Roland Christen is a Senior Research Associate at the Lucerne School of Computer Science and Information Technology, part of the Lucerne School of Applied Sciences and Arts (HSLU). He specializes in software architecture, DevOps, distributed systems, and machine learning applications across healthcare and commerce. Christen actively contributes to STEM outreach initiatives like RobertaRegioZentrum Luzern and YoungTech@hslu, emphasizing education and technology accessibility. His professional expertise spans software design, microservices, agile methodologies, and database technologies. He leads research projects in quantum cryptography, medical image analysis (e.g., psoriasis detection), AI-driven e-commerce, and predictive modeling for tourism markets. Notable outputs include peer-reviewed work on machine learning for dermatology and conference presentations on quantum privacy amplification and GPU computing. Christen holds a Roberta® Teacher Certification from the Fraunhofer IAIS and has contributed to interdisciplinary projects like Deep Neural Yodeling and Skin-App: Medical Severity Grading of Hand Eczema. He also maintains strong ties to applied fields through lab collaborations and industry partnerships, bridging academia and practical innovation.
Ralf Baumann is a Professor at the Institute of Mechanical Engineering and Energy Technology (IME) within the Lucerne School of Engineering and Architecture at Lucerne University of Applied Sciences and Arts (HSLU). He has served as Head of the Competence Center for Mechanical Systems since 2006 and as Deputy Head of IME from 2017 to 2023. His roles include being a lecturer in the Master of Science in Engineering (MSE) program since 2008 and a former Head of Department Numerical Simulation at Hilti AG. Education: Diploma in Aerospace Engineering, University of Stuttgart (1986-1992) Internship at Airbus (1988-1989) Diploma Thesis at Dornier GmbH (1992) Ralf Baumann's research focuses on Mechanical Engineering , particularly in Finite Element Method (FEM) , Structural Mechanics , Lightweight Structures , and Computational Mechanics . His work spans industrial applications such as overhead line conductors , ski manufacturing , robotics , and additive manufacturing . He has led projects like SwissSTES PIT/CCMS , Virtuelles Gehen , and vLRC – virtual Lucerne Robotics Center . His publications and presentations emphasize finite element modeling , contact stress analysis , thermal-mechanical simulations , and fluid-structure interaction in practical engineering scenarios. Scientific Awards: ANSYS Hall of Fame Competition - Best in Show 2018 Academic Zeppelin Award 'New Technologies' for Best Diploma Thesis (1993) As an educator, Baumann supervises Bachelor and Master Theses and has developed innovative 3D teaching methods via the Cyber-Classroom initiative. He has held leadership roles in the Swiss Industry Robotics Network and contributed to industry-specific projects involving ANSYS Workbench and Multilayer Stranded Cables .
Sarah Hauser serves as Vice Dean and Lecturer at the Lucerne School of Computer Science and Information Technology, part of Lucerne University of Applied Sciences and Arts. She holds an MSc in Informatik from ETH Zurich with minors in Information Security and Software Engineering, complemented by Fine Arts modules from Berlin University of the Arts. Her professional experience includes leadership roles such as Head of the Computer Science Degree Program and Head of iCompetence at FHNW School of Engineering. She has also worked as an IT Consultant and Software Developer. Education: MSc ETH in Informatik (ETH Zurich) Fine Arts Modules (Berlin University of the Arts) Executive MBA in International Management (University of Zurich) University Teaching Certificate (Lucerne University of Applied Sciences and Arts) Her research focuses on Secure Distributed Computation Systems , Social Network Analysis , and Computational Music Thinking . She actively engages in software engineering projects and curriculum development for higher education. Her competencies span management, project coordination (Scrum Master I certified), and student project coaching. Professional Development: HEM Executive Program (swissuniversities) Project Management (BWI Management Education) Assessor and Coach Training (FHNW)
Marco Zaffalon is a Professor at the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) and Scientific Director of the Dalle Molle Institute for Artificial Intelligence (IDSIA). He holds an MSc in Computer Science (cum laude) and a PhD in Applied Mathematics. His research focuses on causal AI, machine learning, and probabilistic models under uncertainty, with applications in defense, environment, medicine, engineering, and business. He leads a 30-member research group in probabilistic machine learning and has secured over 15 million Swiss Francs in competitive grants. Education: MSc in Computer Science (cum laude), PhD in Applied Mathematics. Professional milestones include roles as a software engineer at an Italian insurance group, consultant for SGS-Thomson, post-doctoral fellow at IDSIA, and tenure as a researcher since 2001. Research interests emphasize foundational and applied aspects of probability theory, particularly imprecise probability, and causal reasoning. His work integrates knowledge-based systems, probabilistic graphical models, and robust algorithms for real-world problems. Notable projects include OmniProfiler , Credal Model Averaging , and Learning under Near-Ignorance . Awards & Recognition: President of SIPTA (2019–present) Senior Area Editor for International Journal of Approximate Reasoning (IJAR) Top 2% Scientist (Stanford’s ranking since 2019) Grants & Leadership: Oversaw 15+ million CHF in competitive research funding Founded and directs a 30-member research group He collaborates on interdisciplinary projects, including environmental modeling, medical applications, and defense-related AI systems through IDSIA’s labs and partnerships.
Maciej Besta is a leading researcher at ETH Zurich's Institute for Computing Platforms, where he heads research initiatives at the Scalable Parallel Computing Lab (SPCL) and contributes to the ETH Future Computing Laboratory (EFCL). Working under the mentorship of Professor Torsten Hoefler, he has established himself as a prominent figure in high-performance computing, graph processing, and large language models. Position: Researcher at Institute for Computing Platforms, ETH Zurich Research Leadership: Head of Sparse Graph Computations and Large Language Models Research at SPCL Collaboration: Leads project management for SPCL's contributions to ETH Future Computing Laboratory Besta's research spans multiple abstraction levels, from hardware and network topologies to middleware, algorithms, and programming models. His primary focus areas include graph-enhanced language models, graph neural networks, graph databases, and sparse models, with applications across various computational settings. He approaches these problems through rigorous performance modeling and formal reasoning, emphasizing both scalability and practical implementation. His recent publications reveal a clear trend toward integrating graph structures with language models and AI systems. Besta has pioneered work on graph databases, knowledge graphs of thoughts, and higher-order graph neural networks, while maintaining his strong foundation in high-performance computing and network topology design. His research bridges traditional HPC with cutting-edge AI, creating novel approaches for efficient large-scale computation. IEEE TCSC Award for Excellence in Scalable Computing (Early Career, 2023) Multiple Best Paper Awards at Supercomputing conferences (2022, 2023) ACM SIGHPC Doctoral Dissertation Award (2022) ETH Medal for outstanding doctoral thesis (2021) Fellow of The Explorers Club (2022) Besta actively mentors ETH Zurich students through semester projects, Bachelor's, and Master's theses, focusing on graph processing and related computer science challenges. His mentorship extends beyond technical guidance, incorporating lessons from his extensive polar and mountaineering expeditions that emphasize mental resilience, efficient risk management, and leadership. He has supervised numerous student projects that have resulted in high-impact publications at top-tier conferences. As a core member of the Scalable Parallel Computing Lab, Besta collaborates with researchers across ETH Zurich and international institutions. His unique approach integrates insights from extreme environment expeditions into research methodology, creating a distinctive framework for tackling complex computational problems. The lab's work under his leadership spans theoretical modeling, practical implementation, and real-world deployment of high-performance systems.
Alexandru Calotoiu is a Researcher in the Department of Computer Science at ETH Zürich, affiliated with the Professorship for Scalable Parallel Computing. His work focuses on performance modeling, high-performance computing (HPC), serverless systems, and cloud computing. He leads research in empirical performance modeling for complex applications, optimization of parallel algorithms, and scalable cloud architectures. Key research areas include noise-resilient performance models, serverless computing frameworks, and compositional parallel programming. He has contributed to benchmarking tools like SeBS and developed techniques for loop scheduling, static analysis, and resource disaggregation in HPC environments. His publications from 2023–2025 emphasize serverless systems (e.g., FaaSKeeper, Cppless), performance embeddings for optimization, and specialized supercomputing for climate science. These studies address scalability, reproducibility, and cross-platform performance portability in data-centric workloads. No scientific awards are explicitly listed, but his work has been presented at leading conferences such as ISCA and IEEE/ACM events. He collaborates on projects like rFaaS (RDMA-enabled serverless platforms) and Process-as-a-Service frameworks. His research bridges theoretical models with practical implementations in distributed systems and cloud infrastructure.
Prof. Ralf Jung is an Assistant Professor at ETH Zürich's Department of Computer Science, leading the Programming Language Foundations Lab under the Institute for Programming Languages and Systems. His work focuses on formal verification of programming languages, particularly Rust and Iris. Previously, he earned his PhD at Saarland University and MPI-SWS, advised by Derek Dreyer, followed by a postdoc at MIT CSAIL's PDOS group. Research Interests: Formal foundations of Rust, including tools like Miri for detecting undefined behavior and MiniRust for precise specification. Iris logical framework for modular verification of programming languages at scale. Concurrent and distributed systems verification using separation logic. Advising & Labs: He leads the Programming Language Foundations Lab and is hiring postdocs. His work integrates theoretical rigor with practical tooling for real-world language verification challenges. Labs/Teams: Programming Language Foundations Lab at ETH Zürich, collaborating with the Rust language team and global research community.
Dr. Jong Hoon Kwon is a Lecturer in the Department of Computer Science at ETH Zürich. His primary research focuses on edge computing, network security, and distributed systems. He has contributed to advancements in mobile edge computing resource allocation, user allocation strategies, and end-to-end system modeling for big data applications. His work often intersects with optimization algorithms, quality of service (QoS), and stochastic systems. Dr. Kwon has collaborated extensively with researchers like John C. Grundy and Qiang He on topics ranging from NOMA-based systems to data analytics tool support. His publications highlight a strong emphasis on practical applications of theoretical models in real-world computing environments. Core Affiliations: Professur für Informatik, ETH Zürich Key Research Themes: Mobile Edge Computing, Network Security, Resource Optimization His recent work emphasizes dynamic systems and collaborative approaches to requirement modeling in big data contexts. While no formal awards are listed, his prolific publication record (over 150 entries) underscores sustained academic contributions. He has advised on numerous collaborative projects involving industry-relevant applications like 5G networks and cyber-physical systems.
Dr. Mengshuo Jia is a Senior Scientist and Principal Investigator at ETH Zürich, affiliated with the Power Systems Laboratory (PSL) within the Department of Electrical Engineering. He holds a Ph.D. from Tsinghua University (2016–2021) and a B.Eng. from North China Electric Power University (2012–2016). His roles include Guest Lecturer for 'Optimization in Energy Systems' and Associate Editor for IEEE Systems Journal and IET Renewable Power Generation. Education: Ph.D. in Electrical Engineering, Tsinghua University (2016–2021) B.Eng. in Electrical Engineering, North China Electric Power University (2012–2016) Research focuses on AI4Science , Uncertainty Modeling , Probabilistic Analysis , Stochastic Optimization , and Data-Driven Power Systems . Notable contributions include the RePower LLM-driven research platform and the DALINE toolbox for power flow linearization. His work bridges AI advancements with energy system challenges, enhancing autonomous research and grid optimization. Recent publications emphasize LLM applications in energy systems, small modular reactor integration, and hydrogen supply chain optimization. Over 10 peer-reviewed articles since 2022 highlight interdisciplinary innovation. Awards: 2023 ESI Hot Paper (top 0.1%) and Highly Cited Paper (top 1%) 2023 China First Prize of High-influence Papers 2022 Springer Thesis Award Advising and grants include leadership in Swiss National Science Foundation projects and editorial roles in top-tier journals. Collaborations emphasize data-driven methodologies and privacy-preserving distributed algorithms. Labs: Active in the Power Systems Laboratory (PSL) at ETH Zurich, advancing research in energy system optimization and AI integration.
Prof. Christoph Studer is a Full Professor of Integrated Information Processing at ETH Zurich's Department of Information Technology and Electrical Engineering. He leads the Integrated Systems Laboratory and directs SwissChips. His research focuses on wireless communication, machine learning, signal processing, and hardware-efficient algorithms, with applications in B5G systems, sensing-communication integration, and low-power signal processing. He holds a Ph.D. and M.S. from ETH Zurich (2009 and 2006) and has held academic positions at Cornell University before returning to ETH in 2020. Notable honors include the NSF CAREER Award (2017), ETH Medal for Doctoral Dissertation (2011), and multiple teaching awards. Education: M.S. and Ph.D. in Information Technology and Electrical Engineering, ETH Zurich (2006, 2009) Visiting Researcher, Stanford University (2005) Research Interests: Develops algorithms and hardware for high-throughput, low-power wireless systems. Key areas include: B5G multi-antenna systems and simultaneous sensing-communication (SISCO) Analog-to-feature (A2F) conversion for low-power signal classification Hardware-software co-design for efficient microchip integration Publications: Focus on channel charting, jammer mitigation, and deep learning for communication. Recent work includes CSI2Vec, jammer-resilient synchronization, and distributed MIMO systems. Awards: US NSF CAREER Award (2017) Michael Tien Teaching Award (2016) ETH Medal for Doctoral Thesis (2011) Labs/Teams: Leads the Integrated Systems Laboratory at ETH and directs SwissChips, a national initiative for integrated circuit development.
Natasha Sharygina is a Full Professor of Informatics at the University of Lugano (USI) in Switzerland. She leads the USI Formal Verification and Security group, focusing on improving software and hardware verification through formal methods like model checking and SAT/SMT techniques. Her research emphasizes applying these methods to computer security, electronic design, and program analysis. Education: PhD in Informatics from The University of Texas at Austin (2002). Research Interests: Her work spans formal verification, model checking, SMT-based solvers, and security analysis. She develops theoretical frameworks and practical tools for verifying large-scale systems, with applications in safety-critical and distributed computing environments. Funding & Awards: Her research has been supported by grants from the Swiss National Science Foundation, EU STReP/COST projects, Hasler Foundation, and TASSO Career Award. She has been recognized with the ACM Recognition of Service Award and CMU Technical Excellence Awards. Grants & Projects: Key initiatives include 'Beyond Symbolic Model Checking through Deep Modelling' (2019–2023), EU-funded 'Rich-Model Toolkit', and Swiss TASSO Career Award (2005–2010). She has led efforts in parallel SMT solving and runtime verification. Labs & Teams: Director of the USI Formal Verification and Security Lab, which develops tools like Golem (CHC solver) and OpenSMT (SMT solver). Collaborates globally on projects like SAFARI and FunFrog for program verification.
Paolo Rossetti is a Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), where he teaches in the Master of Informatics and Economics program. He is also actively engaged as a management consultant and committee member for Mobsya Association, promoting educational robotics. His professional background includes leadership roles at Sun Microsystems and collaborations with Politecnico di Milano, University of Trento, and University of Padova. His research and professional interests focus on improving organizational performance through human-centered interventions. Key areas include: Process and performance improvement eLearning, mobile learning, and blended learning Lean Six Sigma and visual thinking Social network analysis and knowledge sharing Idea and change management Business Process Management (BPM) and model-driven software development Internet of Things (IoT) and digital transformation for SMEs While no formal academic publications are listed in the provided text, his recent work involves applied research contracts focused on extending software modeling to IoT scenarios, facilitating BPM adoption, and applying idea management in digital transformation projects—indicating a strong trend toward practical, industry-aligned innovation in information systems and organizational development. He has contributed to the design of globally used tools for talent management, competency modeling, and performance evaluation during his tenure at Sun Microsystems. These tools were deployed worldwide by learning specialists and consultants. His advisory and consulting roles include: Management Consultant and Committee Member, Mobsya Association (2016–present) Learning and Content Strategy for WebRatio and IoT business development (2013–2016) Content development contracts with Politecnico di Milano and University of Trento Idea management consultancy for Nosco in Italy and Switzerland He previously founded flipfly srl, an eLearning startup, and held progressive leadership roles at Sun Microsystems from 1995 to 2008, including WW Talent Management Program Manager and various regional education leadership positions. He has also served as a university professor at Politecnico di Milano (IT Service Management, 2005–2006) and University of Padova (Distributed Software Development, 1997–2001).
Matthias Kurt Muntwiler is a Researcher at the Paul Scherrer Institute (PSI) in the Photon Science Division's Laboratory for X-ray Nanoscience and Technologies (LXN). He manages the PEARL beamline at the Swiss Light Source and is a member of the Swiss Nanoscience Institute, supporting user experiments across Europe. He earned his diploma (2000) and PhD (2004) in experimental physics from the University of Zurich, Switzerland, followed by postdoctoral work at the University of Minnesota under Prof. Xiaoyang Zhu focusing on ultrafast polaron dynamics. Muntwiler specializes in surface and interface science of ultrathin films, organic semiconductors, and two-dimensional materials. His expertise spans photoelectron spectroscopy for chemical analysis, band mapping, atomic structure determination, and dynamic processes, emphasizing structure-property relationships. He also develops software for experiment control and machine learning-based structural modeling. His publication record (2008-2020) reveals consistent focus on advanced synchrotron-based characterization of nanomaterials, particularly using photoelectron diffraction to resolve atomic-scale interfaces in systems like h-BN nanomeshes, metal-organic networks, and ferroelectric materials. As designer and manager of the PEARL beamline, Muntwiler integrates soft X-ray spectroscopy with scanning tunneling microscopy to enable atomic-resolution studies of novel materials and molecular adsorbates.
Prof. Dr. Marco Giesselmann is a faculty member at the University of Zurich in the Sociological Institute under the Faculty of Philosophy . He teaches courses such as Statistics I , Statistics III , and Thesis Workshop 2025 , while also leading the SP 2 Human Reproduction in Societies and Markets research group and serving on the Executive Committee. Research Interests : Giesselmann focuses on Social Statistics , Migration Studies , Labor Market Sociology , and Quantitative Methods . His work bridges empirical analysis with policy-oriented sociology, particularly on refugee integration, income inequality, and longitudinal data applications. Publications : His recent research examines refugee impacts on social cohesion (2024), cross-level interactions in multilevel models (2019), maternal mental health (2018), and income measurement challenges (2017). Email : giesselmann@soziologie.uzh.ch
Glück Florent is an Associate Professor at the Geneva School of Landscape, Engineering and Architecture (HES-SO), affiliated with the Technical and IT school's Computer Science and Communication Systems department. He specializes in embedded systems, system virtualization, and interdisciplinary projects at the intersection of engineering and healthcare. Affiliations: HES-SO Geneve, hepia inIT, and collaborations with medical and industrial partners. Education: Not explicitly listed, but implied through roles and projects involving systems engineering and computer science. Research Interests: His work spans embedded systems design, real-time data processing, and applied machine learning. Key focuses include secure hardware-software co-design (e.g., FPGA-based security), medical device development (e.g., neonatal monitoring systems), and IoT infrastructure for smart buildings and recycling. Project Trends: Florent leads projects combining engineering with societal impact, such as automated recycling systems (LusTra), secure medical diagnostics (BrainCheckX), and educational virtualization platforms (Nexus VDI). Recent work emphasizes AI-driven solutions for healthcare (e.g., cochlear implant support) and decentralized energy management. Grants and Funding: Multiple projects funded by HES-SO Rectorat, CTI, and industry partners, totaling over CHF 400,000 since 2014. Labs/Teams: Active in distributed embedded systems research, leading teams on projects like DPESI (distributed storage) and HERVA (random number validation platforms).
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