جست‌وجوی استاد و پژوهشگر

Seraina Mohrمشاهده پروفایل

مدرس

• Digital Communications
• Web Content Development
• Social Media Strategies
• +۴ مورد دیگر

Seraina Mohr is a Lecturer and Head of the Competence Center for Communication Management at the Lucerne School of Business (HSLU Wirtschaft). She holds a Lic. phil I in Germanistik und Geschichte NDS from the Universität Zürich and specializes in Digital Communications, Social Media Strategies, and Content Strategy. Her roles include leading the MAS Digital Marketing and Communication Management program and overseeing various research and service projects focusing on topics like generative AI in marketing, sustainable consumer behavior, and community-oriented sponsorship. Her research spans digital transformation, online community management, and the integration of innovative technologies into marketing practices. Notable projects include studies on AI applications in marketing (2023), cognitive dissonance in sustainable behavior (2023), and the impact of creative education on business attitudes (2020). She has authored multiple publications, including books on innovation and social media strategies for museums. Awards include the 2016 Best Paper Award (GMW) for work on organizational development. Mohr actively contributes to conferences and collaborates on initiatives like the 'WRITE-UP!' creative writing project and EUKO conferences on economic communication. Her expertise bridges academic research, practical marketing strategies, and organizational leadership in digital realms.

• Business Law
• Labor Law
• Data Protection
• +۳ مورد دیگر

Isabelle Oehri holds dual roles as Deputy Head of the Competence Center for Management and Law and Lecturer at the Lucerne School of Business (HSLU). She specializes in business law, labor law, and data protection, with notable expertise in intellectual property and entrepreneurship. Her academic background includes a Master's in Law & Economics from the University of St. Gallen (2011) and a legal qualification as a Zurich-licensed attorney (2015). She leads the 'Smart-up' startup support program and chairs the 'Recht & Steuern' department at HSLU. Her research focuses on AI ethics in law, employment law challenges (e.g., contractual obligations, termination alternatives), and digital transformation in business practices. She actively contributes to regulatory discussions on data protection (EDÖB investigations) and intellectual property rights in AI contexts. Her work bridges academic research with practical business needs, particularly for SMEs. Key projects include evaluating Luzern’s sex work regulations, analyzing administrative burdens for SMEs, and exploring agile management practices. She serves on the University Council of the University of Liechtenstein and co-leads the 'Digital Female Founders' initiative to promote gender diversity in tech startups.

• Insurance
• Cybersecurity
• Sustainability
• +۵ مورد دیگر

Carlo Pugnetti is a Lecturer at the Lucerne School of Business (HSLU) and the Institute of Financial Services Zug (IFZ). He holds a Ph.D. in Industrial Engineering and Management from Stanford University with a focus on Risk Analysis. His professional experience includes leadership roles at Allianz Group, including CEO of Allianz Global Assistance, and advisory positions at iamYiam and Caveo. Pugnetti's research focuses on cybersecurity in SMEs, sustainability in insurance, and behavioral aspects of risk management. He has published extensively on cyber vulnerabilities, InsurTech, and customer expectations in Swiss financial markets. His work bridges academic research with practical industry challenges, particularly in digital transformation and regulatory adaptation. Education: Ph.D. Industrial Engineering and Management (1992-1997), Stanford University M.Sc. Electrical Engineering (1989-1991), Stanford University B.Sc. Electrical Engineering (1986-1989), New Mexico State University Research Interests: Pugnetti's work addresses cybersecurity behavioral challenges, sustainability reporting, and digital innovation in insurance. Key projects include the IFZ InsurTech Report, studies on employee cyber vulnerability, and analyses of customer attitudes toward green insurance products. His research emphasizes practical solutions for SMEs and emerging technologies like AI-driven fraud detection. Publications: Over 20 peer-reviewed articles and reports, including works on cyber resilience, customer sustainability expectations, and social media engagement in insurance. Recent studies explore asymmetric economic impacts of global crises and cross-cultural leadership practices in financial services. Advisory Roles: Member of advisory boards for iamYiam, Caveo, and Benthurst. Served as President of the Faculty Board at Zurich University of Applied Sciences (2020-2023). Active in policy discussions on Swiss pension reform and digital insurance transformation. Labs/Teams: Collaborates with the IFZ research group on behavioral and technological insurance challenges. Engages with industry partners like Medi24 and the American Insurance Association on policy and innovation initiatives.

• Machine Learning
• Deep Learning
• Recommender Systems
• +۳ مورد دیگر

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.

Abdullah Kahramanمشاهده پروفایل

مدرس

• Bioinformatics
• Cancer omics
• Alternative splicing
• +۳ مورد دیگر

Abdullah Kahraman is Group Leader of Data Science in Life Sciences and Lecturer at the Institute for Chemistry and Bioanalytics in the School of Life Sciences at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW). He holds a Diploma in Bioinformatics from University of Applied Science Giessen-Friedberg and a PhD in Computational Biology from the University of Cambridge. His research focuses on computational methods for cancer omics, particularly using long-read sequencing to study alternative splicing in cancer development and therapy resistance. Kahraman develops bioinformatics tools for analyzing isoform switching events in tumors and applies machine learning to identify biomarkers and therapeutic targets. His work bridges computational biology and clinical oncology through collaborations with university hospitals in Zurich and Basel.

Katharina Blankartمشاهده پروفایل

استاد

• Health Economics
• Health Policy
• Health Care Data Science
• +۳ مورد دیگر

Prof. Dr. Katharina Blankart is a Professor of Health Economics at Bern University of Applied Sciences' School of Health Professions, leading the Institute of Health Economics and Policy. She holds affiliations with the Hamburg Center for Health Economics and Leibniz Science Campus Ruhr. Her expertise spans health policy, healthcare data science, and technology innovation in healthcare. Education includes a PhD in Health Economics from Ludwig Maximilian University of Munich (2012), followed by postdoctoral roles at the University of Hamburg and Columbia University. She previously served as Assistant Professor at the University of Duisburg-Essen (2016–2023). Research focuses on efficiency analyses in healthcare systems, health technology evaluation, and regulatory frameworks. Notable work includes studies on off-label drug use, regulatory pluralism, and generic drug market dynamics. Awards include the 2012 GRPG Dissertation Prize. Active in academic leadership as Team Lead and Entrepreneurship Facilitator, she contributes to Swiss and German health economics societies. Language skills include German (native), English (professional), and French (basic).

Sarah Rochatمشاهده پروفایل

استاد

• Robotics
• Human-Robot Interaction
• Artificial Intelligence
• +۵ مورد دیگر

Sarah Rochat is a Professor at the Bern University of Applied Sciences (BFH), affiliated with the Institute for Human-Centered Engineering. Her work focuses on human-robot interaction, intuitive robot programming, and agile production systems. She leads the Robot Programming by Demonstration project, which aims to simplify robot reprogramming through gesture-based interfaces using tools like the Logitech VR Ink Stylus. This innovation targets industries needing flexible automation solutions, particularly in manufacturing sectors with diverse products and small production volumes. Education: Sarah holds a Psychology half-degree, a Mathematics Master's, a Robotics PhD, and a postdoc in brain-machine interfaces. She has been at BFH since 2014, combining teaching and research in robotics and human-centered engineering. Research interests include human-robot collaboration, no-code programming for production workers, and ethical implications of AI/robotics in society. Her projects emphasize practical applications such as cobot integration, worker empowerment through accessible tools, and reducing production costs via agile systems. Current collaborations involve 7 industry partners (robot developers, medical firms, sensor manufacturers, and watchmakers) to refine demonstration-based learning for industrial use. Supported by Microtech Booster and Innosuisse grants, her team explores feasibility through simplified case studies. Labs/Teams: Active in BFH’s Human-Centered Engineering group, focusing on interdisciplinary projects blending robotics, ethics, and industrial needs. Future work aims to expand no-code programming tools and validate technologies in real-world manufacturing environments.

Boi Faltingsمشاهده پروفایل

استاد

• Artificial Intelligence
• Constraint Programming
• Multi-Agent Systems
• +۵ مورد دیگر

Boi Faltings is a Full Professor of Computer Science and Head of the Artificial Intelligence Laboratory (LIA) at EPFL. He holds a Diploma from ETH Zurich and a Ph.D. from the University of Illinois at Urbana-Champaign. His research focuses on artificial intelligence, multi-agent systems, computational game theory, and privacy-preserving AI. He has co-founded six companies in e-commerce and security, advised numerous enterprises, and published over 300 refereed papers. He has graduated over 40 Ph.D. students, many of whom have won major awards. His academic roles include teaching in Computer Science and Communication Systems, and he advises students across multiple disciplines. He leads research in incentive mechanisms, federated learning, and continual learning. His work on peer prediction and privacy-preserving techniques has been widely recognized. Awards include Fellowships from ECCAI and AAAI. Key research themes include game-theoretic information elicitation, adaptive multi-agent systems, and ethical AI. His lab explores cutting-edge topics like AI-driven pricing for sustainability and federated learning frameworks. His teaching includes advanced machine learning seminars and courses on AI applications.

Marilyne Andersenمشاهده پروفایل

استاد

• Sustainable Architecture
• Natural Lighting
• Design Decision Support
• +۷ مورد دیگر

Marilyne Andersen is a Full Professor of Sustainable Construction Technologies at École Polytechnique Fédérale de Lausanne (EPFL), leading the Integrated Performance in Design Laboratory (LIPID). Since April 2025, she also serves as Director General of GESDA, focusing on science-diplomacy for societal impact. Previously, she was Dean of EPFL's School of Architecture, Civil and Environmental Engineering (ENAC) from 2013-2018 and Academic Director of the Smart Living Lab. Her academic journey includes roles at MIT and visiting professorships at Singapore University of Technology and Design. Her research bridges architecture, building science, and chronobiology, emphasizing daylight’s impact on health, well-being, and building performance. Key areas include occupant comfort, light and health interplay, and design decision support tools. She co-founded OCULIGHT dynamics, applying research to architectural practice. Honors include the inaugural Daylight Award for Research (2016), Taylor Technical Talent Award (2009), and EPFL Chorafas Prize (2005). She leads large-scale projects like SWICE (energy transition) and collaborates with 10+ institutions and 30+ partners. She chairs editorial boards for journals like Building and Environment and holds governance roles in CUB and ArtTech Foundations. Her academic network includes over 250 refereed publications and 19 doctoral supervisees. Current roles span EPFL committees (Diversity Office, Academic Evaluation) and international advisory boards (Daylight Academy, InnoSuisse).

Francesco D'Angeloمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +۳ مورد دیگر

Francesco D'Angelo is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences (IC) and the Institute of Computer Science and Communications Systems (IINFCOM). He is part of the Theory of Machine Learning Laboratory (TML) and enrolled in the Doctoral program in computer and communication sciences (EDIC) under the EPFL Doctoral School (EDOC). His research focuses on foundational aspects of machine learning, including sparse attention mechanisms, Bayesian neural networks, uncertainty estimation, and continual learning. He holds the position of Doctoral Assistant at the TML lab, where he contributes to advancing theoretical and practical applications of machine learning algorithms. Research Interests: Francesco's work bridges theoretical computer science with applied machine learning. His key areas include developing robust models for uncertainty quantification, improving generalization in overparameterized networks through regularization techniques like weight decay, and exploring the interplay between transformer architectures and causal structure induction. He also investigates methods to mitigate catastrophic forgetting in continual learning scenarios and applies Bayesian approaches to enhance out-of-distribution detection capabilities. Publications: His recent work explores topics such as sparse attention mechanisms in transformers, the necessity of weight decay in deep learning optimization, and Bayesian methods for uncertainty estimation. These contributions highlight his expertise in both foundational theory and practical algorithm design within the machine learning domain. Labs & Teams: As part of the TML lab, he collaborates on interdisciplinary projects at the intersection of machine learning theory and applications, contributing to advancements in neural network architectures and probabilistic modeling techniques.

Seyedhadi Mirfarshbafanمشاهده پروفایل

پژوهشگر ارشد

• Wireless Communications
• VLSI Circuits and Systems
• Digital Signal Processing
• +۱ مورد دیگر

Dr. Seyedhadi Mirfarshbafan is a Research Fellow at the Institute for Integrated Systems, ETH Zurich. He received his B.Sc. and M.Sc. degrees in Electrical Engineering from Sharif University of Technology, Tehran, Iran in 2016 and 2018, respectively, and an M.Sc. in Electrical and Computer Engineering from Cornell University in 2020. He completed his doctoral studies at ETH Zurich in 2025. His educational background includes: B.Sc. in Electrical Engineering, Sharif University of Technology, 2016 M.Sc. in Electrical Engineering, Sharif University of Technology, 2018 M.Sc. in Electrical and Computer Engineering, Cornell University, 2020 Ph.D., ETH Zurich, 2025 Dr. Mirfarshbafan's research interests encompass wireless communications, VLSI circuits and systems, digital signal processing, and machine learning. He specializes in the design of digital VLSI circuits for communication systems, integrating machine learning to optimize signal processing and hardware efficiency. His interdisciplinary work aims to develop innovative solutions for next-generation wireless networks. He is an active member of the Integrated Information Processing (IIP) research group at ETH Zurich, contributing to projects that bridge theoretical communication models with practical VLSI implementations.

• Computer Security
• Formal Verification
• Networking Protocols
• +۳ مورد دیگر

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.

Haotong Qinمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Dr. Haotong Qin is a Researcher at the Department of Information Technology and Electrical Engineering (D-ITET) at ETH Zurich, affiliated with the Center for Project-Based Learning. His work focuses on model compression techniques such as quantization and binarization, with applications in deepfake detection, diffusion models, and autonomous systems. Key research interests include improving the efficiency and robustness of neural networks, particularly for real-world deployment. Research highlights involve developing methods like SAGNet for robust deepfake detection under limited data, and Q-SAM2 for efficient segmentation models. His contributions span domains from computer vision to robotics, addressing challenges in safety-critical systems and large language model optimization. Recent publications emphasize low-bit quantization for diffusion models, vision-language integration, and traffic demand prediction using graph-based approaches. Collaborative projects include work on autonomous racing trajectory planning and cybersecurity for online social networks. No specific grants or advisees are listed, though his involvement with ETH's project-based learning initiatives suggests pedagogical engagement. The Center for Project-Based Learning serves as his primary research hub.

• Medical Data Science
• Machine Learning in Healthcare
• Artificial Intelligence Applications
• +۳ مورد دیگر

Kieran Chin-Cheong is a Researcher affiliated with the Professur für Informatik (Computer Science Professorship) at ETH Zürich. His position is part of the Department of Computer Science, focusing on Medical Data Science. He holds an email address at kieran.chincheong@inf.ethz.ch and is based at CAB G33.1, Universitätstrasse 6, 8092 Zürich, Switzerland. His research interests center on applying machine learning and computational methods to address challenges in healthcare, including medical imaging analysis, predictive modeling for clinical outcomes, and development of interpretable AI systems for medical diagnostics. His work spans areas such as pediatric disease prediction (e.g., pulmonary hypertension, appendicitis), glucose forecasting in diabetes, and synthetic medical data generation while preserving privacy. Notable contributions include advancements in deep learning for echocardiogram analysis, interpretable ultrasonography models, and methodologies for constrained clustering and multimodal data processing. His interdisciplinary approach bridges computer science and clinical medicine, aiming to improve diagnostic accuracy and patient care through data-driven solutions. No specific grants, awards, or advisees are explicitly listed in the provided materials. His research aligns with ETH Zürich's focus on translational medical informatics and computational healthcare technologies.

• Visual Analytics
• Information Visualization
• Computational Linguistics
• +۳ مورد دیگر

Menna El-Assady is an Assistant Professor at ETH Zurich's Department of Computer Science , leading the Interactive Visualization and Intelligence Augmentation Lab (IVIA) . She works at the intersection of data analysis, visualization, computational linguistics, and explainable AI , focusing on combining machine learning with visual analytics for text data. Current affiliations: ETH Zurich (Department of Computer Science, AI Center) Previous roles: Research Fellow at ETH AI Center, Research Associate at University of Konstanz, Doctoral Student at OntarioTech University Research Interests El-Assady's work focuses on human-AI collaboration , particularly through: Interactive systems for topic model refinement and language model explainability Visual analytics frameworks for argumentation analysis and digital humanities Explainable AI solutions for medical decision support and political deliberation Trust calibration mechanisms in generative AI and recommender systems Scientific Contributions Developed explAIner - a visual analytics framework for explainable machine learning Created LingVis - integrating computational linguistics with visual analytics Designed VALIDA and VisArgue for analyzing political debates and rhetoric Co-organized workshops: ArgVis , Vis4DH , VisLR , and VISxAI Academic Recognition Best Paper Award: Honorable Mention (IEEE Trans. on Visualization and Computer Graphics, 2018) 2024 VGTC Visualization Significant New Researcher Award