Ph.D. in Operations Management, The University of Texas at Austin, Expected 2022
References: Yannis Stamatopoulos (advisor), Ashish Agarwal, Alex Dimakis
M.S. in Operations Research, Columbia University, 2016
B.S. in Operations Research, Columbia University, 2015
Research (IoT, Retail Operations, Data Science)
(1) “Promotional Inventory Displays: An Empirical Analysis Using IoT Data.” with Ashish Agarwal, and Ioannis (Yannis) Stamatopoulos. Reject and resubmit. Management Science.
Abstract: We use internet-of-things (IoT)-generated data on the real-time location of about 15 thousand displays in about 5 thousand stores of a Fortune 500 retailer, paired with the stores’ point-of-sale (POS) data between September 2017 and March 2018, to measure the operational execution and effectiveness of promotional inventory display campaigns. We find that campaigns are poorly executed: 29 percent of displays never made it to a store’s floor, and those that did only spent 62 percent of the campaign there. We also find that poor execution deprives targeted products of substantial sales: placing a display on the floor on an arbitrary week increases the targeted products’ sales by 7.3 percent, and placing it on the floor on a campaign week boosts sales by another 2.3 percent. Finally, we project that stores would decrease targeted products’ dollar sales during campaign weeks by 3.1 percent if they discontinued display campaigns as currently executed, and they could increase these products’ revenues during campaign weeks by up to 6.9 percent by improving display campaign execution.
Abstract: Eliminating excessive energy consumption can result in significant financial savings and environmental benefits. However, the effectiveness of real-time feedback in correcting excess usage has not been investigated for the commercial sector. To answer this question, we leverage detailed data on electricity consumption and abnormal consumption alerts in 14 brick and mortar stores of two major retailers to identify how managers react to real-time feedback and whether these effects persist over time. Our findings show that the alerts correct high consumption, but the outcomes have limited duration. Moreover, we observe that the reactivity of managers to the feedback decreases as the frequency and the number of messages sent increase. Our findings provide valuable insights to energy platforms and policymakers for better design of energy consumption feedback.
(3) “Prediction Models for Promotional Inventory Displays Based on IoT Data.” with Ashish Agarwal, Alexandros G. Dimakis, and Ioannis (Yannis) Stamatopoulos. Work in Progress.
Teaching (as Instructor)
OM 335: Operations Management, Fall 2019
Undergraduate Core Course in Operations Management for Upper-Division Students
Student Evaluation: 4.6/5.0
INFORMS Annual Meeting, Anaheim, CA, October 2021
CIST, Newport Beach, CA, October 2021
31st POMS Annual Meeting, Virtual, May 2021
INFORMS Annual Meeting, Virtual, 2020
INFORMS Annual Meeting, Seattle, WA, October 2019
30th POMS Annual Meeting, Washington, DC, May 2019
29th POMS Annual Meeting, Houston, TX, May 2018
In my spare time, I play the piano, compose piano sheets, play chess, try out different restaurants, and travel. For a sample of the music I compose, scroll down and click play.