leopoldo.lechuga [at] nyu.edu

Posts by Collection

portfolio

publications

New methods on image analysis: augmented reality application for heartbeat sound analysis and MRI brain injury images

Leopoldo Julian Lechuga López, Yamamoto Tomohito, Olga López Rios and Gisela Lechuga López

Journal of Physics Conference series: International Conference on Machine Vision and Information Technology, Guangzhou China, 2019

Traditional statistical methods have become insufficient when applied to image analysis. The increasing size of data volume and its complexity demands new statistical approaches and algorithms. Current methods imply losing intrinsic data structures, for example when data comes from multiway arrays. In this work we concentrate in two applications i) A pre-diagnostic smartphone application for detection of cardiovascular abnormalities through the analysis of heartbeat sounds and the use of augmented reality for displaying valuable information to the end user in an immersive experience. Read more

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Virtual Reality and Statistical Thinking Enhancement

Olga López Rios and Leopoldo Julián Lechuga López

IEEE Integrated STEM Education Conference, Princeton University USA, 2019

For decades, simulation has been a highly reliable tool for decision making. Even before its fundamental origin, the mathematical branch of system dynamics led to pioneering advances in research, technology and business. Today, virtual reality has become a mainstream technique for employee training. The combination of augmented and virtual reality technologies along with traditional methods of simulation has led to the development of a new powerful instrument of learning applied to complex systems. Read more

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A comprehensive statistical assessment framework to measure the impact of immersive environments on skills of higher education students: a case study

Olga López Ríos, Leopoldo Julian Lechuga López and Gisela Lechuga López

14th International Journal on Interactive Design and Manufacturing, 2020

Universities are facing the challenge of updating the contents of their current study programs and adopting novel education strategies in order to prepare the next generation of engineers who can adapt to the highly competitive labor market of Industry 4.0. This new industrial era requires skills and competencies in state-of-the-art technologies which are constantly and rapidly evolving. This research presents an alternative approach to the current teaching–learning methodologies, focusing on the use of Virtual Reality (VR) as an educational tool and its contribution towards the upcoming industrial challenges, via what we call interactive education for future engineers (IE). Read more

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Bringing industry to the classroom through virtual reality: enhancing learning and the undergraduate experience

Olga López Ríos, Leopoldo Julian Lechuga López and Gisela Lechuga López

International Conference on Education and Training Technologies Proceedings, Macau China, 2021

The requirements of Industry 4.0 provide a new opportunity for universities. As it will lead to a substantial transformation of their educational programs and methods to enhance students’ skills and competencies required for a new labor market given the rapidly emerging industry changes. This called Fourth Industrial Revolution is based on cutting-edge technological tools and data collection. Motivating new and innovative ways to operate and transform processes. These new tools and innovative education strategies, using trailblazing technologies, in engineering programs can potentially transform our society for the better. Read more

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Privacy-preserving machine learning for healthcare: open challenges and future perspectives

Alejandro Guerra-Manzanares, L. Julian Lechuga Lopez, Michail Maniatakos, Farah E Shamout

International Conference on Learning Representations 2023: Workshop on Trustworthy Machine Learning for Healthcare, 2023

Machine Learning (ML) has recently shown tremendous success in modeling various healthcare prediction tasks, ranging from disease diagnosis and prognosis to patient treatment. Due to the sensitive nature of medical data, privacy must be considered along the entire ML pipeline, from model training to inference. In this paper, we conduct a review of recent literature concerning Privacy-Preserving Machine Learning (PPML) for healthcare. We primarily focus on privacy-preserving training and inference-as-a-service, and perform a comprehensive review of existing trends, identify challenges, and discuss opportunities for future research directions. Read more

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talks

Welcome to Japan!

Published:

Selected to give the welcoming and closing ceremony speech for the japanese course as the representative of the research exchange group between Mexico and Japan. Read more

Automated control algorithm for inhabitable spaces using emotional domotics

Published:

Presented the results and prototypes obtained for the project developed at the end of my undergraduate studies to obtain the degree of mechatronics engineer. Project focused on the improvement of a person’s emotional state using brain signal analysis and a neural net control system of environment and audiovisual variables. Read more

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post. Read more

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post. Read more