Time Line Nate Russell

Senior ML Scientist @ Cellarity

ML for small molecules, transcriptomics and Graphs + Data Engineering for ML, ELN/LIMS, Compound Registry, Etc.

MIT AIDM Conference Best Student Poster Award

For Poster "Synthetic Planning and Library Optimization for Automated Cross Coupling Synthesis Platforms”

Thesis Research

Working on Reaction Prediction, Reaction Optimization, Molecular Attribute Prediction, Combinatorial Chemistry and Automated Synthesis. Working closely with the Burke Lab

Passed Qualifying Exam

Passed oral and written exams testing my knowledge of deep Learning, reinforcement learning and bayesian optimization for drug and material discovery.

CompGen Fellowship Renewed

Proposed research in deep reinforcement learning for drug discovery accepted. Fellowship renewed for 2017-18.

Intern @ IBM Research

AI and Optimization internship under Murray Campbell. I investigated deep reinforcement learning systems for goal oriented dialog and open style question answering. I developed novel algorithms for deep, semi-supervised representation learning on heterogeneous graphs which improved benchmarks in word embedding, language modeling, question answering, link prediction, etc.

Awarded CompGen Fellowship

Proposed research in heterogeneous graph embedding for knowledge representation in genomics was accepted. Fellowship awarded for 2016-17.

Started PhD Program

Thanks to the support of family, friends, co-workers and a research assitantship from Dr. Bryan White and ARI, I began my PhD work with goal of accelerating the sciences through machine learning.

Graduated B.S. in Industrial Engineering

Specialized in Operations Research. I especially enjoyed my coursework in optimization, numerical analysis, simulation, stochastic processes and decision analysis. I was founding president of the UIUC Chapter of INFORMS and public relations chairperson for IIE. Received Departmental service award 4 years in a row for my involvement in the student community. I also won best poster for my senior design project and took 2nd place in the campus wide EOH 2015 for my exhibit "Facial Tracking and Recognition Photo Booth" in the fun category.

Awarded Grant from Alltech for Computational Microbiome Analysis

As an extension of my work with ARI and Alltech, I was provided a tuition waiver for the final semester of my undergraduate degree. I developed novel methods of P >> N Feature selection based on ensemble models, recursive partitioning, and permutation tests that helped scientists identify biologically relevant microbial OTUs, metabolites, genes and proteins.

Research Engineer @ Illinois Applied Research Institute

As a research engineer, both part time and then full time, I prototyped visual analytics platforms for heterogenous network mining, manifold embedding, and microbiome analysis. I led machine learning endeavors on 16 projects, one resulting in new state of the art results in pre-malignant breast cancer prediction during collaboration with the Mayo Clinic. Article I, Article II group photo

Awarded Gianturco Family Foundation Scholarship

Travel scholarship allowed for me to present my research at Mayo Clinic Individualizing Medicine Conference in Rochester, Minn. The conference was a great learning experience for me and I am thankful to the Gianturco Family Foundation for making it possible. Here is an article written about the scholarship.

SPIN Researcher @ National Center for Supercomputing Applications

Designed temporal-spatial classifiers, data storage system and visual analytics platform for John Deere. Enabled biological knowledge discovery with creation of novel random forest variant for P>>N feature selection. Even honored for my work.

Engineering Intern @ Monsanto (2x)

Had 2 internships with the Crop analytics and automation division. I researched and developed 1st generation automated crop & seed sensing platforms for indoors and outdoors. We were mounting hyper-spectral cameras and LIDAR on tractors before it was cool. Applied signal processing and machine learning to multi-sensor systems (NMR, NIR, MRI, CT, Microwave, etc.) Here is a Promotional Video of SeedChipper technology I worked on.

Head Lab Assistant @ Product Design Lab

Taught students about 3D printing, laser scanning, CAD tools, photogrammetry and FEA software. Manage lab assistant team and projects as well as maintain all lab equipment/software. Worked 15-20 hours a week to gain experience and help pay for college.

Timeline