Prof Chirag Shah
Information and Computer Science
University of Washington
Dr. Chirag Shah, a distinguished academic and researcher, is a Professor at the University of Washington’s Information School (iSchool) and an Adjunct Professor at both the Paul G. Allen School of Computer Science & Engineering and Human Centred Design & Engineering (HCDE). His expertise spans AI, Search and Recommender Systems, and Machine Learning, with a focus on developing intelligent information access systems, proactive recommendations, and generative AI applications for information retrieval and image classification. As Founding Director of InfoSeeking Lab and Founding Co-Director of RAISE, he champions AI-driven transparency, fairness, and bias-free systems. Recognised with awards like the Karen Spärck Jones Award, he continuously shapes the field through publications, affiliations, and impactful consulting projects with industry giants like Amazon and Microsoft.
ML Engineering Lead, Search & Recommendations
A dynamic AI leader, currently driving ML advancements for search and recommendations at Canva, with a strong foundation from 13 impactful years at Microsoft. Within Microsoft, their roles evolved, spanning Bing and MSAI, and culminating in a vital contribution to the AETHER Committee’s Fairness and Inclusiveness working group, operationalizing Responsible AI. Their expansive expertise encompasses communications intelligence, email, text prediction, summarization, and more. With a career rooted in web and enterprise search, they’ve fostered an enduring passion for information retrieval since 1991. Fueled by a penchant for action and results, they thrive in compact, high-performing teams, striking a seamless balance between research and development.
Dr Johanne Trippas
Vice-Chancellor’s Research Fellow
Johanne is a Vice-Chancellor’s Research Fellow at RMIT University’s School of Computing Technologies and a driving force in advancing intelligent systems with a focus on spoken conversational search, cockpit digital assistants, and AI-enabled cardiac arrest identification. A 2019 Computer Science Ph.D. graduate from RMIT University, she earned accolades for her work, including the RMIT Deputy Vice-Chancellor’s Prize. Formerly a Doreen Thomas Research Fellow at the University of Melbourne, she actively contributes to ACM SIGIR and ACM CHIIR as a liaison, organiser, and committee member. Notably, her roles as ACM SIGIR 2022 Workshops Chair and ACM CUI 2022 Full Papers Chair showcase her dedication to shaping future AI capabilities.
Principal Research Scientist
A Principal Research Scientist at CSIRO’s Data61, Sarvnaz boasts 12+ years in health informatics, anchoring her expertise at the confluence of Information Retrieval, Natural Language Processing (NLP), and Machine Learning. With a coding intrigue kindled during high school, she pursued software engineering, AI, and NLP through a medal-winning Ph.D. Driven by creativity and a thirst for learning, she gravitated to CSIRO’s renowned interdisciplinary science. As a Deputy Director for ACL and former President of ALTA, her focus lies in NLP, Information Retrieval, and ‘information extraction.’ Her role in shaping medical decision support systems and pioneering NLP-driven epidemic intelligence for outbreak detection is noteworthy, proving her commitment to real-world impacts. Her advice to women aspiring in tech echoes empowerment, diversity, and unwavering opportunity.
Microsoft Search, Assistant and Intelligence (MSAI)
A Microsoft researcher and Architect in the Microsoft Search, Assistant and Intelligence (MSAI) group, Nick elevates information access techniques for Outlook, Teams, and workplaces. Hailing from Australia, their research focus spans research, publishing, and dataset dissemination. They specialise in search evaluation datasets like MS MARCO and TREC Deep Learning Track, with a vision to enhance search interactivity via “Neural Approaches to Conversational Information Retrieval.” Nick’s ANU PhD pioneered distributed information retrieval, while also navigating the transformative narrative of AI-generated content disrupting information retrieval.