University of Pittsburgh
3939 O'Hara Street
Pittsburgh, PA 15260
Hello! I'm a PhD student studying cognitive psychology at the University of Pittsburgh, based in the Learning Research & Development Center. I work with Benjamin Rottman in the Causal Learning & Decision Making Lab.
I use a combination of behavioral experiments and computational modelling to investigate human learning, reasoning, and decision-making. If you have any questions about my research or share similar interests, I'd love to hear from you.
My GitHub contains code for running experiments and analyses.
Cory Derringer (another student in our lab) does some pretty cool research, too.
I formerly worked with David Lagnado at UCL studying similar stuff.
I'm interested in how people think about causation. My research has investigated how people learn about causal direction (e.g., given two related variables, X and Y, is X or Y the cause?) and causal strength (e.g., how strong is the influence of a drug?). In particular, I investigate how people acquire such knowledge in light of beliefs about the way causal processes unfold over time. I'm also interested in the application of this research in applied contexts; e.g. understanding how patients and doctors understand the effects of drugs, and how this affects adherence.
Decisions from experience
Another thread of my work investigates how people evaluate options in the world based on past experience when making decisions. What strategies do we use to search for information prior to making a decision? Do our beliefs about the structure of the environment (e.g., the presence of temporal trends) influence our strategies? How do our (skewed) perceptions of outcomes and probabilities influence choice behavior?
Electronic versions are provided as a professional courtesy to ensure timely dissemination of academic work for individual, noncommercial purposes. Copyright (and all rights therein) resides with the respective copyright holders, as stated within each paper. These files may not be reposted without permission.
Soo, K. W. & Rottman, B. M. (2018). Causal Strength Induction From Time Series Data. Journal of Experimental Psychology: General, 147(4), 485-513. dx.doi.org/10.1037/xge0000423 [ abstract ] [ pdf ] [ data ]
Soo, K. W. & Rottman, B. M. (2018). Switch Rates Do Not Influence Weighting of Rare Events in Decisions from Experience, but Optional Stopping Does. Journal of Behavioral Decision Making. dx.doi.org/10.1002/bdm.2080 [ abstract ] [ pdf ] [ data ]
Soo, K. W. & Rottman, B. M. (2018). Causal Learning From Trending Time Series. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 2521-2526). Austin, TX: Cognitive Science Society. [ abstract ] [ pdf ]
Soo, K. W. & Rottman, B. M. (2016). Causal Learning with Continuous Variables over Time. In A. Papafrogou, D. Grodner, D. Mirman, & J.C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 153-158). Austin, TX: Cognitive Science Society. [ abstract ] [ pdf ]
Soo, K. W. & Rottman, B. M. (2015). Elemental Causal Learning from Transitions. In R. Dale, C. Jennings, P. Maglio, T. Matlock, D. Noelle, A. Warlaumont, & J. Yoshimi (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 2254-2259). Austin, TX: Cognitive Science Society. [ abstract ] [ pdf ] [ code ]
Soo, K. W. & Rottman, B. M. (2014). Learning Causal Direction from Transitions with Continuous and Noisy Variables. In P. Bello, M. Guarin, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1485-1490). Austin, TX: Cognitive Science Society. [ abstract ] [ pdf ]
In my spare time, I enjoy exploring any data that I can get my hands on.
I try to post write-ups from these projects on my blog.
Malaysia's 2018 General Election
I founded DataTarik, a Malaysian data-journalism blog providing analysis of Malaysia's 2018 elections.
I created interactive visualizations for Pulang Mengundi, an effort to help match voters who needed/offered rides across Malaysia to vote on May 9, 2018.
2016 US Presidential Election
Since the 2016 US Presidential election season, I've written code to scrape and analyze electoral data.
I've published a few posts about my analyses on my blog.
I've only recently become interested in football, upon realizing how rich the statistics are for this sport.
I've written some code for scraping football statistics, and will post analyses when I have the time.
If you're a football fan and have ideas for some questions that my data can help answer, I'd love to talk!
In the meantime, I use my analyses to inform my fantasy football decisions. (Update, January 2018: I won my league!)
I'm regularly playing, watching, and thinking about soccer (or football, as the world calls it).
I'm currently trying to scrape and compile datasets for some analyses.