Ing. in Cybernetics and Robotics
Ing. in Mechatronics Engineering
Data Scientist
Inventor of the Auto-Rotating Neural Networks
AI Researcher & Lecturer
Entrepreneurship Spirit
NOTE: This website is still under renovation!
Some extracurricular projects
October 16th, 2024
Presented my research on Auto-Rotating Neural Networks at the Young AI Research Forum in Prague, as part of event Dny AI 2024, celebrated at CIIRC CTU.
May 16th, 2024
A single-camera system for measuring the displacement of a metal block from its target position. It was developed for an Italian manufacturer and tested using real production data.
May 1st, 2020
A 2 DOF robot that learns to aim a laser beam; by using DDQN, NEAT, and computer vision.
November 7th, 2018
An 8 DOF walking robot built through rapid prototyping, later used in my bachelor’s thesis.
September 2nd, 2018
Kalman filters in MATLAB and real-time sensor-fusion of accelerometer signals on Arduino.
March 19th, 2016
A rolling robot inspired by BB-8, with a magnetically coupled domed head that can rotate while the robot moves.
Academic productions
Sharing knowledge
PUCP
CETAM-PUCP
CETAM-PUCP
PUCP
11 Countries, 17 Institutions
One contribution to AI
"When using deep neural networks, do we ever change the neuron itself?"
Nowadays, all artificial neural networks use the same concept of dot product. The Auto-Rotating Perceptron (ARP) introduces a novel mechanism that rotates the latent hyperplane in the weight space, tackling thevanishing gradient problem from a fundamentally different angle. Our formulation proposes an enhanced dot product operation, so that its resulting values are restricted to belong to the range that goes from -L to +L. This concept has been extended to convolutional, recurrent, and other architectures, becoming the Auto-Rotating Neural Networks (ARNNs) family.
pip install arpkeras) Presented at
Interactive portfolio
Online pose detector for hands. Do not forget to give camera permissions!
Collisions on a 2 DOF Scara Robot: World Space and Simulation Space
Staying curious, learning continuously
Continuous learning has been a recurring part of my academic and professional journey. For the past 12 years, I have pursued at least one training opportunity every year, exploring topics ranging from engineering and artificial intelligence to research, technology, and entrepreneurship.
Scroll vertically to explore all continuous education entries. The list ends after the oldest entry and does not loop.
Aug. 2026
Coursera
Aug. 2026
Sep. 2025
Hasso Plattner Institute (HPI)
HPI Potsdam
Jun. 2025
Aug. 2024
PUCP
Nov. 2023
NVIDIA Deep Learning Institute
NVIDIA DLI
Aug. 2022
Oxford University & AI for Global Goals
Oxford University
Jun. 2022
National University of Engineering (UNI)
UNI
Mar. 2022
National University of Engineering (UNI)
UNI
Jan. 2022
National University of Engineering (UNI)
UNI
Nov. 2021
Asian Conference on Machine Learning (ACML)
ACML 2021
Aug. 2021
International Meeting on AI and its Applications (RIIAA)
RIIAA 2021
Jul. 2021
Center for Advanced Manufacturing Technologies (CETAM)
PUCP
Nov. 2020
IEEE Ricardo Palma University Student Branch
IEEE Peru Section
Jul. 2019
NVIDIA Deep Learning Institute
NVIDIA DLI
Nov. 2018
Udacity / Facebook
Udacity
Apr. 2018
Columbia University
edX
Feb. 2017
AlDelta Technologies
AlDeltaTec.com
May 2016
University of Texas at Austin
edX
May 2015
Queensland University of Technology
QUT MOOC