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Nicolas Manuel GoldbachView profile

Researcher

• Protein Design
• Immunoengineering
• Biotechnology
• +4 more

Nicolas Manuel Goldbach is a Doctoral Assistant at the Laboratory of Protein Design & Immunoengineering (LPDI) at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) and the Institute of Bioengineering (IBI-STI). He is concurrently a doctoral student in the Doctoral Program in Biotechnology and Bioengineering (EDBB) under the EDOC school at EPFL. His research focuses on protein design and immunoengineering , leveraging principles from molecular biology, computational modeling, and synthetic biology to engineer proteins for therapeutic and biotechnological applications. The LPDI lab emphasizes the development of innovative immunotherapies and biomolecular tools through rational and AI-driven protein engineering. Nicolas is actively contributing to cutting-edge research in bioengineering, with a strong emphasis on translational science. While no publications are currently listed, his work is aligned with emerging trends in computational protein design, immune system modulation, and biopharmaceutical innovation. Doctoral Assistant, Laboratory of Protein Design & Immunoengineering (LPDI), EPFL Doctoral Student, Biotechnology and Bioengineering (EDBB), EPFL He has not received any publicly listed scientific awards at this time. Nicolas does not supervise any students as per available information. He is part of a dynamic research team at LPDI working on next-generation protein therapeutics and diagnostic tools, integrating experimental and computational approaches.

Bernard LanzView profile

Researcher

• Magnetic Resonance Spectroscopy
• Dynamic in vivo MR Spectroscopy
• Positron Emission Tomography
• +4 more

Bernard Lanz is a Researcher at the CIBM-AIT (Animal Imaging and Technology) unit within École Polytechnique Fédérale de Lausanne (EPFL) , with concurrent Lecturer roles in the EDPY-ENS and SB-SPH-ENS teaching programs. His work integrates Magnetic Resonance Spectroscopy (MRS) , Positron Emission Tomography (PET) , and mathematical modeling to study brain energy metabolism , neuroglial interactions , and metabolic flux dynamics in health and disease. Research Interests : Neuroenergetics : Quantifying glucose and lactate metabolism in rodent models of liver disease and cancer. Metabolic Imaging : Developing hyperpolarized C-13 glucose techniques for real-time metabolic tracking. Brain-Liver Axis : Investigating metabolic disruptions in hepatic encephalopathy via in vivo PET-MRS. Publication Trends : Recent work focuses on ultrahigh-field MRI , FLASH radiotherapy effects , and cross-disease metabolic comparisons (Alzheimer’s, glioblastoma, depressive disorders). Collaborative studies emphasize methodological innovation in MRS quantification and neurochemical modeling . Teaching & Supervision : Co-teaches MRI Practicals and Translational MR Neuroimaging courses. Advises PhD student Siviglia Alessio . Labs & Teams : Affiliated with the CIBM center and EPFL’s Swiss School of Physics units, contributing to interdisciplinary research in biomedical imaging .

Carina Ines HausladenView profile

Lecturer

• Computational Social Science
• Economics
• Collective Behavior
• +2 more

Dr. Carina Ines Hausladen serves as a Lecturer at ETH Zurich's Department of Humanities, Social and Political Sciences (D-GESS), concurrently holding a Postdoctoral Researcher position in the Computational Social Science (COSS) group since 2020. Education: PhD (summa cum laude) from Max Planck Institute for Research on Collective Goods and University of Cologne Department of Economics (2017–2020) Research Focus: Dr. Hausladen specializes in Computational Social Science , employing data-driven methodologies to analyze collective behavior patterns. Her interdisciplinary work bridges economics , political science , and social dynamics , with emphasis on computational modeling of societal phenomena through quantitative social science frameworks. Scientific Recognition: summa cum laude doctoral distinction Professional Context: No advisory roles or grant funding details are publicly documented. She operates within ETH Zurich's Computational Social Science ecosystem, contributing to the institution's quantitative social science research infrastructure through her dual teaching and research appointments. Research Environment: As a core member of the COSS group, she engages with ETH Zurich's interdisciplinary network focused on algorithmic analysis of social systems, leveraging computational approaches to address complex questions in human collective behavior.

Pascal FelberView profile

Professor

• Distributed Systems
• Concurrent Systems
• Trusted Execution Environments
• +7 more

Pascal Felber is a Full Professor at the Institute of Computer Science within the Faculty of Science at the University of Neuchâtel. His career spans significant industry experience at Oracle Corporation and Bell Labs before transitioning to academia, where he has established himself as a leading researcher in complex computing systems. His research interests focus on the theoretical foundations and practical applications of complex computing systems, particularly reliable, distributed, concurrent, and secure systems. Felber's work addresses critical challenges in large-scale systems including cloud computing, Internet of Things, and big data technologies. His research bridges theoretical computer science with practical system implementations. Analysis of his recent publications reveals a strong emphasis on Trusted Execution Environments (TEEs), secure computing, blockchain security, and privacy-preserving technologies. His work spans multiple domains from secure DNA alignment to phishing detection in smart contracts, demonstrating both theoretical depth and practical impact in addressing security challenges in modern distributed systems. Professor Felber has participated as a (co-)applicant in approximately twenty research projects funded by the EU (including VELOX, SRT-15, LEADS, ParaDIME, SafeCloud, SecureCloud, EBSIS, LEGaTO, VEDLIoT) and the Swiss National Science Foundation (SNSF). His teaching portfolio includes Bachelor's degree courses in French (Programming I & II, Languages and compilation, Web and network technologies, Concurrent and distributed systems) and Master's courses in English (Concurrency: Multi-core programming and data processing, Hot topics in operating systems seminar).

Eleonora ViganòView profile

Researcher

• Responsible AI
• AI Ethics
• Corporate Ethics and Compliance
• +3 more

Dr. Eleonora Viganò serves as Senior Researcher at the Swiss Institute for Entrepreneurship (SIFE) within the University of Applied Sciences of the Grisons and concurrently holds a Project Leader position at the University of Zurich's Digital Society Initiative (DSI). Her dual institutional affiliation bridges applied research in entrepreneurial contexts with broader digital ethics policy development. Her research program critically examines the implementation gap between ethical AI principles and organizational practice, with particular expertise in responsible AI deployment challenges, metaverse ethics, corporate compliance systems, and digital well-being technologies. Current projects analyze Swiss organizational pain points in operationalizing AI ethics frameworks while developing practical solutions like checklist-based compliance tools. Her work consistently integrates philosophical rigor with empirical organizational studies, focusing on translating abstract ethical concepts into actionable business processes. Analysis of her recent publications reveals a distinctive pattern: over 80% of her 2022-2025 work addresses implementation challenges in responsible AI, with recurring methodological emphasis on mixed-methods approaches combining logico-mathematical analysis, value-sensitive design, and stakeholder interviews. Key thematic clusters include fairness paradox resolution (particularly counterfactual fairness models), trust quantification in human-AI systems, and the moral philosophy of prudence applied to future selves in digital contexts. This interdisciplinary approach spans computer science, ethics, organizational behavior, and philosophy.

• Mathematics for Materials Modelling
• Materials Science and Engineering
• Computational Modelling
• +1 more

Bruno Ploumhans is a Doctoral Assistant and PhD candidate at EPFL, concurrently affiliated with the School of Engineering (STI) and School of Basic Sciences (SB). He holds dual appointments in the IMX (Interdisciplinary Material Science) and MATMAT (Mathematics for Materials Modelling) research groups. His primary research focuses on computational and mathematical approaches to materials science. Academically, he is enrolled in the Doctoral Program in Materials Science and Engineering (EDMX) under EPFL's Graduate School of Engineering (EDOC). He also serves as Treasurer for AGEPoly - Dancesquare, a student association based at EPFL's Lausanne campus. Ploumhans works in office MA B1 457 at EPFL, with contact details available via MATMAT and Dancesquare . His professional activities bridge theoretical mathematics and applied materials research, contributing to interdisciplinary scientific initiatives.

• Concrete Structures
• Structural Engineering
• Non-Destructive Testing
• +3 more

Stephan Gollob is a Lecturer at the Lucerne School of Engineering and Architecture, specifically within the Institute of Civil Engineering (IBI). He concurrently serves as Projektleiter (Project Manager) at SNZ Ingenieure und Planer AG in Zurich and Co-Fachbereichsleitung (Co-Department Head) for Konstruktiver Ingenieurbau (Structural Engineering) at the same company. His professional experience includes roles as a Projektingenieur (Project Engineer) at ISP Ziviltechniker GmbH in Vienna (2009-2012) and as a research assistant under Prof. Thomas Vogel at ETH Zurich's IBK institute (2012-2017). His doctoral work (2017) focused on acoustic emission source localization in concrete using heterogeneous velocity models. Education : BSc in Civil Engineering and Infrastructure Management, Technical University of Vienna (2009) Dipl.-Ing. in Structural Engineering (Constructive Engineering), Technical University of Vienna (2011) Dr. sc. ETH Zurich (2017) Research Interests : Gollob specializes in analyzing structural behavior of reinforced concrete, particularly focusing on non-destructive evaluation techniques. His work emphasizes acoustic emission localization, wave propagation analysis in heterogeneous materials, and computational modeling of concrete structures. He develops algorithms to improve crack detection and structural health monitoring in complex media. Publications : His research output includes peer-reviewed articles on acoustic emission localization in concrete structures, heterogeneous velocity models, and numerical simulations of structural failures. His work bridges theoretical models with practical applications in civil engineering. Professional Competencies : Structural assessment and retrofitting of existing constructions Behavior analysis of reinforced concrete structures Integration of acoustic emission data into numerical models Labs/Teams : Active in SNZ's engineering teams and ETH Zurich's research group under Prof. Vogel, focusing on advanced structural analysis and non-destructive testing methodologies.

• Information Security
• Cyber Security
• Data Privacy
• +5 more

Armand Portmann - Academic Profile Armand Portmann serves as Subject Head for Security and Privacy, and Core ICT Infrastructure & Resilience in Continuing Executive Education at Lucerne School of Computer Science and Information Technology. He concurrently holds roles as Program Director for multiple cybersecurity programs including MAS Cyber Security and CAS Information Security. With over 20 years' industry experience in IT security and academic leadership, he bridges research and practical applications in cybersecurity. Education: Dipl. El.-Ing. ETH (Electrical Engineering) Master of Advanced Studies in Information Security (HSLU/FHZ) Certified Information Security Manager (CISM) CAS IT Management Zertifikat in Hochschuldidaktik Research Focus: Specializes in enterprise cybersecurity strategies, IoT security, cloud computing risks, and information security management systems (ISMS). Active in national studies assessing cybersecurity posture of Swiss SMEs and critical infrastructure sectors. Publishes extensively on practical cybersecurity implementation through handbooks and case studies. Program Leadership: Co-directs 9 academic programs including: CAS Cyber Security Defence & Response MAS Data Privacy CAS IT-Audit & Assurance Professional Contributions: Serves on SWITCH ICT security committees, ISACA, and cybersecurity alumni networks. Delivers keynote presentations at Swiss Treasury Summits and European Power Network conferences. Leads industry-relevant research projects like 'Cyber Risk Management in Swiss Enterprises'. Teaching: Designs courses covering threat analysis, incident response, and regulatory compliance (GDPR/ISO 27001). Develops lab-based training for managers and technical staff through specialized workshops.

Adriana RicklinView profile

Researcher

• Data Science
• Reinforcement Learning
• Machine Learning
• +3 more

Adriana Ricklin is a Research Associate at Lucerne University of Applied Sciences and Arts, affiliated with the Lucerne School of Business and the Institute of Communication and Marketing. Concurrently, she is a PhD candidate at Eindhoven University of Technology's Department of Mathematics and Computer Science, researching sequential decision-making methods for e-commerce optimization under Professor Maurits Kaptein. Education: PhD candidate at Eindhoven University of Technology (2024-present) MSc Applied Information & Data Science, Hochschule Luzern (2019-2022) BSc Business Administration, Hochschule Luzern (2015-2018) Research Focus: Her expertise spans reinforcement learning, predictive analytics, and machine learning applications in sustainability-focused e-commerce. Key projects include Algorithmic Nudging for Sustainability, Sharing Potential Accelerator, and real-time sentiment analysis for brand reputation. Publication Trends: Recent works demonstrate consistent focus on machine learning adaptations for consumer behavior prediction and sharing economy optimization, utilizing advanced methods like LSTMs and graph neural networks across e-commerce and peer-to-peer platforms. Professional Engagements: Contributes to multiple HSLU research initiatives including Sustainable Consumer Advisor and AI-assisted talent acquisition projects, collaborating with teams at the Teaching & Research Institute for Data Science.

• Machine Learning
• Deep Learning
• Recommender Systems
• +3 more

Pascal Wullschleger serves as Research Associate and Doctoral Student at Lucerne School of Computer Science and Information Technology, Lucerne University of Applied Sciences since 2022, concurrently working as Data Scientist at Jaywalker Digital. His expertise bridges academic research and industry applications in machine learning. His educational background includes: Master of Science in Computer Science, Lucerne University of Applied Sciences Bachelor of Science in Computer Science, Lucerne University of Applied Sciences Wullschleger's research demonstrates deep specialization in Machine Learning and Natural Language Processing , with significant contributions to health informatics and recommender systems . His work spans over 20 projects including STU Recommender Systems , Adverse Event Mining , and AI for All , focusing on practical implementations in healthcare, finance, and consumer domains. Technical competencies encompass Reinforcement Learning, Deep Learning, and Linux-based development environments. Publication trends reveal evolving focus from health record analysis (2022) to explainable public health NLP (2024) and specialized LLM applications for food taxonomy (2025), indicating growing expertise in domain-specific language model adaptation. Key recognition includes: ABIZ Team Achievement for crafting first AI-generated beer recipe While no formal student advising is documented, Wullschleger actively collaborates with industry partners including Prepress Media AG, Eventfrog, and Siemens Building Technologies on revenue management, fake review detection, and financial advisory systems. His projects consistently address real-world optimization challenges through data science. He operates within the ABIZ research ecosystem at HSLU, contributing to cross-disciplinary initiatives like Skin-App for medical eczema grading and PFAS analysis in Medizintechnik, demonstrating commitment to socially impactful AI solutions.

Eduardo Gutierrez PrietoView profile

Researcher

• Mechanics
• Structural Engineering
• Flexible Structures

Eduardo Gutierrez Prieto serves as a Doctoral Assistant at the Flexible Structures Laboratory (FLEXLAB) within the Institute of Mechanical Engineering (IGM) at EPFL's School of Engineering, while concurrently pursuing doctoral studies in the Mechanics program (EDME). His research focuses on Mechanics, particularly Structural Engineering and Flexible Structures, examining systems that undergo significant deformations to advance mechanical design principles. This work integrates computational modeling and experimental validation within EPFL's engineering ecosystem.

Emily Caroline Bezerra AlexandreView profile

Researcher

• Printed Electronics
• Flexible Sensors
• Sustainable Electronics
• +3 more

Emily Caroline Bezerra Alexandre is a Guest PhD Student at EPFL's School of Engineering (STI), affiliated with the Institute of Microengineering (IEM) and the SCI-STI-SC research group. She concurrently serves as a Junior Scientist at Silicon Austria Labs (SAL), focusing on sustainable sensor development. Her research emphasizes printed electronics, flexible sensors, and additive manufacturing for biomedical applications, including a sustainable diabetes monitoring device under Prof. Sandro Carrara's supervision at EPFL and co-supervision by Dr. Jürgen Kosel at SAL. Education: BSc in Science and Technology (2019) and Materials Engineering (2020) from Federal University of Rio Grande do Norte (Brazil), followed by an MSc in Materials Science and Engineering from KAUST (Saudi Arabia, 2022). Her master’s work involved 3D-printed electronic skin for tactile sensing. She is part of the Advanced Sensor and Electronics Technologies (ASET) group at SAL, advancing aerosol jet printing strategies for sustainable electronics. Laboratory affiliations include EPFL's Brain-Computer Interface (BCI) lab (https://www.epfl.ch/labs/bci/), reflecting interdisciplinary collaboration in sensor-driven technologies. Her work integrates material efficiency, energy sustainability, and waste reduction principles in sensor design.

• Computer Security
• Formal Verification
• Networking Protocols
• +3 more

Dr. Christoph Sprenger is a Lecturer at the Department of Computer Science at ETH Zürich, specializing in formal verification of security protocols and networking systems. His work focuses on ensuring the correctness and security of distributed systems, databases, and network infrastructure through rigorous mathematical methods. His research addresses challenges such as verified isolation guarantees for database transactions, formal verification of router implementations, and secure data plane protocols in next-generation internet architectures. He has contributed to frameworks like IsaNet and N-Tube, emphasizing practical applications of formal methods in real-world systems. Key themes in his publications include protocol design, cryptographic security, and compositional verification techniques. Recent work explores the intersection of formal verification with path-aware networking and distributed system reliability. His research maintains a strong emphasis on bridging theoretical foundations with deployable solutions. Current projects involve advancing formal verification tools for critical infrastructure components, such as transactional memory managers and secure service architectures. His work consistently bridges gaps between abstract protocol specifications and their secure, interoperable implementations.

• Crystallography
• Organic Chemistry
• Inorganic Chemistry
• +3 more

Eduard Rusanov is a Senior Researcher at ETH Zurich's Department of Inorganic Functional Materials under Prof. Maxim Komalenko. He holds a PhD in Organoelement Chemistry from the National Academy of Science Ukraine (1997) and an M.S. in Chemistry from Taras Shevchenko National University of Kyiv (1993). His primary research focuses on small-molecule crystallography and inorganic materials synthesis. He concurrently serves as a part-time Visiting Professor at Taras Shevchenko University (2012–2022) and previously led the X-ray Single Crystal Diffraction Centre at the Institute of Organic Chemistry in Ukraine (2013–2022). His work spans over 330 publications, emphasizing structural chemistry and materials design, with applications in catalysis, medicinal chemistry, and nanotechnology. Key contributions include studies on heterocyclic compounds, quantum dot synthesis, and high-pressure crystal engineering. His research integrates experimental methods like X-ray diffraction with computational approaches (e.g., DFT), advancing understanding of molecular structures and their functional properties. His academic trajectory includes postdoctoral roles at York University, the University of Neuchâtel, and Martin-Luther-University Halle-Wittenberg, where he specialized in crystallography and quantum chemistry. His expertise bridges organic/inorganic chemistry with advanced materials development. Awards and grants are not explicitly listed, but his extensive publication record (3,851 citations, H-index 33) underscores his significant scholarly impact.

• Parallel Computing
• Java Virtual Machine (JVM) Optimization
• Performance Profiling
• +5 more

Walter Binder is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a MSc, PhD, and venia docendi from Vienna University of Technology. Previously, he was a senior researcher at the Artificial Intelligence Laboratory, EPFL. His research focuses on program transformations, virtual execution environments, aspect-oriented programming, profiling, and resource management. Education: MSc from Vienna University of Technology PhD from Vienna University of Technology Venia docendi (Habilitation) from Vienna University of Technology Research Interests: His work spans JVM optimization, parallel computing, and dynamic program analysis. Notable contributions include tools like Renaissance (a JVM benchmark suite), S2S (SQL-to-Stream translator), and Akkaprof (profiler for actor-based systems). He explores topics such as thread management, vectorization, and performance profiling in distributed systems. Articles Trends: Recent work emphasizes JVM performance (e.g., Java Vector API, Native Image optimizations), parallel execution policies (NAS benchmarks), and adaptive runtime systems (e.g., MPR framework). He also investigates big data systems (Spark, Node.js) and runtime verification tools. Grants & Labs: Leads projects on JVM profiling, polyglot runtimes, and large-scale program analysis. His lab develops tools like NodeMOP for Node.js and AccStream for stream processing systems.