Ing. Pedro Jesús Nájera Chávez

• Increased the share of Juniper's latest portfolio of network equipment and solutions within Deutsche Telekom's network by participating in the design of the proposal for new expansion networks within Eastern Europe. • Enhanced security for remote connections for some DT devices by advising on the implementation of new security updates in the remote connection protocols to the network equipment.

• Developed firmware and software in Python and C++ for data extraction, processing, and interpretation of information obtained from the sensor gas in development. • Creation of a database for the development of a real profile to test the developed sensor using web scrapping with Python. To later extend it with the use of Machine Learning techniques. • Designed a testing PCB data field-board to compare and improve the design of our gas sensor under development with those from different companies.

Machine Learning LSTM-based prediction of 3D human activities poses (artificial recurrent neural network - RNN architecture): • Obtain a 3D skeleton pose of diverse human activities through the graphic analysis of a person through a camera (image processing). • Prediction of next human trajectory based on previous movements using a LSTM architecture in a Python environment.

I took part in the Unified Infrastructure R&S team (Optical and Service Provider R&S technology) • Development of strategy for infrastructure migrations. • Migration of legacy equipment infrastructure. • Supervision and verification of migrations carried out. • Dealing with clients and technical team

Master Thesis: Deep Reinforcement Learning with Double-DQN algorithm approach for resources allocation in an Edge Network Slicing in a 5G use-case.

Full scholarship for the summer Trepcamp entrepreneurship program at Georgetown University (sponsored by Santander and Impulsa México). A program of three weeks long with classes and training to develop entrepreneurial skills.