Chris Cotter Email & Phone Number

St. Louis, Mo, Us

Greater St. Louis

Greater St. Louis

Greater St. Louis Area

Applying tools from computer science, machine learning, and biology to data science problems.

Athens, Georgia Area

Utilize deep learning, software engineering, and data science approaches to create new tools to analyze complex, heterogeneous data sets, and make these tools available to a broad audience. Projects include:Full-stack design and implementation of the back (Python, SQL, REST) and front (Vue.js) ends of a web platform to analyze data sets at scale using an easy-to-use interface.-- Management of a team of two UI/UX designers.-- Designed APIs to facilitate interactions between compute clusters, web servers, and data management systems. Establish collaborations with other laboratories to utilize machine learning approaches to enable their data-intensive projects. For example coding and training an augmented U-Net neural network architecture to segment microscopy images. -- Converted already available data into a training data set, eliminating need to manually generate training data. -- Network is 25x faster than manual quantification, reducing data set quantification time by months. -- Features extracted from the neural network segmentation highly correlate (r>0.99) with manual methods.Develop unsupervised deep neural networks that extract traits encompassing the biologically relevant variation within a data set, translate between genotypic and phenotypic data, and predict new genotype-phenotype combinations.

Athens, Georgia Area

Utilized deep learning, clustering, and computer vision to quantify and annotate a bacterial model of multi-cellular development. Projects include:Feature extraction and clustering of time-lapse microscopy images: Develop a mutual information theory centric approach to train convolutional neural networks to extract global features from a data set of highly variable time-lapse movies of bacterial development.Utilize computational techniques developed during my Ph.D. thesis (image quantification, multiple object tracking, nearest-neighbor regression, data-smoothing and annotation, and modeling) to explore biological mechanisms underlying the phenotypes of Myxococcus xanthus developmental mutants.

Athens, Georgia Area

Combined computer science, statistics, and biological science to turn high-dimensional and noisy experimental data into understanding about biological systems. Projects include:Designed a mutual information centric training approach able to distinguish salient variation from noise using semi-supervised neural networks. Currently using networks to extract features for clustering of approximately 1000 time-lapse movies from over 250 overlapping and noisy groups. -- Performed data acquisition, normalization, and augmentation for neural network training. -- Work performed in Python, utilizing packages such as Jupyter Notebooks, NumPy, PyTorch, and scikit-learn. -- Implemented techniques from convolutional adversarial networks and variational autoencoders.Extracted almost 40 quantitative features from time-lapse fluorescent microscopy data and performed model driven hypothesis testing to understand cell coordination in a bacterial model of multi-cellular patterning. -- Developed custom image segmentation and multiple object tracking algorithms. -- Utilized unsupervised machine learning techniques, such as nearest neighbor regression and ReliefF. -- Denoised and categorized highly variable cell trajectories using extended Kalman filters. -- Tested identified-cell-behavior predictors using in silico simulations directly driven by experimental data. -- Created advanced visualizations for presentations and publication (example at: sciencesundries.com/publications). -- Performed strain construction (cloning, PCR, sequencing, etc.) and time-lapse fluorescent microscopy. Noted Outcomeo Publication in high-impact journal: Cotter, Schüttler, Igoshin, & Shimkets. Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development. PNAS. 2017.

Rochester, Ny

St. Marys, Pa

Identified and implemented a website front end (HTML/CCS/JavaScript) and backend framework (PHP/MySQL) that addressed client’s needs and facilitated rapid website development. Outcomes: • Website in use by the foundation for the past 6 years.• Utilized a website back end that allowed changes without computer programming knowledge.• Implemented a framework to generate usage statistics for annual report to board members

Athens, Georgia Area

Inferred metabolic state of bacterial species in chicken gut microbiome samples from RNA sequencing data

Doctor Of Philosophy - Phd, Microbiology (Focus On Applied Computational Methods)

Bachelor Of Science (Bs), Bioinformatics

Activities and Societies: RIT Bioinformatics Journal Club, Founder