Andrew Rider, PhD

Andrew Rider is a machine learning expert who is passionate about providing reproducible analysis and well tested software. He has professional experience in recommendation systems, time series analysis, clustering, NLP, deep learning, mixture models, AB testing, network analysis, and distributed systems.

Dr. Rider has applied machine learning in several domains, including systems biology, health care, social media, and logistics.

He received a PhD in Computer Science from the University of Notre Dame in 2013, with a dissertation entitled "Data and Network Science for Noisy Heterogeneous Systems." He studied the application of machine learning to domains in which there are simultaneously systematic problems in the data and multiple types of information that are complimentary but cannot be directly compared.

Publications:

• Rider AK, Milenković T, Siwo GH, Pinapati RS, Emrich SJ, Ferdig MT, Chawla NV. Networks' Characteristics Matter for Systems Biology. Network Science (Camb Univ Press). 2014 Aug;2(2):139-161.
• Rider AK, Chawla NV, An Ensemble Topic Model for Sharing Healthcare Data and Predicting Disease Risk. ACM-BCB 2013.
• Rider AK, Reid A. Johnson, Darcy A. Davis, T. Ryan Hoens, Nitesh V. Chawla. Classifier Evaluation with Missing Negative Class Labels. Advances in Intelligent Data Analysis XII Volume 8207 of the series Lecture Notes in Computer Science pp 380-391
• Rider AK, Chawla NV, Emrich SJ. A Survey of Current Integrative Network Algorithms for Systems Biology. Systems Biology, 2013 479-495
• Rider AK, Siwo G, Emrich SJ, Ferdig MT, Chawla NV. A supervised learning approach to the ensemble clustering of genes. Int J Data Min Bioinform. 2011;9(2):199-219.
• Rider AK , Siwo G, Chawla NV, Ferdig M, Emrich SJ, A statistical approach to finding overlooked genetic associations. BMC bioinformatics 11 (1), 1
• Johnson R, Yang Y, Aguilar E, Rider AK, Chawla NV. ALIVE: a Multi-relational Link Prediction Environment for the Healthcare Domain. Emerging Trends in Knowledge Discovery and Data Mining, 2013.
• Meyer P, Siwo G, Zeevi D, Sharon E, Norel R, Segal E, Stolovitzky G, Rider AK, Et. al. Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach. Genome Research, 2013