Sotabase

Career

· Machine Learning Scientist, Harbinger Health2023–
· Research Intern, Verily2022–
· Research Intern, Google Research2021–
· Ph.D. Student, Computer Science, Harvard University2019–2023
· Research Intern, Microsoft Research India2019–
· Intern, Spatial.AI2018–
· Teaching Assistant, University of Southern California2018–
· Application Developer Intern, PNC2017–
· Undergraduate Researcher (Pelotonia Cancer Research Fellow), The Ohio State University2017–2018
· Independent Database Developer, Delaware City Bus Company2015–
· Bachelor's degree, The Ohio State University2014–2018

Publications (48)

Envisioning Communities: A Participatory Approach Towards AI for Social Good
AAAI/ACM Conference on AI, Ethics, and Society · 2021
107
cited
Collapsing Bandits and Their Application to Public Health Interventions
Neural Information Processing Systems · 2020
73
cited
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Knowledge Discovery and Data Mining · 2019
60
cited
Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
Proceedings of the National Academy of Sciences of the United States of America · 2020
58
cited
The Role of Age Distribution and Family Structure on COVID-19 Dynamics: A Preliminary Modeling Assessment for Hubei and Lombardy
2020
46
cited
Q-Learning Lagrange Policies for Multi-Action Restless Bandits
Knowledge Discovery and Data Mining · 2021
39
cited
Beyond "To Act or Not to Act": Fast Lagrangian Approaches to General Multi-Action Restless Bandits
Adaptive Agents and Multi-Agent Systems · 2021
34
cited
Genome-wide DNA hypermethylation opposes healing in patients with chronic wounds by impairing epithelial-mesenchymal transition
Journal of Clinical Investigation · 2022
29
cited
Identification of a Recurrent LMO7–BRAF Fusion in Papillary Thyroid Carcinoma
Thyroid · 2018
23
cited
Evaluating COVID-19 Lockdown Policies For India: A Preliminary Modeling Assessment for Individual States
2020
13
cited
Learning to Detect Heavy Drinking Episodes Using Smartphone Accelerometer Data
KHD@IJCAI · 2019
12
cited
Networked Restless Multi-Armed Bandits for Mobile Interventions
Adaptive Agents and Multi-Agent Systems · 2022
12
cited
Evaluating COVID-19 Lockdown and Business-Sector-Specific Reopening Policies for Three US States
2020
8
cited
Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth Program
AAAI Conference on Artificial Intelligence · 2023
8
cited
Equitable Restless Multi-Armed Bandits: A General Framework Inspired By Digital Health
arXiv.org · 2023
7
cited
Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcare
International Joint Conference on Artificial Intelligence · 2023
7
cited
Flexible Budgets in Restless Bandits: A Primal-Dual Algorithm for Efficient Budget Allocation
AAAI Conference on Artificial Intelligence · 2023
6
cited
Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learning
Conference on Uncertainty in Artificial Intelligence · 2021
6
cited
A STUDY OF SIGNIFICANT CHEMICAL CHANGES IN THE BLOOD COINCIDENT WITH MALIGNANT TUMORS
1921
5
cited
Evaluating COVID-19 Lockdown and Reopening Scenarios For Georgia, Florida, and Mississippi
2020
5
cited
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Jackson Killian | Researcher Profile | Sotabase | Sotabase