Erfan Loghmani

I am a fourth-year Quantitative Marketing Ph.D. student at the University of Washington's Foster School of Business. My research focuses on developing novel methods to improve and understand the effects of marketing activities, with applications in online platforms and the healthcare domain. By adapting and enhancing methodologies from causal inference, adaptive experimentation, and language models, I aim to provide policymakers and platform designers with more effective tools.

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Academia

TOPS Presentation

TOPS Presentation

Last week I had the opportunity to present our work, "Investigating the Impact of Advertising on Smoking Cessation: The Role of Direct-to-Consumer Prescription Drug Advertising," co-authored with Ali Goli, at the Tobacco Online Policy Seminar (TOPS). It was a great experience engaging with a multidisciplinary audience and discussing …

From Frustration to Fast: Using Ray for Parallel Computing on a Single Machine or a Cluster

If you're someone who works with data and runs computationally-intensive tasks, you know that multiprocessing can be a game changer. It can speed up your work significantly and save you precious time. I previously used the multiprocessing Python package for running my jobs concurrently, but that didn’t always go …

M.Sc. seminar

Representation Learning on Dynamic Graphs

Abstract: Graphs are a common language in modeling several problems, from social and economic networks to interactions in cells and brain neurons. According to the availability of an enormous amount of data from graphs, Machine Learning algorithms gained lots of attention in this area. But …

ICTP workshop

Last week I had the chance to attend the ICTP workshop on science of data science.

From the very beginning of landing at Venice to the last moments of my visit, there was lots of learning for me. Not just from the lectures, but from all the people I've met …

My B.Sc. project

Profiling Researchers Based on Features Extracted from Articles and Citations

A researcher may be evaluated based on several measures such as the total number of published papers, number of citations, and her/his h-index. These measures may not reflect the real quality of researchers as many self citations and citing …