Talks, lectures, and panels Keynotes Emancipatory Information Retrieval: Radically Reorienting Information Retrieval Research to Resist Corporate and Authoritarian Capture of our Information Ecosystems Forum for Information Retrieval Evaluation (FIRE) SlideShare | PPT Bias and Beyond: On Generative AI and the Future of Search and Society The International Workshop on Algorithmic Bias in Search and Recommendation (BIAS) , SIGIR SlideShare | PDF Efficient Machine Learning and Machine Learning for Efficiency in Information Retrieval The Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR) , SIGIR SlideShare | PPT Benchmarking for Neural Information Retrieval: MS MARCO, TREC, and Beyond NLIWOD workshop , International Semantic Web Conference SlideShare | PPT 5 Lessons Learned from Designing Neural Models for Information Retrieval The 10th Recherche d’Information SEmantique (RISE) workshop , The CORIA-TALN-RJC conference SlideShare | PPT Invited talks Sociotechnical Implications of RAG for Information Access Dagstuhl Seminar 25391: Retrieval-Augmented Generation – The Future of Search? SlideShare | PPT Emancipatory Information Retrieval People and Technology Lab (PATLab) , University College Cork SlideShare | PPT | Recording VIDEO Sociotechnical Implications of Generative AI for Information Access (Re)defining Responsible AI workshop, MILA SlideShare | PPT Search and Society: Reimagining Information Access for Radical Futures Canadian AI 2024 SlideShare | PPT Joint Multisided Exposure Fairness for Search and Recommendation SEA: Search Engines Amsterdam SlideShare | PPT What’s next for deep learning for Search? Etsy SlideShare | PPT So, You Want to Release a Dataset? Reflections on Benchmark Development, Community Building, and Making Robust Scientific Progress Spotify SlideShare | PDF Multisided Exposure Fairness for Search and Recommendation Lowe's SlideShare | PPT Deep Learning for Effective, Exposure-Aware, and Efficient Information Retrieval Microsoft Research Cambridge Multisided Exposure Fairness for Search and Recommendation Microsoft Research Montreal Neural Information Retrieval: In search of meaningful progress CIIR Talk Series , University of Massachusetts Amherst Details | SlideShare | PPT | Recording VIDEO Neural Information Retrieval: In search of meaningful progress CLIP Colloquium , University of Maryland Details | SlideShare | PPT Neural Models for Information Retrieval Facebook SlideShare | PPT Neural Models for Information Retrieval Microsoft Research Redmond SlideShare | PPT | Recording VIDEO Neural Models for Information Retrieval School of Computing Sciences , University of Glasgow SlideShare | PPT Neural Models for Document Ranking The 4th International Alexandria Workshop SlideShare | PPT Neural Models for Information Retrieval The NLIP seminar series , University of Cambridge computer laboratory SlideShare | PPT Using Text Embeddings for Information Retrieval School of Computing Sciences , University of Glasgow SlideShare | PPT A Simple Introduction to Word Embeddings North Eastern University SlideShare | PPT Vectorland: Brief Notes from Using Text Embeddings for Search Search Solutions SlideShare | PPT Lectures Neural Learning to Rank Dayananda Sagar College of Engineering SlideShare | PPT Deep Neural Methods for Retrieval University College London SlideShare | PPT Neural Learning to Rank University College London SlideShare | PPT Deep Neural Methods for Retrieval Emory University SlideShare | PPT | Recording VIDEO Neural Learning to Rank Emory University SlideShare | PPT | Recording VIDEO Learning to Rank for Information Retrieval with Neural Networks ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM) SlideShare | PPT | Recording | Hands-on lab materials VIDEO Deep Learning for Search ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM) SlideShare | PPT | Hands-on lab materials A Simple Introduction to Neural Information Retrieval University College London SlideShare | PPT Invited panels AI Ethics and the Tech Industry With Stefania Pecore , Florian Carichon , and Lilia Jemai McGill University McGill Computer Science Undergraduate Society (CSUS) and Encode Canada To Use Generative AI or Not To Use It With Mia Shah-Dand , Hessie Jones , and Beatriz González Mellídez Women in AI Ethics Plus (WAIE+) Debate Recording VIDEO Diversity, Equity, and Inclusion (DEI) lunch With Clemencia Siro , Vanessa Murdock , Nicola Ferro , and Doug Oard SIGIR From Research To Production With Julia Kiseleva , Craig Macdonald , Radim Řehůřek , and Agnes van Belle Industry Day , ECIR 