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Hi. My name is Jeff Rzeszotarski.

I research human-AI collaboration, data visualization, and social computing within a domain of computer science called human-computer interaction (HCI).

My current work focuses on helping both experts and everyday people make sense of data using empirically validated design practices and AI-augmented tools. These days, I am especially interested in how human-AI collaborations can help novice users to manage large amounts of complex information while maintaining independence, intellectual property rights, and trustworthiness. I employ interdisciplinary knowledge from psychology (sensemaking theory), art history, and design in my work to make tools that are both effective and usable. I strongly believe that data big and small must be made accessible to as many people as possible, and I endeavor to encode that value into the systems I design and the research I pursue.

In the recent past I was a faculty member of the School of Information Science at Cornell University. In addition to maintaining my research group independently, I am currently consulting with organizations on the implementation of AI-powered tools and data analytics platforms.

My name is pronounced "Jeff Rez-oh-TAR-ski" [dʒɛf ɹ̠ˤʷɛzoʊtɑɹ’skiː]. You can call me Jeff Rz (rez).

Feel free to email me at "jeff [dot] rzeszotarski [@t] gmail.com"

About Me

I received my PhD from the Human-Computer Interaction Institute at Carnegie Mellon University, advised by Niki Kittur. I pursued my BA at Carleton College and received a MS in human-computer interaction from Carnegie Mellon. My work has been featured publicly in venues such as TechCrunch and GigaOM. While a graduate student I co-founded a startup, DataSquid. I am a former Siebel Scholar, Carnegie Mellon Innovation Fellow, and Microsoft Graduate Research Fellow. In the past I have spent summers researching at Google and Microsoft Research. My current work is primarily supported by grants from the National Science Foundation, Bloomberg, and Microsoft.

Back at Carleton I developed a continuing interest in Japanese and Chinese art history, which has led me to collect ink paintings and woodblock prints. In my spare time I experiment with 3d printing, make ceramics, and travel. If you've managed to read this far, here are some more fun facts: in the past I've hosted radio shows on KRLX; I once was nipped by a pet tiger; some of my video game themed pottery was briefly Internet-famous; and sometimes I attend conventions for vintage fountain pens.

My lab is currently investigating the intersection of data visualization, HCI, psychology, and AI in a variety of ways:

  • With former advisee Swati Mishra, I examined how treating AI models as students in need of teaching can lead to better outcomes for novice model builders.
  • With former advisee Jing Nathan Yan, I have developed interactive techniques for exploratory data analysis and visualizing issues in the AI data pipeline.
  • Working with Daye Kang, I am looking into how large language models can be seamlessly embedded into interactive tools for qualitative analysis.
  • I have also advised the field work of Sharifa Sultana as she investigates how data management and storytelling practices in rural Bangladesh do and do not align with "canonical" conventions for visualizing data.
  • Co-advisees Shengqi Zhu, Chao Zhang, and Ayana Monroe are currently pursuing projects for novel interactive systems for supporting writers and journalists using language models as well as more fundamental human factors studies of the usability and impact of generative models on creativity.

Please reach out to me via email for portfolio samples, example syllabi, past course evaluations, and letters of reference.

Publications