Provide technical expertise and statistical perspectives as a senior engineer in the Industry 4.0 team at Watlow Electric. My daily work may involve working with stakeholders to solve complex industrial problems using machine learning or other statistical solutions, orchestrating, training and refining on and off-prem models for a variety of tasks including time-series forecasting, LLM knowledge and instruct agents, or predictive models for Watlow's next gen industrial heat applications, or engineering ETL and dashboarding applications for IOT and other workflows. In my spare time I work to develop next-gen automated solutions for complex industrial problems using machine learning and software engineering.

Below are key technical ownership and support roles I performed towards research and development of a next-generation nano grid system at YouSolar. Product owner and lead engineer of the Cirrus monitoring system, a OTA cloud monitoring system that allows complex user querying, dashboarding, and alert monitoring for our clients.Provide technical expertise and leadership for infrastructure and operations, including leading PR and git branch reviews with senior engineers.Design key data streaming and engineering infrastructure inside of AWS, including serverless data engineering and database operations.Provide guidance for both data quality, data governance, and data maintenance.

Performed multiple roles as software engineer and team lead of project seeking to understand the neural basis of movement. Responsibilities included leading daily team meetings, managing and assigning stories, lead key technical stakeholder presentations, engage in technical writing such as grants and research papers.Conceive with team, build, and experimentally validate a 6-DOF pneumatic robot with machine vision capability using C, C++.Devise, integrate a multi-camera 3-D computer vision embedded solution with microcontrollers using Python, C++. Develop, automate tests, and maintain software for real-time control, streaming, and warehousing of high-bandwidth sensor data(>100mbs) using C++, Python, CUDA, OPENCV. Build using Tensorflow, train, deploy supervised, semi-supervised CNN, DNN, and other types of computer vision based neural network models for keypoint identification, scene classification using Tensorflow, PyTorch, MLFlow. Increase CNN performance metrics using semi-supervised learning methods such as pseudo labeling, synthetic data, and data augmentation. Train, validate alternative key point detection models for validation (Mxnet, VGG) using AWS Sagemaker/Docker/Tensorflow. Utilize unsupervised machine learning techniques such as UMAP, TSNE for real-time computer vision scene classification. Design, collaborate, develop and maintain modeling and data visualization dashboarding software using Python/SQL/R/mpl.

Worked towards publication of astrophysical (exoplanet) orbital simulation using high-dimensional time-series data. Performed research-focused data engineering, data science, high-performance compute administration, and software engineering.