes , and knowledge-augmented socio-technical systems . His work bridges knowledge graphs , robotic assembly , and digital twins . Scientific Awards Best Cognitive Robotics Paper Award (2015) Perzylo has contributed to numerous EU H2020 , BMBF , and StMWi Bayern projects, including SMErobotics, RoboEarth, and DiProLeA. He has taught courses on Cognitive Robotics and Human-Robot Interaction at TUM since 2012.
Researcher
Sascha Dengler, M.Sc. , is a doctoral candidate at the Chair of Space Mobility and Propulsion within the School of Engineering and Design at the Technical University of Munich (TUM) . His work focuses on advancing Water Electrolysis Propulsion (WEP) technology for spacecraft, particularly for CubeSats, and optimizing operational strategies using Reinforcement Learning . He is also the project manager of S4I2T (Solar for Ice to Thrust) , an EIC-funded initiative demonstrating in-situ resource utilization for propulsion systems. Educated in Mechanical and Process Engineering at TU Darmstadt Specializes in transpiration cooling for additively manufactured thrust chambers Active in developing sustainable propulsion systems for European space programs
Professor
Dierk Raabe serves as Professor at RWTH Aachen University and Director of the Department of Microstructure Physics and Alloy Design at the Max Planck Institute for Sustainable Materials in Düsseldorf. His leadership spans computational materials science, sustainable metallurgy, and advanced alloy development, with emphasis on creating innovative materials for energy, mobility, and health applications through physics-based design approaches. Raabe earned his academic credentials at RWTH Aachen University, completing his Diploma (1984-1990, summa cum laude), Dr.-Ing. (1990-1992, summa cum laude), and Habilitation (1992-1997) in Metallurgy and Metal Physics. Prior to his doctoral studies, he attended Musikhochschule Rheinland (1983-1984) for music education. His research centers on integrating thermomechanical processing, atomic-scale characterization, and computational modeling to develop next-generation materials. Key focus areas include atom probe tomography, crystal plasticity finite element modeling, high-entropy alloys, and sustainable metallurgical processes. Raabe pioneered the DAMASK simulation toolbox for crystal mechanics and multiphysics property prediction. His distinctive approach combines theory, characterization, and development to invent alloys with exceptional strength, ductility, and damage tolerance while addressing hydrogen embrittlement and decarbonization challenges. Recent publications (2025) reveal strong emphasis on sustainable metallurgy, particularly hydrogen-based iron reduction and high-entropy alloy design. His team investigates atomic-scale hydrogen barriers, plasma reduction of iron ores, and sustainable aluminum recycling. The work bridges fundamental atomic phenomena with industrial applications for CO2-free metal production, showcasing his leadership in transforming materials science toward circular economy principles. Gottfried-Wilhelm-Leibniz Prize (2004) ERC Advanced Grants (2012, 2022) Acta Materialia Gold Medal (2022) Lee Hsun Lecture Award (2008) Weinberg Lecture Award (2011) Multiple Best-Paper Awards across major materials journals Membership in German National Academy of Sciences Leopoldina Raabe has supervised over 70 PhD students, many now holding leadership positions in global industry and academia. His research is supported by major grants including two ERC Advanced Grants and extensive industrial collaborations focused on sustainable materials development. He previously served on the German Science Council (2010-2016) and chaired RWTH Aachen's University Council (2012-2016). Leading the Department of Microstructure Physics and Alloy Design at the Max Planck Institute, Raabe directs teams combining experimental characterization (including state-of-the-art atom probe tomography) with computational modeling. Current flagship projects include CO2-free metal production through hydrogen plasma reduction and designing high-performance sustainable alloys, with the DAMASK simulation platform serving as a cornerstone for multi-scale materials design.
Professor
Prof. Dr.-Ing. Richard Membarth is a faculty member at Technische Hochschule Ingolstadt , where he holds the professorship for System-on-a-Chip and AI for Edge Computing. He is also affiliated with the German Research Center for Artificial Intelligence (DFKI) as a Senior Researcher and Team Leader for Compiler Technologies and High-Performance Computing, and with the Saarland University Computer Graphics Lab . His research spans GPU computing, domain-specific languages, and compilers. PhD from Friedrich-Alexander University Erlangen-Nürnberg (2013) Postgraduate diploma from Auckland University of Technology His research focuses on: Parallel computer architectures and programming models Automatic code generation for embedded to HPC systems Image processing, computer graphics, and deep learning applications Domain-specific languages for performance-portable code Recent publications highlight compiler design, GPU acceleration, and parallel algorithms. Scientific awards include the HiPEAC Paper Award (2018) and GPCE Best Paper Award (2015) . Professional roles include organizing High-Performance Graphics conferences as Treasurer (2024-2025) and Papers Chair (2020).
Researcher
Daniele Ottaviano is a Researcher at the Technical University of Munich (TUM) , affiliated with the Faculty of Mechanical Engineering and the Chair of Cyber-Physical Systems in Production Engineering . His work focuses on real-time virtualization , mixed-criticality systems , and embedded systems , particularly in optimizing memory hierarchies and managing heterogeneous processing elements including FPGA-based architectures . Education : Ph.D. in Fusion Science and Engineering (University of Padua & University of Naples Federico II, 2025), M.Sc. in Computer Engineering (University of Naples Federico II, 2021), B.Sc. in Computer Engineering (University of Naples Federico II, 2019). Prior Role : Visiting Researcher at Boston University's Cyber-Physical Systems Lab (2023-2024). His research investigates cache partitioning techniques , real-time virtualization for MPSoCs , and FPGA integration to enhance performance, isolation, and predictability in embedded systems. Publications highlight contributions to hypervisor optimization , container orchestration , and virtualization frameworks for mixed-criticality environments.
Professor
Michael Schluse is a Professor and Chair of the Institute for Human-Machine Interaction at RWTH Aachen University, where he also serves as Chief Engineer. His work bridges academic research and industrial application in digital systems engineering, with a physical presence at Im Süsterfeld 9 in Aachen's Former customs office building. His research centers on Experimentable Digital Twins (EDZ) – a paradigm enabling real-time interaction between physical systems and their digital counterparts. Key focus areas include: Human Digital Twin specification frameworks addressing stakeholder needs and transparency requirements Convergence of simulation and reality for lifecycle-spanning system validation Virtual testbed development for robotics, forestry, and construction applications Carbon balancing technologies in timber supply chains and environmental modeling Augmented reality systems for error-based learning (FeDiNAR project) His publication trends reveal a strategic shift from foundational simulation technologies (2000-2015) toward human-centered digital twin architectures since 2018. Recent work emphasizes practical implementation in Forestry 4.0, construction site modeling, and cybersecurity frameworks, demonstrating consistent translation of theoretical concepts into domain-specific solutions. The research shows strong interdisciplinary alignment between computer science, mechanical engineering, and environmental systems. As head of the Institute for Human-Machine Interaction, Schluse leads a research ecosystem developing runtime environments for experimentable digital twins. The institute maintains close ties with industrial partners through projects like ClusterWIS (forestry information systems) and Off-Highway-Twins, focusing on real-world validation of simulation technologies in mobile and distributed environments.
Researcher
Dr. Stephan Fahrenkrog-Petersen is a Researcher at the Institute of Computer Science , Humboldt University of Berlin , affiliated with the Faculty of Mathematics and Natural Sciences . He works on privacy-preserving process mining and business process management at the Weizenbaum Institute, Berlin. Email: stephan.fahrkrog-petersen@hu-berlin.de Address: Hardenbergstr. 32, 10623 Berlin His research focuses on data privacy , event log anonymization , and control-flow reconstruction in process mining. Recent work explores EU taxonomy compliance , human-centric BPM , and multi-perspective privacy mechanisms. Key article trends include privacy-preserving frameworks for process discovery, semantic anonymization techniques, and sustainable BPM . Publications span 2018–2025, with collaborative efforts in privacy-aware analysis and data generalization .
Professor
Wouter M. Koolen is a Professor of Mathematical Machine Learning at the University of Twente and a Senior Researcher in the Machine Learning group at Centrum Wiskunde & Informatica (CWI) in Amsterdam. Appointed to his professorship on June 1, 2022, he delivers his expertise across both institutions with offices in Enschede and Amsterdam. He is actively engaged in academic leadership through his organization of the Machine Learning Theory Research Semester Programme at CWI in Spring 2023 and serves as an ELLIS Scholar since December 2020. Dr. Koolen's research spans machine learning theory with particular focus on pure exploration in multi-armed bandit models , game tree search algorithms , and provably accelerated learning in both statistical and individual-sequence settings, which he characterizes as 'learning faster from easy data.' His work bridges theoretical foundations with practical applications, especially in safe statistical testing using e-values. He maintains active collaborations through INRIA-CWI associate teams 6PAC with Inria Lille and 4TUNE with Inria Paris and Grenoble. His recent publications reveal a strong emphasis on developing theoretically sound methods for statistical inference that maintain validity under optional stopping and continuation, representing a significant shift from traditional p-value based approaches. This work has important implications for fields requiring rigorous statistical guarantees in adaptive experimental settings. NWO VENI grant recipient QUT Vice-Chancellor's postdoctoral research fellowship awardee ELLIS Scholar (elected December 2, 2020) Member of ACM Future of Computing Academy Professor Koolen has supervised numerous PhD students to completion, including Hongwei Wen, Clément Lezane, and Tyron Lardy in 2025, and formerly Rianne de Heide who won the VVSOR Willem R. van Zwet award. He has served on program committees for major conferences including COLT, ICML, and ALT, and actively organizes workshops on cutting-edge topics in machine learning theory. His research group at CWI hosts regular reading groups and seminar series, fostering a vibrant theoretical machine learning community in the Netherlands.
Assistant Professor
Casey S Martin serves as an Assistant Professor and Leader within the Department of Family Medicine and Community Health at the University of Minnesota, Twin Cities campus. Their work focuses on advancing primary care systems through residency training innovation and evidence-based clinical practice, with current involvement in HRSA-funded rural healthcare initiatives. Research interests center on Family Medicine and Primary Health Care , particularly addressing Rural Residency Training challenges, Team-Based Care models, and sports medicine dermatology. Key areas include continuity of care optimization, diagnostic testing validation, and evidence synthesis for complex clinical scenarios like stroke management. Recent publications demonstrate evolving focus on healthcare delivery systems, with 2024 work analyzing tripartite mission integration in academic family medicine, 2023 studies examining set-day clinics and expanded medical assistant roles, and sports dermatology diagnostics. Collaborative patterns show strong emphasis on rural healthcare access and interprofessional team dynamics. Martin contributes as Co-Investigator to the active Planning and Development of a Rural Residency Training Track in Grand Rapids, Minnesota (2023-2026), funded by HRSA and Fairview Health Services. This project targets Residency Training expansion in underserved areas, with measurable impacts on physician workforce development. Research activity is amplified through social media engagement, with publications referenced by 6 news outlets, 12 X users, 1 Facebook page, and 2 Bluesky users. The work aligns with UN Sustainable Development Goals through primary health care innovation and rural medical access improvement.
Researcher
Alberto De Marchi is a Research Associate at the Institute of Applied Mathematics and Scientific Computing at Universität der Bundeswehr München (UniBw M) in Germany. He holds a doctoral degree (Dr.rer.nat.) in Applied Mathematics from UniBw M (2021), an M.Sc. in Mechatronics Engineering (2016), and a B.Sc. in Industrial Engineering (2014) from the University of Trento (UniTn) in Italy. In Fall 2022, he was a Visiting Research Associate with Ryan Loxton at Curtin University, Australia. Education Dr.rer.nat., Applied Mathematics, UniBw M (2021) M.Sc., Mechatronics Engineering, UniTn (2016) B.Sc., Industrial Engineering, UniTn (2014) His research spans computational optimization, mathematical modeling, numerical analysis, and control systems, with a focus on developing robust numerical optimization tools. Recent work includes applications in IoT digital twins, blockchain-based anonymity frameworks, and hybrid optimal control methods. His 2025–2023 publications emphasize nonlinear and mixed-integer optimization techniques, constrained composite optimization, and advanced algorithms for control systems. These works explore topics like augmented Lagrangian methods, proximal gradient approaches, collision avoidance, and blockchain ethics. Scientific Awards COAP 2022 Best Paper Prize Alberto collaborates internationally and is intellectually curious about interdisciplinary topics, including the philosophy of mind and literature.
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