Cornelia Ilin

I am a Faculty in AI/ML at UC Berkeley's School of Information.

My research is at the intersection of health and environment, employing a wide variety of geospatial, causal inference, and ML/NLP methods.

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

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

News

[2022] Coming soon! My paper on "Ped-BERT: Early Detection of Disease for Pediatric Care".

[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 setup 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, Nature (2021)
J.Tseng, K.C. Coy, C. Ilin, A.C. Ewing, T. Chong, S.M. Marks, I. Bolliger, N.M. Gonzalez, K.Bell, A.J. Hakim, S. Hsiang

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

Evolution of Learning in Technology Adoption: The case of the U.S. Soybean Seed Industry, under review, PLOS One (2021)
C. Ilin, G. Shi

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

Journal publications (in preparation)

The Role of Birth and Contemporaneous Pollution Exposure on Health Outcomes.
C. Ilin, D. Phaneuf, 2019

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

Design, implementation and analysis of quantitative surveys related to patent infringment.
Confidential v. Google, Confidential v. Apple, Confidential v. FTC

Students and Mentees

Past Mentees:

Nicole Lin (Stanford)
Nathanel Jo (Stanford)

Past Teaching Assistants:

Adam Theising (UW Madison)

Past Independent Study MS Students:

Liza Peckham (UW Madison)

Past Project Assistants:

Jingyi Tong (UW Madison)
Yuxuan Li (UW Madison)

Teaching

DATASCI W207: Applied Machine Learning, UC Berkeley: Fall 2022, Summer 2022, Spring 2022, Fall 2021, Summer 2021, Spring 2021, Fall 2020, Summer 2020

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

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