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Andrew Rider, PhD

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San Francisco, California, US

About 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.
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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
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Our Services (2)


ic

Machine Learning and AI Solutions

Price on request

We will develop a machine learning model for your problem. You will receive:

  • An analysis of your data with visualizations exploring the relationships between the variables and more.
  • A thorough evaluation of the model and at least one baseline model trained on your data.
  • An implementation of the model with all code... Show more »

We will develop a machine learning model for your problem. You will receive:

  • An analysis of your data with visualizations exploring the relationships between the variables and more.
  • A thorough evaluation of the model and at least one baseline model trained on your data.
  • An implementation of the model with all code necessary to apply it to your data set or any similar data sets.
  • Unit tests -- all of our software is well tested.
  • A script to install and set up all of the necessary software.

Pricing:
Small data sets (less than 20 variables and 10,000 observations) - $1250
Large data sets - price on request
Custom projects - price on request

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ic

Computational Modeling

Price on request
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Andrew Rider

Machine learning scientist

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