James G. Email and Phone Number

During grad school, I transitioned to Ziteo as a Software Engineer working on nuclear medicine imaging robotics. I am also a postgrad SJSU MS AI researcher improving my results in AI stroke diagnosis. In the early part of grad school, I was a R&I Software Engineering intern at Noah Medical working on embedded to AI/ML software infrastructure for medical surgical robotics that uses minimally invasive procedures to fight against cancer. Before graduating in my SJSU MS AI program, I focused on building AI Apps for Medical Imaging targeted toward minimally invasive procedures. With the AI Medical Imaging apps that I build, I plan to put some emphasis toward AI Ethics. For my masters thesis, I worked on building Brain Medical Imaging AI infrastructure that detects stroke lesions in effort to potentially help Radiologists and Neuroendovasdcular surgeons with early stroke intervention to save patients.I worked as a Software Engineer at startup Parry Labs (DoD contractor) in the field of Unmanned Aircraft Systems focusing on developing middleware using Data Distribution Services (DDS) and Apache Kafka in C++ that allow data to flow from Unmanned Aircraft (UA) operator to Ground Data Terminal (GDT) for a Ground Control Station (GCS) to communicate with an UA System.At Cloudera, I worked as an Engineer developing, debugging and revamping software prototype applications and tutorials using big data technologies, deep learning and robotics. I trained new interns to get them up to speed with the technologies. I collaborated with Solutions Engineers and Software Engineers on these efforts. Prior to leaving, I developed a small scale self-driving car. The car's hardware technologies used were RACECAR/J powered by Nvidia Jetson TX2, 3 USB cameras, servo steering, brushless DC motor and an electronic speed controller. The car's software stack included Keras on TensorFlow, OpenCV, ROS. Cloudera Distribution Hadoop and Cloudera Data Flow were integrated into the car prototype for dealing with the scenario of powering fleets of self-driving cars. Later through collaboration, the Solutions Engineering team used this project for their certification.I completed Udacity's Self-Driving Car Engineer Nanodegree program. I have knowledge in developing a Self-Driving Car Software Stack from Udacity. This software stack includes Perception, Sensor Fusion, Localization, Path Planning, Particle Filtering and Robotic System Integration. I am looking at ways to apply what I learned in the nanodegree in medical robotic projects that I work on in my masters program