Cornelia Paulik

I am an Assistant Professor of Practice at UC Berkeley's School of Information.

My research is at the intersection of health and the environment, employing various geospatial, causal inference, and machine learning (ML) methods.

Before this, I was a Research Scientist at Stanford University and a Postdoctoral Fellow in the Data-Intensive Development Lab at UC Berkeley. I received my doctorate in Applied Economics from UW-Madison.


Email: cornelia.paulik [at] berkeley.edu  /  Office: TBD  /  Curriculum Vitae


News

  • [2024] Excited to lead the Women in MIDS initiative at UC Berkeley!

  • [2023] I am giving a talk on October 27 in the statistics department at UC Davis on Ped-BERT, my latest research.

  • [2023] Excited to give a talk at UC Berkeley's School of Information on Transformers with an application to Electronic Medical Records [slides].

  • [2023] My MIDS students won the Hal Varian award for their Curie.AI Capstone project (jointly advised with A. Todeschini)

  • [2022] My MIDS students won the Hal Varian award for their HealthCAir Capstone project (jointly advised with A. Todeschini)

  • [2022] My 5th-year MIDS students won the Hal Varian award for their Wildfire-RX Capstone project (jointly advised with F. Nugen)

  • [2020 - present] I am teaching Applied Machine Learning for the MS in Data Science program at UC Berkeley.

  • [2020] I have been working on deploying ML models at scale lately. These are my notes on how to set up a Spark cluster using Hadoop/HDFS from scratch.

  • [2019] Excited to teach a new class on Fundamentals of OOP and Data Analytics using Python for the MS in Applied Economics at UW-Madison.


Journal publications

Estimating Health and Economic Impacts of Global Behavior Change During the COVID-19 Pandemic, under review, Science (2024)
J.Tseng, K.C. Coy, C. Paulik (Ilin), A.C. Ewing, T. Chong, S.M. Marks, I. Bolliger, N.M. Gonzalez, K.Bell, A.J. Hakim, S. Hsiang

Utilizing Prenatal Data for Early Detection of Pediatric Health Risks: An Exploratory Approach for Improved Clinical Outcomes, Nature Scientific Reports, volume 14, article number 15350 (2024)
C. Paulik (Ilin)

Improving Nonalcoholic Fatty Liver Disease Classification Performance With Latent Diffusion Models, Nature Scientific Reports, volume 13, article number: 21619 (2023)
R. Hardy*, R. Mitchell*, J. Klepich*, S. Hall*, J. Villareal*, C. Paulik (Ilin)#

Public Mobility Data Enables COVID-19 Forecasting and Management at Local and Global Scales, Nature Scientific Reports, volume 11, article number: 13531 (2021)
C. Paulik (Ilin), Sebastien Annan-Phan, Xiao Hui Tai, Shikhar Mehra, S. Hsiang, J. Blumenstock

Competition, Price Dispersion and Capacity Constraints: The Case of the U.S. Corn Seed Industry, European Review of Agricultural Economics, volume 1 (2021)
C. Paulik (Ilin), G. Shi


*=student co-author, #=senior author
Research (in progress)

The Aerial History Project and the Mapcasting Project, joint with the Global Policy Lab at Stanford University.

Contribution to manuscripts and posters

Longitudinal Matching. A Method for Generating Comparable Samples of Treatment and Treatment-Naive Patients with Progressive Conditions.
K. Cook, O. Ali, D. Gupta, C. Ilin, D. Holmqvist, D. Lee, E. Tuttle, P. Bradt, 2018

Patient Quality of Life and Benefits of Leptin Replacement Therapy (LRT) in Generalized and Partial Lipodystrophy.
study funded by Aegerion Pharmaceuticals Inc., 2018

Effect of Leptin Replacement Therapy (LRT) on Survival and Disease Progression in Generalized and Partial Lipodystrophy.
study funded by Aegerion Pharmaceuticals Inc., 2018


Litigation consulting

Analysis of claims data related to mental health and substance abuse disorders.
Des Roches, et. al v. Blue Shield and Magellan

Analysis of claims data related to emergency department orthopaedic services.
Confidential v. Blue Shield


TAs and Mentees

Current TAs

  • Matthew Holmes (UC Berkeley)
  • Thomas Lai (UC Berkeley)
  • Stone Jiang (UC Berkeley)

Past Mentees:

  • Romain Hardi (UC Berkeley, incoming PhD in Bioinformatics student at Harvard)
  • Nicole Lin (Stanford)
  • Nathanel Jo (Stanford)
  • Liza Peckham (UW Madison)
  • Jingyi Tong (UW Madison)
  • Yuxuan Li (UW Madison)

Teaching

DATASCI207: Applied Machine Learning, UC Berkeley: Summer 2024, Fall 2023, Summer 2023, Spring 2023, Fall 2022, Summer 2022, Spring 2022, Fall 2021, Summer 2021, Spring 2021, Fall 2020, Summer 2020

DATASCI210: Capstone, UC Berkeley

AAE875: Fundamentals of OOP and Data Analytics using Python, UW-Madison: Summer 2019

AAE724: Practicum for Applied Economists, UW-Madison, Fall 2019