Hello! I'm Yue
I am a fifth-year doctoral candidate in Operations Management at the Kellogg School of Management in Northwestern University, advised by Professor Jan A. Van Mieghem and Professor Itai Gurvich.
My research generally focuses on people-centric operations. I build empirical models to understand and measure people behavior in online/offline communities, with the goal of developing interventions to support people's collaboration and to improve people's productivity. My work involves first-hand data--both quantitative and qualitative--in the industry of healthcare and analytics. I have been actively collaborating with hospitals, the Fortune-500 e-commerce company and the tech start-up.
News & Upcoming Events
November 5, 2018: I am going to present at 2018 INFORMS Annual Meeting
>> Phoenix Convention Center, Phoenix, Arizona
Talk 1: Balancing Patient Care And Resident Supervision In Emergency Medicine: Resident Effect On Attending Physician Workload Study (with Ernest Wang, Itai Gurvich, Jan A. Van Mieghem)
Schedule: Monday, Nov 5, 11:00 - 11:20 , 126B, North Bldg
Talk 2: Learning By Doing Versus Learning By Viewing: An Empirical Study Of Data Analyst Productivity At eBay On A Collaborative Platform (with Itai Gurvich, Stephanie McReynolds, Debora Seys, Jan A. Van Mieghem)
Schedule: Monday, Nov 5, 12:00 - 12:15 , 126C, North Bldg
November 3 - 7, 2018: I am going to present at the 21st ACM Conference on Computer-Supported Cooperative Work and Social Computing
>> Hyatt Regency Jersey City on the Hudson located in Jersey City, NJ
September 27-28, 2018: I am going to present at the Workshop on Empirical Research in Operations Management,
>> The Wharton School, University of Pennsylvania, Philadelphia, PA
August 8, 2018: Our paper, "Learning by Doing versus Learning by Viewing: An Empirical Study of Data Analyst Productivity on a Collaborative Platform at eBay" was conditionally accepted to CSCW 2018 Second Cycle!
Ph.D. in Operations Management
Kellogg School of Management
Master of Arts in Economics
Weinberg School of Arts and Science
Master in Science in Computer Science
College of Computing
Bachelor of Business Administration
Shanghai Jiao Tong University
Antai College of Economics and Management
Yue Yin, Itai Gurvich, Stephanie McReynolds, Debora Seys, and Jan A. Van Mieghem. 2018. Learning by Doing versus Learning by Viewing: An Empirical Study of Data Analyst Productivity on a Collaborative Platform at eBay. In Proceedings of the ACM on Human-Computer Interaction, Vol. 2, CSCW, Article 193 (November 2018)
We investigate how data-analyst productivity benefits from collaborative platforms that facilitate learning-by-doing (i.e. analysts learning by writing queries on their own) and learning-by-viewing (i.e. analysts learning by viewing queries written by peers). Learning is measured using a behavioral (productivity-improvement) approach. Productivity is measured using the time from creating an empty query to first executing it.
Using a sample of 2,001 data analysts at eBay Inc. who have written 79,797 queries from 2014 to 2018, we find that: 1) learning-by-doing is associated with significant productivity improvement when the analyst’s prior experience focuses on the focally queried database; 2) only learning-by-viewing queries that are authored by analysts with high output rate (average number of queries written per month) is associated with significant improvement in the viewer’s productivity; 3) learning-by-viewing also depends on the social influence of the author of the viewed query, which we measure ‘locally’ based on the number of the author’s direct viewers per month or ‘globally’ based on the how the author’s queries propagate to peers in the overall collaboration network. Combining results 2 and 3, when segmenting analysts based on output rate and ‘local’ social influence, the viewing of queries authored by analysts with high output but low local influence is associated with the largest improvement in the viewer’s productivity; whereas when segmenting based on output rate and ‘global’ social influence, the viewing of queries authored analysts with high output and high global influence is associated with the largest improvement in the viewer’s productivity.
Ernest E. Wang, Yue Yin, Itai Gurvich, et al. Resident Supervision and Patient Care in Emergency Medicine: A Comparative Study of Emergency Attending Physician Time Spent. (Submitted to Academic Emergency Medicine Education and Training )
Objective: To delineate emergency attending physician (EP) time spent on direct and indirect patient care activities in an emergency department (ED) with emergency medicine (EM) residents and in one without residents.
Methods: We performed an observational, time-motion study on 25 EPs, each for two 240-minute observations in an academic community-based ED (with 37,000 annual visits) and two 240-minute observations in a non-academic community ED (with 27,000 annual visits). Mean time-percentages (out of an observation) of main-category activities are reported with 95% confidence intervals for each ED. Minutes spent on various sub-category activities is summarized with mean and standard deviation, as well as with median and interquartile ranges. We report the number of minutes EPs spent per patient on various activities. Wilcoxon two-sample test was performed to check for differences between time spent at two EDs.
Results: In 100 4-hour observations, same 25 EPs executed 34, 358 tasks at two EDs. EPs spent 14.2% (95% CI, 13.6% to 14.9%) of their time working in the academic ED supervising EM residents. Supervision activities included data presentation, treatment development and case discussions that occurred separately from patients and relatives. Such time spent due to the presence of EM residents came from the savings on indirect patient care time without deteriorating direct patient time expenditure. There was an increase in the number of patients that EPs were managing during the observations in the academic ED, but there was no difference in the number of patients that EPs had discharged during the observations in the academic ED from the non-academic ED.
Conclusions: EPs in our study spent 14.2% of their time (8.5 minutes/hour) supervising residents. The time spent supervising residents was largely offset by time savings related to indirect patient care activities, and to a less extent, direct patient care.