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Sai Soundarya Gorthi

Title: 
PhD Student, Information Systems
Sai Soundarya Gorthi
Contact Information
Email address: 
sai.gorthi [at] mail.mcgill.ca
Address: 

Bronfman Building []
1001 rue Sherbrooke Ouest
Montreal, Quebec
Canada
H3A 1G5

Degree(s): 

Oklahoma State University
M.S., Management Information Systems Stillwater, USA Aug 2015 - May 2017

Osmania University
B.Tech., Chemical Engineering Hyderabad, India Aug 2011 - Jun 2015

Area(s): 
Information Systems
Group: 
PhD Student
Research areas: 
Data Science
Digital Platforms
Impact of AI & Analytics on Work
IT in Healthcare
Awards, honours, and fellowships: 

Best Student of Management Information Systems
(Awarded to one outstanding management student – Oklahoma State University)
Gold Medals (2)
(Awarded to one outstanding student – Osmania University)

Conferences: 

Influence of Twitter on Hydroxychloroquine prescription patterns for COVID-19 patients

  • Presented at Hawaii International Conference on System Sciences (ICIS) 2024, Waikiki, USA
    ()
  • Presented at International Conference of Information Systems (ICIS) 2023, Hyderabad, India
    ()
  • Presented at The Conference on Health IT and Analytics (CHITA) 2023, Washington, USA
  • Presented at International Conference of Information Systems (ICIS) 2022, SIG Health Workshop,
    Copenhagen, Denmark

Mobile search advertising: Ad personalization based on device models
Presented at Symposium on Statistical Challenges in Electronic Commerce Research (SCECR) 2020
(Virtual)

  • Presented at Informs 2022, Indianapolis, USA
  • Presented at Montreal Symposium on IS Research (MSISR) 2022, Montreal, Canada
Current research: 

Influence of Twitter on Hydroxychloroquine prescription patterns for COVID-19 patients
Coauthors (Dr. Kartik Ganju, Dr. Alain Pinsonneault)

  • Collected the requirements of the project and designed the project pipeline
  • Using SQL, retrieved the prescription patterns from Insurance claims data hosted in Snowflake
  • Collected Tweets from Twitter API v2 using R
  • Built a pipeline in Python to preprocess tweets and determine their geolocation and stance
  • Employed several econometric panel models to determine the patterns of association

Mobile search advertising: Ad personalization based on device models
Coauthors (Dr. Kartik Ganju, Dr. Alain Pinsonneault)

  • Created a pipeline in Python to emulate different mobile devices using Selenium and BeautifulSoup
  • Collected ads for different iPhone device models through emulation and automation of search using Chrome Driver
  • Analyzed ads to determine if ads are personalized based on device models in mobile search advertising

User Engagement with Digital Platforms - A Scoping Review
Coauthors (Dr. Alain Pinsonneault)

  • Categorized Digital Platforms based on the main focus of interest
  • Reviewed academic literature on user engagement with digital platforms at the platform category level
  • Suggested several opportunities for future research regarding the phenomenon
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