Mike Huang Email & Phone Number

Seattle, WA, US

Seattle, WA, US

• Developed image processing techniques for registering and visualizing a human macaque brain atlas in a cloud-based WebGL viewer.
• Designed and implemented software to process spatial transcriptomics and two-photon microscopy datasets
• Performed data ETL to package and serve our large-scale open source datasets
• Developed production level API software that’s released open source
• Scaled transcriptomics analysis pipeline on AWS cloud

Boston, MA, US

• Implemented an NLP generative model to find novel analogs of drugs
• Developed an end-to-end pipeline from data curation to post-hoc analysis

Singapore, SG

• Commercialization of spatial transcriptomics imaging technology with an industry partner, Applied Materials
• Developed a machine learning pipeline for the analysis of spatial transcriptomics imaging data, led to patent https://patents.google.com/patent/US20220375546A1/en
• Developed image processing techniques including segmentation and stitching.
• Worked with a team of biologists and engineers to devise QC metrics on imaging data

• Built a data pipeline to detect lung nodules from CT scan images and predict its probability of malignancy https://github.com/mikejhuang/LungNoduleDetectionClassification
• Achieved similar recall and precision to trained radiologists
• Implemented a data pipeline to predict phage protein function using NLP techniques (Word2Vec) https://github.com/mikejhuang/PhageProtVec
• Completed Georgia Tech Machine Learning courses hosted by Udacity consisting of projects relating to supervised learning, unsupervised learning, and reinforcement learning

Singapore, SG

• Developed software for the analysis of Illumina NGS data in a CLIA/CAP certified laboratory
• Wrote production level code in Python to streamline laboratory database software
• Mined, processed, and performed NLP analysis on journal metadata to find the most popular topics with R

Assisted students on brain teaser Python algorithms with constructive feedback (worked on Coursera data science specialization in tandem)

Los Angeles, CA, US

• Led a project to integrate, validate, and optimize multi-scale models from synapses to neurons
• Multi-objective evolutionary optimization of a high dimensional model to capture the system's nonlinear dynamics.

Studied the mechanisms of synaptic plasticity regarding learning and memory. Developed drug treatments for FragileX mental retardation. Conducted a broad literature review of the mechanisms of memory consolidation and presented my findings to the lab. - Breeding, Handling and Experimentation with wild-type (WT) and knock-out (KO) Mouse Models- Behavior.

Master'S Degree, Biomedical/Medical Engineering

Machine Learning Engineering

Data Science Specialization

Bs, Neuroscience