Thesis Director: Prof. N. Marzari,
\r\nPhysics doctoral program
\r\nThesis Nr. 11552
\r\n
\r\nTo take part in the public defense, please contact directly the speaker
BRIDGE is a joint programme conducted by the Swiss National Science Foundation (SNSF) and Innosuisse, the Swiss Innovation Agency. It offers new funding opportunities at the intersection of basic research and science-based innovation, thereby supplementing the funding activities of the two organisations.
\r\n
\r\nBRIDGE Proof of Concept projects support young researchers (see eligibility criteria on the website) who aim to develop an application or service based on their own research findings. These projects may feature any type of innovation or research field.
\r\n
\r\nSubmission deadline: \r\n
The talk is jointly organized by the EPFL AI Center and the EPFL Human-Computer Interaction Group as part of the AI for Health seminar series.
\r\n
\r\nHosting professor: Prof. Pearl Pu (GR-PU)
\r\n
\r\nTitle
\r\nBeyond Recommendations: Designing Conversational Music Agents for Self-Awareness and Psychological Well-being
\r\n
\r\nAbstract
\r\nAs the demand for scalable mental health tools grows, the potential of Large Language Models (LLMs) lies in their ability to move beyond generic retrieval toward deeply adaptive, trustworthy support. This talk explores how music-driven conversational systems can bridge the gap between algorithmic recommendation and psychological intervention. The journey begins with establishing a foundation of trust through user-centric exploration. Using conversational music recommenders as a case study, I will discuss how critiquing strategies—such as progressive and cascading suggestions—shape user perceptions of helpfulness and serendipity. However, because trust is personal, I demonstrate how individual traits, including personality and trust propensity, dictate whether a user thrives under system-led or user-led initiatives.
\r\nBuilding on this rapport, the talk examines how these interfaces transition from suggesting songs to fostering psychological well-being. I will illustrate how music acts as a catalyst for self-awareness, using agents to guide users through emotional resonance and self-reflection. Furthermore, I will share findings on the role of generative AI in music-based reminiscence for older adults, where adaptive dialogue helps overcome cognitive barriers to memory recall. Collectively, these studies provide a roadmap for designing AI that moves beyond the playlist, transforming music-based chatbots into sustained partners for emotional and psychological health.
\r\n
\r\nBio
\r\nProfessor Li Chen is currently a Full Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU). She obtained her PhD degree in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and her Bachelor's and Master's degrees from Peking University, China. Her recent research focus has mainly been on conversational AI, explainable AI, recommender systems, and human-computer interaction. She has authored and co-authored over 160 publications, with over 13,000 citations (H-index 53). Her co-authored papers have received several awards, such as the RecSys’24 Best Student Paper Award, CHI’22 Honourable Mention Award, UMAP’20 Best Student Paper Award, UMUAI 2018 Best Paper Award, and UMAP’15 Best Student Paper Award. She received the President’s Award for Outstanding Performance in Teaching (Individual) 2024/25 and the President’s Award for Outstanding Performance in Research Supervision 2022/23. She has been included in the list of the world’s top 2% most-cited scientists by Stanford University since 2021, and the list of the Best Computer Science Scientists 2025/2026 by Research.com.
\r\n
\r\nShe is now an ACM senior member, founding co-editor-in-chief of ACM Transactions on Recommender Systems (TORS), steering committee member of ACM Conference on Recommender Systems (RecSys), associate editor of International Journal of Human-Computer Studies (IJHCS), editorial board member of User Modeling and User-Adapted Interaction Journal (UMUAI), and associate editor of ACM Transactions on Interactive Intelligent Systems (TiiS). She has also served as program co-chair of IUI’26, general co-chair of ACM RecSys’23, program co-chair of ACM RecSys’20, and program co-chair of ACM UMAP’18.
\r\n
Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.
\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.
\r\n
\r\nEffective quiz design:
\r\nIn this 1-hour workshop, we will focus on the design of effective quiz questions for your class with the assistance of LLM tools. We will explore both the ethical and practical questions associated with LLM use for this task through theoretical inputs and hands-on activities.
We are pleased to announce that the second edition of the Summer School on “Numerical methods for random differential models” (NUMRAD26), will take place at the Bernoulli Center at EPFL, Lausanne (CH), from June 2nd to 5th, 2026.
\r\n
\r\nThe summer school will cover both introductory and advanced topics on numerical methods in the following areas: high-dimensional approximation, Gaussian processes, reduced order modeling for scientific machine learning, and mathematical finance. The up-to-date program of the summer school can be found at
\r\nhttps://numrad.epfl.ch/scientific-program/
\r\n
\r\nThe school is addressed to young mathematicians (PhD students, early postdoc researchers, and highly motivated master students), and it will consist in lectures delivered by world-wide renowned experts. Participants will have the chance to share their research during a poster session.
\r\n
\r\nThere are no registration fees, but the number of participants is limited. You can apply to the summer school by submitting the application form by February 13th 2026 at:
\r\nhttps://numrad.epfl.ch/registration/
\r\nApplicants will be informed of the admission decision by email within three weeks after the application deadline.
\r\n
\r\nFor more details, please visit:
\r\nhttps://numrad.epfl.ch
\r\n
\r\nThe event is funded by the Bernoulli Center at EPFL, the EDOC EPFL, and by the CSQI Chair.
\r\n
\r\nLooking forward to seeing you in Lausanne next June!
Ultra-high-field MRI is delivering tangible clinical impact. With four 7T systems nationwide, Switzerland is uniquely positioned to drive efficient translational innovation in advanced imaging. This first national UHF MRI symposium brings together the experts shaping the future of UHF MRI in Switzerland and beyond. The event aims to address unmet clinical needs, spark new collaborative projects, and strengthen a community dedicated to advancing patient care through innovation. The CIBM is proud to be one of the organizers of the event, which will take place at the Sitem-insel on in Bern on June 3, 2026.\r\n