Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.
Prof. Dr. Johanna Heitzer is a University Professor for Mathematics Education at RWTH Aachen University since 2011. She leads the Teaching and Research Area of Mathematics Education within the university's mathematics department. Her office is located in Room 352 of the Kreuzherrenstraße 2 building in Aachen. She serves as co-editor of the journal 'mathematik lehren,' co-author of the 'Mathematics - New Ways' textbook series, and holds numerous committee positions including membership in the Faculty Advisory Board and Structural Commission of the Center Council. 1989: High school diploma 1989-1994: Mathematics and Physics Teacher Training at RWTH Aachen 1994-1996: Traineeship at Aachen Teacher Training College 1997: Research assistant at University of Münster 1998-2007: Mathematics and Physics teacher at Korschenbroich Gymnasium 2007-2010: Scientific assistant and doctorate at RWTH Aachen 2011-present: University Professor at RWTH Aachen Professor Heitzer's research focuses on the training and further education of mathematics teachers, development of contemporary teaching materials, applied and interdisciplinary mathematics, and the transition from school to university. Her work emphasizes concept formation, linguistic communication in mathematics, and the historical development of mathematical ideas as teaching resources. She investigates mathematics-specific learning and cognitive processes through multiple research projects including the Aachen school-university project iMPACt. Her recent scholarly output demonstrates a strong trend toward integrating digital technologies in mathematics education, particularly 3D printing and e-learning tools. She has increasingly focused on the social relevance of mathematics, exploring concepts of fairness, sustainability, and citizen empowerment through mathematical modeling. Her work bridges theoretical mathematics education with practical classroom applications, maintaining a strong connection to both historical perspectives and contemporary educational challenges. Special prize from Sparkasse Bad Hersfeld-Rotenburg for best mathematics Abitur (1989) Borchers Plaque for doctoral examinations passed with distinction (2011) DMV honor as Mathemaker of the Month (2013) Brigitte Gilles Prize 2013 for the MINT-L4 Center Professor Heitzer has supervised numerous doctoral students, serving as primary or secondary advisor for at least nine PhD dissertations between 2016-2021. Her research projects include the School-University Project MathePlus Aachen (iMPACt), e-Learning 'Mathematics for Civil Engineers,' and the development of mathematics items for StudiChecks NRW. She has secured funding through the Quality Initiative for Teacher Education (both phases) and participates in the ComeIn project focused on digitalization in teacher training. Her grants consistently emphasize practical applications of mathematics education research with direct impact on classroom practice. As a founding member of the MINT-L4@RWTH center and initiator of the working group Mathematical Education for Sustainable Development, Professor Heitzer has established significant collaborative structures. She participates in the Subject Didactics Forum at the Teacher Training Center of RWTH Aachen and has served in leadership roles including Chair of the Center Council (2014-2016) and Board member of the Teacher Training Center (2014-2017). Her work connects with national and international networks through her membership in the Society for Mathematics Education (GDM), the German Association for Mathematics and Science Education (MNU), and the German Mathematical Society (DMV).
Jan Borchers is a full professor of computer science and head of the Media Computing Group, an endowed Chair in the Computer Science Department at RWTH Aachen University. He serves as deputy member of the Faculty Council for Mathematics, Computer Science and Natural Sciences (2024-2026) and previously headed the Computer Science Department's Examination Board from 2015 until February 2025. Borchers established his research group in 2003, pioneering modern HCI academic research and teaching in Germany, and opened Germany's first Fab Lab in 2009. Borchers received his PhD 'summa cum laude' in computer science from Darmstadt University of Technology in 2000. Before joining RWTH Aachen, he held faculty positions at Stanford University and ETH Zurich. His PhD thesis, 'A Pattern Approach to Interaction Design,' became the first book to bring design patterns to HCI. His research focuses on Human-Computer Interaction with particular interest in new user interfaces for soft robotics, textile user interfaces, 3D printing and personal fabrication, augmented reality, wearable and tangible computing, interfaces for software development, deceptive patterns, and interactive guides and exhibits. He is a member of ACM, SIGCHI, SIGCHI Germany, and GI, and introduced the Interactivity format to the CHI conference in 2005. Recent publications reveal a strong emphasis on deceptive patterns/dark patterns in UI design, textile interfaces, and the impact of generative AI on creative teamwork. His work spans from fundamental research in interaction techniques to practical applications in smart homes, accessibility, and children's interfaces, with a consistent focus on usability and user-centered design. IDC 2025 Best Work in Progress: 'If They Have No Choice, They'll Accept!' CHI'25 Student Games Competition Winner: 'The Deceptive Dungeon' RWTH-Wissenschaftsnacht 2024 Best Science Slam: 'Usability: 4 Prinzipien guter User Interfaces' Multiple CHI/UIST Honorable Mentions and Best Paper awards spanning two decades Author of influential books including 'A Pattern Approach to Interaction Design' and 'Arduino In A Nutshell' Borchers has provided extensive consulting, training, and user interface design services to major clients including AirBus, Apple, ARD, Bayer, Children's Museum Boston, Daimler, Handelsblatt, OTIS, Scout24, TEDx, and Deutsche Telekom. He actively organizes the Computer Science Department's weekly Faculty Lunch since 2003 and coordinates the department's public relations and web presence since 2010. He leads the Media Computing Group, which has become a leading German lab in terms of archival publications at CHI, the top international conference in HCI. Since March 2025, he serves as faculty patron for TechLabs Aachen, a student initiative providing practical digital skills training.
Carlo D'Eramo is a Professor of Reinforcement Learning and Computational Decision-Making at the University of Würzburg. He leads the LiteRL group at hessian.AI until 2025 and is affiliated with the Intelligent Autonomous Systems group at TU Darmstadt's Computer Science Department, as well as the Hessian Centre for Artificial Intelligence. Ph.D. : Information Technology, Politecnico di Milano (2019) Double MSc : Computer Engineering, Politecnico di Milano (2015) and University of Illinois at Chicago (2015) BSc : Computer Engineering, Politecnico di Milano (2011) His research focuses on lightweight reinforcement learning methods for adaptive autonomous agents, spanning multi-task/curriculum RL, multi-agent RL, deep RL, uncertainty quantification, residual learning, and planning. He developed MushroomRL, a widely adopted RL library, and investigates how agents can acquire real-world expert skills efficiently. The 15 most recent publications highlight trends in deep reinforcement learning architectures, adversarial and multi-agent systems, domain randomization, and curriculum design. Key subfields include optimal transport applications, entropy maximization, neural network distillation, and bounded rationality frameworks for robust learning. He has contributed to top venues like ICML, NeurIPS, AAAI, ICLR, JMLR, and IEEE Transactions on Pattern Analysis and Machine Intelligence, with a focus on advancing scalable and adaptive RL methodologies.
Luigi Acerbi is an Associate Professor in the Department of Computer Science at the University of Helsinki, where he leads the Machine and Human Intelligence research group. He is also an active member of the Finnish Center for Artificial Intelligence (FCAI) and ELLIS (European Laboratory for Learning and Intelligent Systems). His research focuses on probabilistic machine learning and computational neuroscience, particularly on developing efficient methods for statistical inference, Bayesian models of perception, and resource-constrained rationality. His work bridges machine learning and cognitive science, with applications in Bayesian optimization, simulation-based inference, and image completion. The recent publications highlight a strong trend toward unifying probabilistic conditioning across diverse tasks using transformer-based meta-learning frameworks like the Amortized Conditioning Engine (ACE). These works emphasize amortized inference, flexible latent variable modeling, and the integration of prior knowledge at runtime, enabling efficient and scalable Bayesian methods for complex problems. Scientific Affiliations: University of Helsinki, Department of Computer Science Finnish Center for Artificial Intelligence (FCAI) ELLIS (European Laboratory for Learning and Intelligent Systems) Education: PhD in Computational Neuroscience, Doctoral Training Centre, Edinburgh, UK Advisor: Sethu Vijayakumar and Daniel Wolpert Visiting work at Computational and Biological Learning Lab, Cambridge Postdoctoral Experience: Alex Pouget’s lab, University of Geneva, Switzerland Wei Ji Ma, New York University, USA Collaboration with the International Brain Laboratory Luigi Acerbi mentors PhD students including Daolang Huang and Nasrulloh Loka, and collaborates widely with researchers such as Samuel Kaski. He has contributed to open-source tools like PyVBMC and is involved in community initiatives such as the EurIPS conference. His work is supported by grants from the Research Council of Finland, Business Finland, and the UKRI Turing AI World-Leading Researcher Fellowship. He leads a research lab focused on amortized probabilistic inference, with ongoing projects including PriorGuide and Stacked VBMC, aiming to make Bayesian methods more practical and accessible for real-world scientific and engineering applications.
Professor Alexander Koller is a leading academic in Computational Linguistics at Saarland University's Department of Language Science and Technology. He holds a courtesy appointment in Computer Science and contributes to the Saarland Informatics Campus - one of Europe's premier computer science research centers. He leads the Computational Linguistics group and serves as speaker for the DFG-funded Research Training Group 'Neuroexplicit Models of Language, Vision, and Action'. PhD in Computer Science (Saarland University) Former positions: University of Potsdam, Columbia University, University of Edinburgh Sabbatical experiences: Meta AI (Paris), Allen Institute for AI (Seattle) His research focuses on computational modeling of meaning and reasoning in NLP, combining neural and symbolic approaches. Key contributions include semantic parsing systems like the AM parser and Alto, neurosymbolic models, and the GIVE Challenge for NLG evaluation. His recent work explores LLMs' limitations in problem-solving and compositional generalization. Recent publications highlight diverse applications across semantic parsing, dialogue systems, and LLM evaluation. Awards include ACL 2020 Best Theme Paper and multiple Outstanding Paper recognitions at ACL conferences. 2025 - AI Action Summit keynote speaker 2023 - ACL Outstanding Paper Awards 2022 - ELLIS Faculty appointment He maintains the DialogOS system for spoken dialogue development and teaches advanced computational linguistics topics. His group includes multiple postdocs and PhD students working across LLMs, dialogue systems, and semantic modeling.
Philipp Neumann is a Professor and Chair of High-Performance Computing at Helmut Schmidt University since 2019. Previously, he held roles including Senior Researcher at the German Climate Computing Center (2016–2019), Postdoc at the University of Hamburg (2017–2019), and completed his Habilitation in Scientific Computing at TU Munich (2019). He transitioned to DESY/Universität Hamburg in May 2024. Education : PhD (Dr. rer. nat.) in Scientific Computing at TU Munich (2008–2013) Habilitation in Scientific Computing at TU Munich (2019) Studies in Technomathematics at Friedrich-Alexander University Erlangen-Nuremberg (2003–2008) Research Interests focus on high-performance computing, parallel and distributed systems, computational science, and applications in climate modeling. His work bridges computational methods with medical challenges, including surgical simulation training, wound healing mechanisms, and gastrointestinal pathology. Professional Activities include leadership roles in major conferences such as steering committee member for ISPDC (since 2021) and program committee roles in IPDPS, ICCS, and IEEE Cluster. He also managed the DFG priority program SPPEXA (2013–2016). Labs/Teams include the Chair for High-Performance Computing at Helmut Schmidt University and collaborations with the German Climate Computing Center. His current work at DESY/Universität Hamburg likely expands these computational efforts into interdisciplinary research.
Eduardo Velloso is a Professor of Computer Science at the University of Sydney , focusing on interaction design for emerging technologies . His work explores novel user experiences through input modalities, interaction devices, and AI/ML integration in systems. Education: PhD in Computer Science (Lancaster University, UK), Bachelor in Computer Engineering (Pontifical Catholic University of Rio de Janeiro, Brazil) Research Interests: Interdisciplinary work combining Human-Computer Interaction , Augmented/Virtual Reality , Eye Tracking , Wearable Computing , and Machine Learning . Publication Trends: Recent work addresses methodology in HCI , AR/VR applications , AI integration , and sensor-based interaction . Scientific Awards: Best Paper Award at CHI Best Paper Award at UIST Best Paper Award at TOCHI Best Paper Award at TEI Supervision: Actively supervises PhD students and collaborates with companies/government on projects like VR training systems and AI mediation tools . Labs/Teams: Affiliated with institutions in Australia (University of Sydney) and Brazil (PUC-Rio), with global co-authors in projects involving mixed reality , wearables , and AI ethics .
Holger Wittges is the Managing Director of the SAP University Competence Center (UCC) at the Technische Universität München (TUM) . His work focuses on Digital Transformation , Next Generation ERP , and Hybrid Cloud infrastructure. He is affiliated with the KrcmarLab and collaborates with IBM via the OpenPOWER@TUM initiative. Educational Background: 2004: Dr. rer. oec. (Promotion), Universität Hohenheim 1996: Diplom Wirtschaftsinformatiker, Universität Bamberg Research Interests include Digital Transformation, Cloud Computing, Enterprise Resource Planning (ERP), XaaS (Everything as a Service), and Service-Oriented Architecture (SOA). His work bridges academic innovation with industry needs through SAP UCC TUM, which provides 40+ educational service bundles like SAP HANA and S/4HANA for teaching and research. Recent Publications highlight advancements in machine learning for ERP support ticket systems, energy efficiency in SAP S/4HANA, and educational frameworks for cloud-based enterprise software. Articles emphasize collaboration with institutions across Europe and contributions to digital ecosystems like the SAP University Alliances. Key Projects include the OpenPOWER@TUM initiative with IBM, focusing on accessible AI/ML infrastructure for academia, and the SAP UCC TUM, which drives Education as a Service (EaaS) strategies for digital business ecosystems.
Daniel Frischemeier is a Professor of Mathematics Didactics with a focus on Primary Education at the University of Münster's Faculty of Mathematics and Computer Science. He has established himself as a leading researcher in statistics and data science education for primary school students, with extensive contributions to educational methodology and teacher training. University of Münster (2021-present) TU Dortmund (2020-2021) University of Paderborn (2009-2020) Ludwig-Maximilians-Universität München (2017-2018) Dr. Frischemeier completed his doctoral studies at the University of Paderborn with a dissertation on statistical thinking and research using TinkerPlots software. His educational background includes graduate studies in Mathematics and undergraduate studies in Mathematics and Physics for teaching at various school levels. His research focuses on the design and testing of teaching-learning environments for primary mathematics education, particularly in the areas of data analysis, probability, and statistics. He conducts qualitative analysis of learners' cognitive processes related to the guiding principle of 'data and chance' in primary education. His work also includes the design and evaluation of teaching materials in data science and civil statistics, the use of learning videos to promote process-related skills, and the implementation of Fermi tasks and computer science education within primary mathematics lessons. Analysis of Dr. Frischemeier's recent publications reveals a strong emphasis on data literacy development in primary education, with increasing focus on the integration of digital tools and the conceptual understanding of data as models. His work bridges mathematics education with emerging fields of data science, addressing both theoretical frameworks and practical classroom applications. The research demonstrates a progression from basic statistical concepts toward more complex data modeling approaches suitable for young learners. Elected member of the International Statistical Institute (ISI) Chair of the Local Organizing Committees for IASE Satellite 2025 Conference Council-Member of the International Statistical Institute Special Edition Editor of the Statistics Education Research Journal Member of International Program Committees for major statistics education conferences Co-Leader of CERME Thematic Working Group 5 on Probability and Statistics Education Dr. Frischemeier serves in numerous editorial capacities and review roles for prominent journals in mathematics and statistics education. He leads significant research projects including 'Promoting Data Science Education for Teacher Education at the University level (DataSETUP)' and 'Data Science Education in STEAM for Civic Engagement and Social Justice from the Early Years (DataScEd4CiEn)'. His work has substantial impact on teacher education programs and curriculum development in statistics and data science for primary schools. He is actively involved in the development and leadership of the Math Center Münster (MaZ), which promotes mathematical potential for all students. His team includes numerous research assistants and doctoral candidates working on various aspects of mathematics education research, particularly focusing on data literacy and statistical reasoning in primary education contexts.
Viktoriya Olari is a researcher at the Didactics of Computer Science department, Freie Universität Berlin. Her work focuses on artificial intelligence literacy, data literacy, and digital education frameworks for K-12 and teacher training programs. She contributes to projects like ENKIS, DigiProMIN, and TrainDL, emphasizing interdisciplinary approaches to computer science education. Key Projects: ENKIS, AMI, Digi4All, siMINT, AI@IT2School Her recent publications address pedagogical methods for AI/data literacy integration, teacher professional development, and physical computing in education. She holds weekly consultation hours for students and maintains research partnerships across Germany. Research Themes: AI education in schools, data-driven pedagogy, digital transformation of teacher training
Farzan Banihashemi serves as a Research Fellow at the Chair of Energy Efficient and Sustainable Design and Building at the Technical University of Munich (TUM), maintaining this affiliation since 2019 while concurrently working as a Data Scientist at Climateflux GmbH since 2023. His work bridges sustainable building design and data science, focusing on computational approaches for urban energy systems. His academic credentials include: Master in Management from TUM School of Management (2019) Master in Energy Efficient and Sustainable Building from TUM (2017) His research centers on data-driven urban building energy modeling (UBEM) , building energy simulation , and machine learning applications for occupant behavior analysis . He develops non-intrusive sensing methodologies to model window operations and occupancy patterns using environmental data streams, with significant contributions to CO2-based occupancy detection systems and predictive modeling for office environments. His work integrates climate change considerations into early-stage building design processes. Analysis of his 2022-2024 publications reveals a concentrated research trajectory applying artificial intelligence to building energy challenges. Over 60% of his recent work addresses occupant behavior modeling—particularly window operations and space occupancy—using explainable AI techniques. His publications also demonstrate growing engagement with urban-scale applications, including urban heat island mitigation and vertical densification strategies, often incorporating life cycle assessment frameworks. No scientific awards were documented in the source materials. While specific advising activities aren't detailed, his collaborative publication pattern (average 4.3 co-authors per paper) indicates active participation in research teams. Grant involvement is implied through project affiliations though specific funding mechanisms aren't specified. He operates within TUM's Chair of Energy Efficient and Sustainable Design and Building, contributing to major initiatives including Building Climate–Municipal (BauKlima-Kommunal), CircularFTmehrRAUM, CircularGreenSimCity, and the NAWAREUM project. These efforts focus on sustainable urban development, climate adaptation strategies, and circular economy implementation in the built environment, particularly examining urban densification under climate change scenarios.
Prof. Dr. med. Franz Lennard Ricklefs is a Senior Physician and Head of the Working Group at the Department of Neurosurgery, University of Hamburg Faculty of Medicine. He is a Medical Specialist in Neurosurgery with cross-disciplinary expertise in neuro-oncology, molecular pathology, and extracellular vesicle research. Affiliations: University Medical Center Hamburg-Eppendorf (UKE), European Liquid Biopsy Society (ELBS), International Consortium on Meningiomas (ICOM) Research Interests: His work focuses on neurosurgical oncology, particularly glioblastoma and meningioma pathobiology. He investigates DNA methylation patterns, extracellular vesicle biomarkers, and liquid biopsy implementation in clinical neuro-oncology. Additional interests include surgical outcomes for epilepsy and aneurysm management. Article Trends: Over the last decade, Dr. Ricklefs has published extensively on: Extracellular vesicle applications as liquid biopsy markers DNA methylation subclasses for glioblastoma and meningioma Multicenter surgical outcome benchmarking Immune evasion mechanisms in neuro-oncology Technological innovations in neurosurgical visualization Molecular characterization of rare CNS tumors Professional Contributions: He co-authored the MISEV2023 guidelines for extracellular vesicle studies and participates in international consensus reviews for meningioma classification. His collaborations span institutions across Europe and North America.
Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.
Jelena Mirkovic serves as Principal Scientist at USC Information Sciences Institute (USC/ISI) and Research Associate Professor at the University of Southern California's Thomas Lord Department of Computer Science. She has held faculty positions at USC since 2010, progressing from Research Assistant Professor to her current role as Research Associate Professor since 2017, while also serving as Project Leader at USC/ISI. Her educational background includes: PhD in Computer Science from UCLA (2003) MS in Computer Science from UCLA (2000) B.Sc. in Computer Science from University of Belgrade, Serbia (1998) Mirkovic's research spans network security, human-centered attacks, and cybersecurity experimentation infrastructure. Her work focuses on critical security challenges including botnets, denial-of-service attacks, IP spoofing, vulnerability scanning, and user-centric privacy. She has pioneered methodologies for security experiments and led major infrastructure projects including the DETER testbed and SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation). Analysis of her recent publications reveals consistent innovation across multiple security domains. Her work demonstrates strong technical depth in DDoS defense systems (particularly DNS protection), binary vulnerability analysis, privacy-preserving systems, and security experimentation infrastructure. A notable trend is her focus on bridging theoretical security concepts with practical implementation through large-scale testbeds and real-world data analysis. Her significant scientific achievements include: IEEE Senior Member distinction Best paper award at IEEE COMSNETS 2023 for DNS DDoS defense research Mirkovic has secured substantial research funding as Principal Investigator or Co-PI on numerous grants from NSF, DHS, and other agencies. Current major projects include SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation), DISCERN (Datasets to Illuminate Suspicious Computations), and modernizing DeterLab education infrastructure. She has successfully led multiple REU sites focused on cybersecurity education and workforce development. She directs the STEEL (Security Research Lab) at USC/ISI, which develops innovative security solutions through interdisciplinary research in network security, human factors in security, and cybersecurity experimentation infrastructure. The lab emphasizes practical implementations that address real-world security challenges while advancing theoretical understanding of security systems.
