In this episode I talk with Srikar Katta. Srikar is a PhD researcher focused on Computer Science at Duke University. During the discussion we review methods from Causal Inference, a field closely related to statistics, Srikar goes over his papers where he studies data from wearable devices and political polarization using methods from Causal Inference, we discuss how social media affects our perceptions and we talk about board games and books Srikar has been getting into. I hope you enjoy!

PAPERS DISCUSSED:

Interpretable Causal Inference for Analyzing Wearable,Sensor, and Distributional Data: https://arxiv.org/abs/2312.10569

A Design-based Solution for Causal Inference with Text: Cana Language Model Be Too Large?: https://arxiv.org/abs/2510.08758

Political Polarization Dataset on GitHub: https://github.com/kattasa/text_as_treatment_repository

ARTICLES:

Neuroeconomics Laboratory: https://sites.temple.edu/neuroeconlab/

Automated Recognition of Robotic Manipulation Failures inHigh-throughput Biodosimetry Tool (blood centrifuge): https://pmc.ncbi.nlm.nih.gov/articles/PMC3339769/

The principled control of false positives in neuroimaging(dead salmon paper): https://pmc.ncbi.nlm.nih.gov/articles/PMC2799957/

What is Causal Inference? Why Do We Care? Can We Do It? fromPurdue University: https://www.stat.purdue.edu/~sabbaghi/teaching/DTSS/Causal%20Epiphanies.html

“A calculated risk”: the Salk polio vaccine field trials of1954: https://pmc.ncbi.nlm.nih.gov/articles/PMC1114166/

Bag-of-words models: https://www.cs.cornell.edu/courses/cs6670/2009fa/lectures/lec16_bag_of_words.pdf

Facebook says it dismantles disinformation network tied toIran's state media: https://www.reuters.com/article/idUSKBN22H2DJ

BOOKS:

The Most Human Human by Brian Christian: https://www.amazon.com/dp/0385533063

Mistborn by Brandon Sanderson: https://www.amazon.com/dp/076531178X

CONNECT:

LinkedIn:https://www.linkedin.com/in/adrian-dolinay-frm-96a289106/

GitHub: https://github.com/ad17171717 X:https://twitter.com/DolinayG

Odysee: https://odysee.com/@adriandolinay:0

Medium: https://medium.com/@adriandolinay

PODCAST:

Apple Podcasts:https://podcasts.apple.com/us/podcast/the-aspiring-stem-geek/id1765996824

Audible:https://www.audible.com/podcast/The-Aspiring-STEM-Geek/B0DC73S9SN?source_code=ASSGB149080119000H&share_location=pdp

iHeart Radio: https://iheart.com/podcast/202676097/

Spotify:https://open.spotify.com/show/60dPNJbDPaPw7ru8g5btxV?si=26e034e416f446d8

|-Video Chapters-|

0:00 – Intro
1:52 – Getting into STEM
3:37 – Srikar dual majoring in math and computer science
6:52 – Attending graduate level courses as an undergrad
13:12 – Srikar starting his PhD in Comp Sci at Duke University
15:07 – Having two PhD advisors
17:42 – Defining Causal Inference
28:19 – Srikar’s paper on Continuous Glucose Monitoring devices for Type Idiabetics
47:27 – Srikar’s paper on political polarization
1:01:48 – Sometimes the simpler model is better
1:06:14 – Are we more politically polarized relative to different periods intime?
1:17:08 – Preferred programming languages
1:19:56 – Board games
1:21:20 – Book recommendations
1:31:00 – Conclusion