Nick Weir Email & Phone Number

Arlington, Va, Us

San Francisco, California, Us

San Francisco, California, Us

Seattle, Wa, Us

Seattle, Wa, Us

Seattle, Wa, Us

Seattle, Wa, Us

Data Scientist in the ML Specialty Group at Amazon Web Services Worldwide Public Sector Professional Services.

Us

● Senior Data Scientist executing computer vision research projects and software development projects for CosmiQ Works, an In-Q-Tel lab● Led the 4th SpaceNet Challenge for Off-Nadir Building Footprint Detection, including developing a baseline algorithm and writing several blog posts analyzing the dataset and results● Created Solaris, a software stack for performing computer vision/deep learning analysis on overhead imagery

Us

Co-leader of the SpaceNet 4: Off-Nadir Building Footprint Extraction Challenge.● Co-managed challenge operations during the challenge● Performed all solution validation for the top 10 competitors. ● Analyzed competitors' algorithms, wrote analysis blog posts for The DownlinQ (www.medium.com/the-downlinq) and Towards Data Science, and presented conclusions to interested parties within and outside of USG.● Lead author on a research article describing a MultiView Overhead Imagery analysis baseline alongside members of CosmiQ Works and the Intel AI Lab.

San Francisco, Ca, Us

● Built a web application using Python that predicts when dogs will be adopted from pet adoption agencies using data from Petfinder.com listings● Predicted pet adoption time to 70% accuracy using NLP, survival regression methods, and random forests

Cambridge, Massachusetts, Us

● Contributed to software for Deep Learning-based segmentation of microscopy data● Developed R/Shiny interactive visualizations for CRISPR screen experiments: crispr.deniclab.com● Generalized and enhanced modularity of automated fluorescence microscopy analysis, as well as training other scientists' in use of these methods● Projects:→ Interactive data visualizations of high-throughput screen results (see publications and crispr.deniclab.com)→ Guidance of the laboratory subgroup studying Msp1 function (with Dr. Denic)→ Deep learning-based microscopy image segmentation (with the Garner Lab)→ Ported laboratory databases to cloud-based systems using Python/Flask, AWS, and MySQL

Cambridge, Massachusetts, Us

Computational and quantitative analysis‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾● Developed Python and R packages for quantitative image and flow cytometry analysis, now used throughout the lab● Analyzed genetic screen and Next-Gen Sequencing results with Python and R● Became the in-lab expert in high-throughput image analysis and other big data analyses using Python and R● Completed courses in Mathematical Modeling and Mathematics for Biology (Linear Algebra and Probability)● Quantitative methods:→ Regression Analysis: curve fitting, model comparison→ Probability and Statistics→ Support Vector Machines→ Gillespie Simulation→ Computer vision methods: SIFT, edge detection, watershed segmentation, binary morphology→ Data Viz in R and Python● Programming languages:→ Python:scikit-image (contributor) and scikit-learn, pandas, matplotlib, numpy/scipy, others→ R: tidyverse, Shiny, numerous stats packages → git● See www.github.com/nrweir for publicly available analysis packagesBiochemistry and cell biology‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾● Characterized Msp1-mediated protein quality control using quantitative microscopy● Published discoveries in the journals Nature and eLife (see Publications)● Presented research findings at the Keystone Mitochondria Communication Symposium● Extensive bench research experience:→ Confocal fluorescence microscopy→ Next-Gen Sequencing→ Flow cytometry: sample preparation, running, and analysis→ In vitro protein biochemistry: protein purification, activity assays, etc.→ Yeast cell biology: live-cell imaging, organelle isolation, protein purification, and in vitro assays → High-throughput screening: screen preparation, execution, and analysisLeadership and mentoring‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾● Mentored six graduate students and undergraduates in bench research and computational analysis● Independently planned, performed, and analyzed all experiments, guiding projects alongside Dr. Denic

Cambridge, Massachusetts, Us

● Led laboratory sections for Harvard's introductory cell and molecular biology course, MCB 52, and the core physical biochemistry course for undergraduates, MCB 56● Prepared and led interactive review sessions on course material with a focus on achieving high levels of engagement with students through the use of active learning techniques● MCB 56: Co-authored problem sets, exams, and laboratory section materials alongside course faculty and another teaching fellow● Recognized for teaching excellence after receiving perfect scores in undergraduate feedback forms for MCB 56 (see Honors & Awards)

Hanover, Nh, Us

● Characterized cytokinin signaling pathways in Arabidopsis and rice● Published research findings as the co-leading author on a paper in the peer-reviewed journal Plant Physiology (see Publications)● Mentored two undergraduates as they joined the lab

Hanover, Nh, Us

● Studied similarities and differences between plant hormone signaling pathways in different species● Completed an Honors thesis that received high honors and two departmental thesis prizes (see Honors & Awards)● Learned molecular cloning, live-cell imaging, and plant physiology techniques● Established rice as a research model in the Schaller Lab

Doctor Of Philosophy - Phd, Biochemistry

Bachelor Of Arts - Ba, Cell/Cellular And Molecular Biology