Jun 22, 2020

Tatsat Vyas

  • Software Development Cyber Engineer Intern
  • Kearny, NJ, 07032, US
Full time Engineering Entry Level Information Technology

Personal Summary

Skills
C/C++, Java, Python Linux/Unix
Software Development Lifecycle AWS services (IoT Services, SageMaker, and more)
ML Algorithms Version control(GIT)
Scipy, Scikit-learn, Pandas, OpenCV TCP/IP protocols
Hadoop big data ecosystems Matlab
Spark AutoCad
SQL

Work Experience

Software Development Cyber Engineer Intern
May 2020 - CACI International Inc

Research and Implement tools to optimize Deep Learning networks on different platforms.
Design and develop synthetic data generation tools to train deep learning networks.
Actively collaborate with software engineers, data scientists, data engineers, ML engineers, researchers, and designers to get things done.
Develop solution ideas with given objectives and constraints.

Information Technology Assistant
Jul 2018 - May 2020 Rutgers University School

Developed streamlined task system to provide more effective workflows for both peers and management staff.
Created, edited, and updated technical documentation used by the entire team.
Worked with staff members to analyze computing and network needs and installed appropriate solutions within each
department's budget.
Prepared and presented technical proposals for faculty members.

Research Assistant
May 2017 - Jul 2017 Rutgers Chemical and Biochemical Engineering Department

Synthesized Nanoparticles for a drug delivery process to improve the treatment of diseases such as cancer.
Tested different combinations of polymers and surfactants to obtain the ideal particle size of under 100 nanometers.
Collaborated with peers and supervisors to discuss a better approach to minimize Nanoparticles.
Gained experience Operating equipment such as Sonicator, laser diffraction analyzer, and a high-pressure
homogenizer to obtain the smallest size of droplets.
Projects & Extracurricular
ADL Recognition Using Deep LSTM Network (Deep Learning, Python)
Trained a Deep Learning model to detect activities of daily living using sensor Data from smartphones and alert the system if the person falls while performing any activity.
Used domain adaptation to deploy the trained model on different smartphones and achieved an average accuracy of
87%.
Version Control System(java & c)
Designed a version control system similar to Git which consisted of a remote server that held the repository and managed changes to it.
Implemented parallel programming concepts to serve multiple clients at once and zlib file compression to store data
efficiently.

Education

Bachelor of Science - Electrical and Computer Engineering
Sep 2016 - May 2020 Rutgers University