Data Analyst

Vladyslav (Vlad) Oles

§ vlad-oles ï vlad-oles # ****.****@******.** H 509-***-****

An experienced data analyst with strong computational skills, expertise in statistics and machine learning, and a corporate background. Author of a Python library for shape matching, a Scikit-TDA module, and an MPI-based package for Boolean network analysis. Into electronic music and open science. Tools

Fluent in Python (scikit-learn, scikit-tda, networkx, pyspark, dask, mpi4py, pandas, seaborn, mat- plotlib), R (dplyr, tidyr, ggplot2, igraph), SQL, and LATEX Familiar with C/C++, MATLAB, Torch, TensorFlow, Spark, NoSQL Experience

(US employment authorization was pending) Feb 2023 – May 2023 Postdoc in data analytics @ Oak Ridge National Laboratory Oct 2020 – Feb 2023

• Performed root cause analysis of GPU memory failures by applying survival analysis, interpretable machine learning, and hypothesis testing to 20TB multimodal supercomputer operational data

(Python + Spark + scipy/scikit-learn/seaborn)

• Formulated the problem of learning carcinogenic mutations in terms of community detection in bi- partite graphs, and developed a parameter-free algorithm for solving it (Python + networkx)

• Prototyped a new GNN architecture by combining multi-head and multi-hop attention mechanisms

(Python + Torch)

• Benchmarked world’s fastest supercomputer on solving a linear system (C++/CUDA) Data scientist @ Washington State University Mar 2020 – Aug 2020

• Analyzed 450 GB of geospatial data to detect climate anomalies (R) Research intern @ Los Alamos National Laboratory Jun 2017 – Aug 2017

• Developed algorithm for shape analysis on unweighted graphs and applied it to identify anomalies in 73GB corporate LAN traffic dataset (Python + networkx) Research Analyst (part-time) @ Flex Ltd Jul 2013 – Aug 2019

• Designed a convolutional neural network for invoice classification (Python + TensorFlow)

• Visualized company performance data to inform executive decisions (Python + seaborn) Software Engineer @ Flex Ltd Mar 2007 – Jun 2013

• Developed and optimized algorithms on data structures and database queries (SQL + C) Education

PhD in mathematics @ Washington State University Aug 2014 – Dec 2019 MS in applied mathematics @ Kyiv Polytechnic Institute Sep 2007 – Jun 2009 BS in applied mathematics @ Kyiv Polytechnic Institute Sep 2003 – Jun 2007 Workshops

Big data @ The Data Incubator Nov 2018

Representations of high-dimensional data @ Mathematical Studies Research Institute Jul 2018 Selected publications

Oles, V. et al. (2023). BiGPICC: a graph-based approach to identifying carcinogenic gene combinations from mutation data. Submitted.

Oles, V. et al. (2023). Understanding GPU memory errors at extreme scale: the Summit case study. Submitted.

Fiedler, L. et al. (2022). Electronic Structure Machine Learning Surrogates without Training. Machine Learning: Science and Technology.

Shin, W. et al. (2021). Revealing power, energy and thermal dynamics of a 200PF pre-exascale super- computer. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis.

Oles, V. et al. (2020). Efficient estimation of a Gromov–Hausdorff distance between unweighted graphs. Submitted.

Oles, V. et al. (2020). BoolSi: a tool for distributed simulations and analysis of Boolean networks. Journal of Open Research Software.

Talks

iSciMath Seminar @ Washington State University Feb 2022 Session on Combinatorial Approaches to Topological Structures @ Joint Math. Meetings Jan 2021 Data Science and Image Analysis Conference of the Pacific Northwest @ Wash. State Univ. Feb 2020 Analysis Seminar @ Washington State University Nov 2018 T Division Lightning Talks @ Los Alamos National Laboratory Aug 2017 American Mathematical Society Fall Western Sectional Meeting @ California State Univ. Oct 2015 Honors

Director’s Award (Team Accomplishment category) @ Oak Ridge National Laboratory Nov 2022 Team Award (Research Accomplishment category) @ Oak Ridge National Laboratory Nov 2022 Team Award (Distinguished Innovation category) @ Oak Ridge National Laboratory Nov 2022 Best Paper Award @ SuperComputing’21 conference Sep 2021 MITx Philosophy Award Sep 2020

Fellowship @ The Data Incubator Nov 2018

Sidney G. Hacker Graduate Research Math. Scholarship @ Washington State University Apr 2017

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