Miguel Moisés Serrano, Ph.D. Email & Phone Number

United States

Atlanta, Georgia, United States

Lead ML Engineer:* Creating, Developing and Deploying ML solutions.

San Francisco Bay Area

* Led the development of a pre-consult summary generator using large language models (LLMs) to extract and summarize comprehensive patient information, reducing provider preparation time.* Collaborated on a chat response generator that utilized LLMs, significantly reducing provider billable time by automating initial communication with members.* Created.

Marietta, Georgia, United States

* Designed, developed and launched a Cash Flow Forecast tool that is currently used to guide business decisions and initiatives* Led multiple projects resulting in the development of products and contributed significantly to three patent submissions currently under review.* Led the team in adopting best practices for cloud infrastructure, code management.

Greater Atlanta Area

* Managed the efforts of interns, developers, and fellow machine learning engineers to successfully deliver a model-agnostic cloud-based training, evaluation, and inferencing pipeline for aerial imagery.* Oversaw collaborations with research partners at GTRI, facilitating communication, updates, and objective establishment.* Applied modern machine learning.

Atlanta, Georgia, United States

* Investigated the use of hybrid machine learning and model-based computer vision for human pose estimation, focusing on practical methods for medical applications.* Utilized de-convolutional neural networks to identify subsections of subjects (e.g., human, infant, robotic manipulator) for accurate human pose estimation.* Incorporated model-based methods.

Instructor of record for an intro to electrical engineering course for two consecutive semesters. Additionally, taught a series of lectures in controls, robotics, and computer vision course.

Atlanta, Georgia

* Conducted research and developed methods to detect and categorize unique structures from densely reconstructed point cloud data, with the output converted to industry-standard formats such as CAD.* Utilized machine learning methods, including deep convolutional neural networks and support vector machines, to extract semantic and quantitative values from.

Doctor Of Philosophy - Phd, Electrical And Electronics Engineering

Master'S Degree, Electrical And Electronics Engineering

Activities and Societies: Controls, Computer Vision, Robotics, and Machine Learning

Bachelor'S Degree, Electrical And Electronics Engineering

Activities and Societies: Eta Kappa Nu, Tau Beta Pi