جست‌وجوی استاد و پژوهشگر

Pascal Felberمشاهده پروفایل

استاد

• Distributed Systems
• Concurrent Systems
• Trusted Execution Environments
• +۷ مورد دیگر

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).

Consuelo De Moraesمشاهده پروفایل

استاد

• Chemical Ecology
• Plant-Insect Interactions
• Multi-Trophic Interactions
• +۵ مورد دیگر

Consuelo De Moraes is a Full Professor at the Department of Environmental Systems Science, ETH Zürich. Her research centers on chemical signaling in ecological interactions, particularly plant-insect relationships, with applications in sustainable agriculture, conservation, and human health. She teaches courses in insect biology, plant-insect interactions, and ecological communication for Environmental Systems Science and Biology students. Research Focus: Her work explores sensory cues in shaping multi-trophic interactions, including olfactory signaling, disease transmission by vectors, and plant defense mechanisms. Current projects address ecological questions with implications for agroecosystems and public health. Scientific Awards: Nan-Yao Su Award for Innovation and Creativity in Entomology (2018) Fellow of the Entomological Society of America (2013) International Society of Chemical Ecology Silverstein-Simeone Award Fellow of the American Association for the Advancement of Science (2011) National Science Foundation CAREER Award (2007) Beckman Foundation Young Investigator Award (2003) David and Lucile Packard Foundation Award (2002) Academic Leadership: She oversees the ETH Zurich Entomological Museum, managing over two million specimens. The museum supports research, education, and public outreach through digitization efforts and guided tours.

Dejan Milojevicمشاهده پروفایل

مدرس

• Robotics
• Autonomous Vehicles
• Control Systems
• +۵ مورد دیگر

Dejan Milojevic is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where he works in Prof. Emilio Frazzoli's group at the Institute for Dynamic Systems and Control. He received his Ph.D. in robotics from ETH Zürich with affiliations at both the Institute for Dynamic Systems and Control and the Chemical Energy Carriers and Vehicle Systems Laboratory at Empa. He also earned his BSc. and MSc. in Mechanical Engineering from ETH Zürich. His educational background includes: Ph.D. in Robotics, ETH Zürich (affiliated with Institute for Dynamic Systems and Control and Empa) MSc. in Mechanical Engineering, ETH Zürich BSc. in Mechanical Engineering, ETH Zürich Dr. Milojevic's research focuses on the co-design of embodied intelligence systems, with particular interest in sensor selection and placement for mobile robots. His work explores the interplay between perception, decision-making, and control in autonomous systems. He is also keen on advancing uncertainty estimation and explainable AI within machine learning frameworks. His research has practical applications in autonomous vehicles and robotics. His recent publications demonstrate a consistent focus on optimizing the integration of perception systems and decision-making for mobile robots. The research shows how resource prioritization influences sensor choice, with cameras preferred for cost-effective designs while lidar sensors are chosen for better energy and computational efficiency. His work provides actionable information for designers of autonomous systems. His notable scientific contributions include: CODEI framework for Co-design of Embodied Intelligence Research on occupancy queries to quantify perception requirements for motion planners Integer Linear Programming approach for sensor and algorithm selection Dr. Milojevic has conducted research at Stanford University under Prof. Marco Pavone and has professional experience as a software engineer at Vay in Berlin, Germany. He has led significant research projects including the Automated Driving Sensor Test Vehicle project with multiple industry partners.

Jan Milan Deriuمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Jan Milan Deriu is affiliated with the ZHAW School of Engineering, where he is part of the Centre for Artificial Intelligence. He holds the role of Researcher and has been actively involved in multiple research projects, serving as Project Leader and Deputy Project Leader in areas such as dialogue systems evaluation, speech translation, and misinformation analysis. His work spans academic publications in top conferences and journals, focusing on AI-driven solutions in natural language processing and related fields. His research interests are centered around Natural Language Processing (NLP), including dialogue systems, text generation, and sentiment analysis; Artificial Intelligence evaluation methodologies; Speech technology, particularly dialect recognition and speech-to-text systems; Analysis of organized misinformation in social networks; Machine learning applications for data-centric AI development. Deriu has led or co-led several significant projects, including: Unified Model for Evaluation of Text Generation Systems (UniVal) – Deputy Project Leader (ongoing) Holistic Analysis of Organised Misinformation Activity in Social Networks – Project Leader (ongoing) End-to-End Low-Resource Speech Translation for Swiss German Dialects – Deputy Project Leader (completed) Pre-Study on Generation of Hockey News – Deputy Project Leader (completed) Call-E – Virtual Call Agent – Team Member (completed) DeepText: Intelligent Text Analysis with Deep Learning – Deputy Project Leader (completed) He collaborates extensively with international researchers and institutions, contributing to advancements in dialogue systems, speech technology, and AI evaluation frameworks. His publications emphasize practical applications, such as Swiss German dialect processing and misinformation detection in social media.

• Artificial Intelligence
• Data Management
• Machine Learning
• +۵ مورد دیگر

Dr. Jonathan Fürst is a Researcher at the ZHAW School of Engineering, part of the Intelligent Information Systems research focus at ZHAW Zurich University of Applied Sciences. His work spans AI-driven data systems, ontology matching, IoT applications, and cross-domain data integration. Key research interests include: AI applications in healthcare and education Machine learning for data integration and systems Multi-modal data exploration and natural language interfaces IoT networks and smart building technologies His projects include: AI-based Quality Management of BIM Models (project leader) DataGEMS : A data discovery platform for generalized exploratory search Multi-lingual data exploration systems Digital Health Zurich: Patient-centered clinical innovation Recent research trends emphasize explainable AI, weakly supervised learning, and real-world system robustness. His work bridges theoretical advancements with practical implementations in domains like healthcare, education, and smart infrastructure. No scientific awards are explicitly listed, though his active role in Horizon Europe projects reflects collaborative excellence. He contributes to interdisciplinary teams across data science, engineering, and healthcare.

• Complex Systems Science
• Artificial Intelligence
• Biomedical Engineering
• +۳ مورد دیگر

Prof. Rudolf Marcel Füchslin is a Professor at the ZHAW School of Engineering, specializing in Applied Complex Systems Science. His research spans interdisciplinary fields including biomedical engineering, quantum computing, medical physics, and data science. His work integrates computational modeling with practical applications in cancer therapy optimization, hyperthermia-radiation synergy, and quantum machine learning. He leads numerous projects involving advanced therapies, complex systems analysis, and AI-driven solutions. Notable projects include optimizing tumor control probability in hyperthermia-radiotherapy, developing quantum neural networks, and simulating droplet-based chemical systems. He has authored/co-authored over 50 peer-reviewed articles and edited books on topics like morphological computation and complex systems. Füchslin actively contributes to international conferences (e.g., ALIFE, ESHO) and collaborates with institutions globally. His research emphasizes translating theoretical models into real-world solutions, particularly in healthcare and engineering.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +۳ مورد دیگر

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.

• Data Science
• Information Retrieval
• Machine Learning
• +۳ مورد دیگر

Prof. Martin Braschler is a Lecturer and Director of the Institute of Computer Science at ZHAW School of Engineering (Zurich University of Applied Sciences). He specializes in data science, information retrieval, and enterprise search systems. His interdisciplinary work bridges computer science, machine learning, and multilingual systems. Key projects include leadership in the DataInc, Skillue, and INODE initiatives, focusing on data integration, intelligent systems, and EU-funded research. He has published extensively in top journals like SIGMOD Record and Information Systems , emphasizing practical applications of data science in business environments. His research explores topics such as cross-language retrieval, algorithmic approaches for multilingual systems, and enterprise knowledge management. Research interests revolve around applied data science methodologies, information access evaluation (e.g., CLEF), and real-world implementation of machine learning techniques. He co-authored influential books like Applied Data Science: Lessons Learned for the Data-Driven Business and Multilingual Information Retrieval: From Research to Practice , highlighting transitions from theoretical research to industry solutions. Braschler has led multiple projects in collaboration with industry partners, focusing on scalable data systems and enterprise applications. Notable contributions include developing the INODE end-to-end data exploration system and pioneering work on untrained models for multimodal retrieval. His work on skill-extraction algorithms for job-matching platforms demonstrates practical impact in human resources automation. Braschler’s projects often address challenges in data integration, semantic search, and the evaluation of information systems in real-world contexts.

• Bioinformatics
• Computational Biology
• Genomics
• +۴ مورد دیگر

Prof. Dr. Maria Anisimova is a Professor at the Institute of Computational Life Sciences within the ZHAW School of Life Sciences and Facility Management. Her research focuses on computational methods in evolutionary genomics, bioinformatics, and molecular evolution. Key areas include tandem repeat analysis, ancestral sequence reconstruction, and cancer genomics. She leads multiple projects on colorectal cancer mechanisms, computational drug discovery, and evolutionary biology. Her work integrates statistical models and algorithms to address challenges in genome analysis, including indel evolution, phylogenetics, and natural language-based database querying. Notable contributions include tools like ARPIP, ProPIP, and TRAL, advancing sequence alignment and tandem repeat detection. She also explores the role of protein intrinsic disorder and tandem repeats in cancer biology. Prof. Anisimova’s interdisciplinary approach spans bioinformatics, computational biology, and clinical applications, with publications in journals like *Nature*, *Genome Biology*, and *Molecular Biology and Evolution*. She has authored a textbook on evolutionary genomics and contributed to major conferences and workshops in the field.

• Data Science
• Machine Learning
• Privacy-Preserving Technologies
• +۳ مورد دیگر

Valentin Hartmann is a Researcher at the Data Science Laboratory (DLAB) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). His work focuses on advanced topics in data science, including differential privacy, optimal transport theory, and privacy-preserving machine learning. He holds a postdoctoral position and contributes to cutting-edge research in computational statistics and secure distributed learning. His research interests span multiple domains: (1) Development of privacy-preserving techniques for machine learning and data analysis, (2) Optimization of transport problems with applications in statistics and geometry, (3) Design of secure algorithms for distributed systems, and (4) Implementation of robust statistical methods through R packages like 'transport'. Valentin actively publishes in top-tier venues, with recent contributions addressing neural network behavior analysis, privacy risks in data distribution inference, and novel cryptographic approaches for collaborative learning. His work bridges theoretical foundations with practical software solutions, as evidenced by his development of the 'transport' R package for optimal transport computations. He is affiliated with the DLAB research group at EPFL's INN building (Office INN 315), contributing to interdisciplinary projects at the intersection of computer science, mathematics, and privacy engineering.

Ruedi Arnoldمشاهده پروفایل

استاد

• Computer Science Education
• Software Engineering
• Mobile Programming
• +۵ مورد دیگر

Ruedi Arnold is a Professor at the Lucerne School of Computer Science and Information Technology, part of the Lucerne University of Applied Sciences and Arts. He serves as Head of the Master's Program in Specialized Media and IT Teaching and Learning Methods. His academic journey includes a PhD from ETH Zurich (2007) and a Higher Teaching Degree from ETH Zurich (2003). Education: Dr. sc. ETH (Computer Science, 2007), Dipl. Informatik-Ing. ETH (2002), Matura Type C (1996). Professional experience spans roles at ETH Zurich (2002–2007), Ergon Informatik AG (2008–2011), and EB Zurich (2009–2012). Research focuses on software engineering, programming didactics, human factors, and interactive learning environments like InfoTraffic . Projects include Skin-App (medical image analysis) and Algorithmic Thinking in Lower Secondary Education . Awards include recognition for academic excellence at ETH Zurich and Strathclyde University. He has supervised numerous student projects and contributed to educational initiatives like Scratch workshops for youth. Publications span topics from AI pedagogy to P2P systems, with recent work emphasizing computational thinking in education. He is actively involved in academic committees, including the Luzerner Maturitätskommission and CH Open Workshop-Tage.

Jonas Freyمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Machine Learning
• +۷ مورد دیگر

Dr. Jonas Frey is a researcher at the Professorship for Robotic Systems within the Department of Mechanical and Process Engineering at ETH Zürich . His work focuses on autonomous robotic navigation, perception learning, and robust state estimation in challenging environments.

• Parallel Computing
• Java Virtual Machine (JVM) Optimization
• Performance Profiling
• +۵ مورد دیگر

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.

Tova Miloمشاهده پروفایل

استاد

• Database Systems
• Theoretical Computer Science
• Data Management
• +۳ مورد دیگر

Prof. Dr. Tova Milo is a prominent computer scientist and the Dean of the Faculty of Exact Sciences at Tel Aviv University. She holds the Chair of Information Management as a full professor and has served as Head of the Computer Science Department from 2011 to 2014. Her academic journey began with a doctorate in computer science from the Hebrew University of Jerusalem in 1992, followed by research positions at INRIA in Paris and the University of Toronto. Education: PhD in Computer Science (Hebrew University of Jerusalem, 1992) Milo’s research bridges database systems and theoretical approaches, focusing on large-scale data management. Key areas include semi-structured data , data-centric business processes , and crowdsourcing , with both theoretical and practical implications. Her work has shaped advancements in data integration, schema inference, and query optimization. She has received numerous accolades, including the ACM PODS Test-of-Time Award , the Weizmann Prize for Exact Sciences , and the VLDB Women in Database Research Award , reflecting her influence and advocacy for gender equality in STEM. Her leadership roles in major conferences (PODS, VLDB, ICDT) and editorial contributions (TODS, IEEE Data Engineering Bulletin) underscore her prominence in the field. Scientific Awards: ACM PODS Test-of-Time Award Weizmann Prize for Exact Sciences VLDB Women in Database Research Award IEEE TCDE Impact Award Fellow of the ACM Member of Academia Europaea Milo has secured significant grants from the Israel Science Foundation, US-Israel Binational Science Foundation, Israeli and French Ministries of Science, and the European Union, including an ERC Advanced Investigators Grant . She founded ExactShe , a mentoring program addressing gender disparities in exact sciences, further amplifying her commitment to inclusivity.

Teodora Vukovicمشاهده پروفایل

پژوهشگر ارشد

• Computational Linguistics
• Multimodal Analysis
• Human-Computer Interaction
• +۵ مورد دیگر

Dr. Teodora Vuković is a computational linguist at the University of Zurich's Faculty of Arts, specializing in multimodal analysis of human interaction and language technology. As Principal Investigator of the CAPIRE and LCP projects, she leads development of automatic tools for analyzing speech, gestures, and facial expressions to identify person-specific patterns while implementing data anonymization techniques.