Department of Electrical Engineering and Computer Science
Tickle College of Engineering
University of Tennessee
Github: rusheniii
Orcid:
0000-0002-5632-5723
Email: erush3 "at" vols.utk.edu
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PhD Student, Computer Science Department of Electrical Engineering and Computer Science Tickle College of Engineering University of Tennessee Github: rusheniii Email: erush3 "at" vols.utk.edu |
I have a passion for developing high quality software that utilize machine learning. I help build efficient, reliable, and scalable systems for moving, managing, analyzing, and modelling big data. I have experience with DevOps and DataOps taking software and statistical models through their entire life cycle. I work well in an environment with agile development practices and continuous integration. I am used to working in a secure environment with strict security guidelines.
Experience working with interdisciplinary groups of researchers to deliver high quality scientific software on-time.
Experience developing machine learning applications using multi-modal data: text, DNA, and structured electronic health records
Good oral and written communication skills
Self-starter that is motivated to excel in data engineering
I am able to handle the five V's of big data. I have training and experience in technologies that support my engineering role at the intersection of big data and HPC in a modern data center.
Software Development Engineer June 2022 to present
Document management backend for ship.amazon.cn
Cross-border machine learning applications.
Cross-border trade compliance applications.
Data Engineer Aug. 2017 to June 2022
Led the Scientific Computing Team for MVP-CHAMPION
Member of the Data Management Team for MVP-CHAMPION
Collaborated and published papers with world-class data scientists
Developed Clinical Pathways framework for Antidepressant Medication Management
Deployed proof-of-concept system enabling DataOps in PHI enclave
Intern May 2016 to Aug 2017
Learned aspects of data management for scientific data
Modernized and automated streaming data pipeline for big atmospheric data
Modernized visualization of historic atmospheric data
Ph.D. Candidate, Computer Science, Aug. 2020 - Present
Ph.D. Candidate, Computer Science, Aug. 2015 - Aug 2016
M.S., Computer Science, Aug. 2013 - Aug. 2015
B.A., Liberal Studies, Aug. 2007 - May 2013
* Concentration in Mathematics
2014 to 2016 - Graduate Teaching Assistant for Operating Systems
2014 - Global Teaching Assistant for Edx: Software as a Service
University of Louisville Fellowship Aug. 2015
University of Louisville Trustee’s Scholar, Aug. 2007
Jun Wen et al. "Multimodal representation learning for predicting molecule-disease relations". In: Bioinformatics 10.1093/bioinformatics/btad085
Doudou Zhou et al. "Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonizationâ€. In: Journal of Biomedical Informatics 10.1038/s41746-021-00519-z
Chuan Hong et al. "Clinical knowledge extraction via sparse embedding regression (Keser) with multi-center large scale electronic health record dataâ€. en. In: npj Digital Medicine 4.1 (Oct. 2021), pp. 1–11. ISSN: 2398-6352. DOI: 10.1038/s41746-021-00519-z
Everett Rush et al. "JSONize: A Scalable Machine Learning Pipeline to Model Medical Notes as Semi-structured Documents".
In: 2020 AMIA Technology Summit, Houston, TX, USA
Kathryn E Knight et al. "Standardized Architecture for a Mega-Biobank Phenomic Library: The Million Veteran Program (MVP)" in: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science 2020 (2020), 326—334. ISSN: 2153-4063. URL: https://europepmc.org/articles/PMC7233040
Everett Rush et al. "Characterizing Sub-Cohorts via Data Normalization and Representation Learning." In: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). 2020, pp. 173–176. DOI: 10.1109/CBMS49503.2020.00040
Benjamin Mayer et al. "Evaluating Text Analytic Frameworks for Mental Health Surveillance". In: 34th IEEE International Conference on Data Engineering Workshops, ICDE Workshops 2018, Paris, France, April 16-20, 2018. 2018, pp. 39–47. DOI: 10 . 1109/ICDEW.2018.00014. URL: https://doi.org/10.1109/ICDEW.2018.00014
E. Tomes, E. N. Rush, and N. Altiparmak. "Towards Adaptive Parallel Storage Systems". In: IEEE Transactions on Computers
67.12 (2018), pp. 1840–1848
Everett Neil Rush et al. "Dynamic Data Layout Optimization for High Performance Parallel I/O". in: 23rd IEEE International Conference on High Performance Computing, HiPC 2016, Hyderabad, India, December 19-22, 2016. 2016, pp. 132–141. DOI: 10.1109/HiPC.2016.024
Everett Neil Rush and Nihat Altiparmak. "Exploiting Replication for Energy Efficiency of Heterogeneous Storage Systems". In:
24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MAS-
COTS 2016, London, United Kingdom, September 19-21, 2016. 2016, pp. 79–84
Ranjeet Devarakonda et al. "Next-gen tools for big scientific data: ARM data center example". In: 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016. 2016, pp. 3968–3970. DOI: 10 . 1109 / BigData.2016.7841078
Giri Prakash et al. "HPC infrastructure to support the next-generation ARM facility data operations". In: 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016. 2016, pp. 4026–4028. DOI: 10 . 1109 / BigData.2016.7841098