Srishti Palani is a PhD Candidate at the University of California, San Diego. She researches at the intersection of human-computer interaction, cognitive science, and artificial intelligence. She conducts mixed-methods studies to deepen our understanding of how people search, synthesize, and create using vast amounts of disparate information on the Web and Large Language Models. Based on this understanding of user behavior, she develops novel intelligent interaction techniques to augment knowledge discovery, sensemaking, and creativity! Her research has been published at top conferences such as ACM CHI, UIST, CSCW, CHIIR, and SIGIR and has won several prestigious awards, including best paper awards and nominations. Among other honors, she is a Google PhD Research Fellow, Heidelberg Laureate Young Researcher, NCWIT Aspirations in Computing Awardee, and Grace Hopper Research Scholar mentor. During her PhD, she has also worked in top industry research labs such as Microsoft Research, Autodesk Research, and the Allen Institute for AI. Before her PhD, she graduated summa cum laude from Mount Holyoke College, double majoring in Computer Science and Psychology, where her thesis was a CRA Outstanding Undergraduate Researcher Award finalist and awarded the Phi Beta Kappa Research Prize. Outside of research, she is passionate about establishing mentorship programs to bridge the gender gap in tech and teaching computational and design thinking courses to the next generation of innovators.

AG 1, AG 2, AG 3, INET, AG 4, AG 5, D6, SWS, RG1, MMCI   Info

AG Audience

English

60 Minutes

Kaiserslautern

Searching and exploring information online is integral to everyday life, shaping how we learn, work, and create. As the Web paradigm evolves to include foundational AI models and beyond, we are experiencing a shift in how we search and work. With this transformation in human-AI interaction, it is important to investigate how we might present the user with the right information in the right context, the right representation, and at the right time. In this talk, I will share how I have explored these questions in the context of complex critical information work (such as knowledge discovery, synthesis, and creativity). I present insights about user behaviors and challenges from mixed-method studies observing how people conduct this work using today’s tools. Then, I present novel AI-powered tools and techniques that augment these cognitive processes by mining rich contextual signals from unstructured user-generated artifacts. By deepening our understanding of human cognition and behavior and building tools that understand user contexts more meaningfully, I envision a future where human-AI interactions are more personalized, context-aware, cognitively-convivial, and truly collaborative.

Annika Meiser

+49 681 9303 9105

--email hidden

Zoom

668 9092 0474

passcode not visible

logged in users only