I'm Derek Onken, a PhD Candidate in the Computer Science and Informatics Program at Emory University. I focus on data-intensive problems, ranging from the mathematical theory to implementation, especially for application to problems with biological motivation.
(Such approaches include the following buzzwords: machine learning, deep learning, neural networks, big data, statistical analysis, GPUs, numerical optimization, continuous normalizing flows)
Doctor of Philosophy - Emory University (2016-Present)
Computer Science & Informatics track
Master of Science - Emory University (2019)
Bachelor of Science - University of Georgia (2015)
Majors: Mathematics and Computer Science
Minors: Physics and Classical Culture
PDE-based Machine Learning with Lars Ruthotto . (2018 - present)
Applying knowledge of optimizers and partial differential equation solvers to machine learning architectures (also known as neural differential equations). More specifically, we explore higher-order schemes, bound constraints, and the Discretize-Optimize approach (public code). We also are interested in developing methods for lowering computational cost of continuous normalizing flows.
Parkinson's Disease Telemonitoring and Voice Analysis via Mobile App with Eugene Agichtein as part of his IRLAB. (2017)
Collecting and analyzing voice data, touch pressure, and rest tremor to detect Parkinson's disease symptoms via remote patient monitoring. Building machine learning classifier using motor and vocal features extracted from these patients.
Using CDR data from H1N1 outbreak to predict future disease outbreaks with Ymir Vigfusson (2016-2019)
Our dataset contians cellphone data from the H1N1 outbreak in 2009-2010 and linked health data. We develop a classifier to determine/predict sickness based on human behavior changes around Date of Diagnosis. Motivation: give health officials a more real-time and accurate estimation of sick individuals as an outbreak is occuring.
Lunar study with Juan B. Gutierrez in UGA's Biomathematics Research Group. (2014-2016)
Analysis of 56 million natality records and sex ratio correlations.
Comparison of Parallelization Methods with Juan B. Gutierrez in UGA's Biomathematics Research Group. (2014)
Exploration of MPI, CUDA, and OpenCL. Application of MPI to Geneset Enrichment Analysis (GSEA).
PreprintsD Onken, S Wu Fung, X Li, L Ruthotto. OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport. 2020. preprint D Onken and L Ruthotto. Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows. 2020. preprint
PresentationsSIAM Annual Meeting, Jul 2020, poster SIAM Mathematics of Data Science, Jun 2020, slides Deep Learning in Medical Applications Workshop at Institute for Pure and Applied Mathematics (IPAM), Jan 2020, poster Emory Scientific Computing Seminar, Apr 2019, slides Georgia Scientific Computing Symposium, Feb 2019, poster Amazon Graduate Research Symposium, Oct 2017, poster
Summer 2020: Graduate Data Science Intern for United Health Group
Summer 2019: Graduate Data Science Intern for United Health Group
Summer 2018: High Performance Computing Intern for Air Force Research Labs
Spring 2018: TA for Dr. Li Xiong's Data Mining (CS378)
Fall 2017: Lab Instructor for Dr. Lars Ruthotto's Numerical Analysis (MATH315)
Spring 2017: TA for Dr. Michele Benzi's Numerical Analysis (MATH315)
Fall 2016: TA for Dr. Davide Fossati's Intro to Java (CS170)
400 Dowman Drive
Department of Mathematics and Computer Science
Atlanta, GA 30322
donken [at] emory [dot] edu