Show Notes
- (01:30) Doris walked through her time doing research in physics and astrophysics at UC Berkeley and getting involved with data science.
- (04:11) Doris reflected on her decision to pursue the Ph.D. program in computer science at the University of Illinois, Urbana-Champaign.
- (05:53) Doris discussed her development of no-code, interactive visualization interfaces accelerating users toward data insight discovery.
- (10:37) Doris explained how the RISE Lab and I School at UC Berkeley helped shape her thinking around working with end-users and building something to serve the data science community.
- (16:05) Doris unpacked the focus of her Ph.D. dissertation - which is to make data exploration and visualization easier and more accessible through automation.
- (17:27) Doris shared the motivation and high-level design behind the development of Lux, a general-purpose visual exploration assistant situated within a computational notebook.
- (21:25) Doris revealed the recipe for open-source community engagement and roadmap prioritization with Lux.
- (26:17) Doris shared the founding story of Ponder, whose mission is to improve data science productivity by empowering users to do data science at all scales.
- (31:02) Doris explained how Ponder helps solve the fragmentation challenges across the data stack.
- (34:27) Doris provided a brief overview of Modin, which improves the scalability of data frames.
- (38:41) Doris discussed Ponder's go-to-market strategy to drive more enterprise interest toward the product.
- (41:23) Doris discussed her team's challenges in finding early design partners across various industries.
- (44:16) Doris shared valuable hiring lessons to attract the right people who are excited about Ponder's mission.
- (47:42) Doris shared fundraising advice to founders who are seeking the right investors for their startups.
- (49:33) Doris highlighted the difference between being a researcher and a founder.
- (51:06) Closing segment.
Doris' Contact Info
Ponder's Resources
Mentioned Content
Publications
- The Case for a Visual Discovery Assistant:A Holistic Solution for Accelerating Visual Data Exploration (IEEE Data Bulletin 2018)
- Understanding Sense-making in Visual Query Systems (IEEE Visual Analytics Science and Tech 2019)
- Deconstructing Categorization in Visualization Recommendation: A Taxonomy and Comparative Study (IEEE Transactions on Visualization and Computer Graphics 2021)
- Lux: Always-On Visualization Recommendation for Exploratory Data Science (Dec 2021)
Blog Posts
- Insight Machines: The Past, Present, and Future of Visualization Recommendation (Multiple Views, Feb 2020)
- Announcing Ponder (March 2022)
- How we parallelized 600+ pandas functions with Modin (March 2022)
- Using Lux to visualize your pandas dataframes with zero effort
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