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Edwin Salcedo

I'm a Lecturer and Research Engineer at the Bolivian Catholic University UCB in the Department of Mechatronics Engineering. There, I study computer intelligence through software and hardware integration. I specially focus on building ML algorithms for sensor data and computer vision. Previously, I completed an MSc in Advanced Software Engineering at the University of Sheffield and a PgDip in Machine Learning and Big Data at the Pontifical Catholic University of Chile. Read more about my background here.


  • ■ Apr 2024 : Invited as a reviewer for IEEE Access Journal
  • ■ Apr 2024 : Awarded with the Recognition for Teaching Excellence at UCB
  • ■ Feb 2024 : Our project CUBITAL was awarded with the Premio Plurinacional de Ciencia y Tecnología.
  • ■ Jan 2024 : Our paper "Towards Continuous Floating Invasive Plant Removal Using Unmanned Surface Vehicles and Computer Vision", has been accepted in IEEE Access.
  • Lecturer in Computer Vision
  • Research Engineer
  • Data Scientist
  • Systems Engineer

About Me

I'm a lifelong learner. To summarise, I'm committed to developing innovative, intelligent systems to improve other's lives. My research and professional projects occur at the intersection of four fields: Machine Learning, Internet of Things, Computer Vision, and Software Engineering. I can't stop being grateful to God, my ex-supervisors, and funders for all their support through my journey.

MIT Innovator Under 35

Awarded due to my research in the medical imaging field and its combination with virtual reality.

Chevening Scholar 2017/2018

Sponsored by the British government to further my studies in Advanced Software Engineering

National Science Prize 2016

Awarded due to my undergraduate final project related to healthcare.

About Skills

Edwin Salcedo

Bio: I'm a Lecturer and Research Engineer at the Bolivian Catholic University in the Department of Mechatronics Engineering, where I study computer intelligence through software and hardware integration. My research focuses on designing and building deep learning architectures for sensor data and computer vision that can run efficiently on constrained platforms. In particular, I'm interested in designing hardware-aware optimizations for deep learning workloads enabling efficient inference when consuming data in the form of images, audio, and graphs. I'm also interested in exploring the area of cyber-physical systems, which use networked smart devices to sense and interact with physical entities.

Previously, I completed my B.Sc. in Systems Engineering at UCB in 2015 and an M.Sc. in Advanced Software Engineering at The University of Sheffield (United Kingdom) in 2018, where I later worked as a Research Software Engineer and Graduate Teaching Assistant. I recently finished a PgDip in Machine Learning and Big Data at Pontifical Catholic University of Chile to polish my machine learning skills.

Outside of the academic arena, I've had extensive experience as a software engineer, IT manager, and team lead. Until August 2020, I worked as a Research and Data Science Consultant for Hivos and Swisscontact.


Python Backend Development
Computer Vision
Machine Learning and Data Science
JS Full Stack Development
Internet of Things

Most recent technologies used


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Game Design

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  • Years of Experience in Tech

  • Talks and Conferences

  • Kilometers in Marathons, Half Marathons and Races
  • Some facts

Working at "Bolivian Catholic University"

2020 - Present

Lecturer · Research Engineer
IoT/Machine Learning/Software Engineering/Teaching

Modules Taugh: DIT-500 Internet of Things Fundamentals, SIS-111 Programming Fundamentals, DAA-530 Unsupervised Machine Learning.
Developing an IoT system for a smart saline level monitoring device. Creating ML models for risk trajectories and anomaly detection.


My Projects

  • All
  • IoT
  • Machine Learning
  • Front-end
  • Back-end
  • Algorithms
  • NLP


I’m always interested in personal initiatives or professional projects where I can apply my knowledge in IoT,
\ Machine Learning, Computer Vision, and Software Engineering.




ADRAS: Airborne Disease Risk Assessment System for Closed Environments Conference Paper

Abstract: Airborne diseases are easy to spread in the population. The advent of COVID-19 showed us that we are not prepared to control this type of disease. The pandemic has drastically posed challenges to the daily functioning of public and private establishments. In general, while there have been several approaches to reduce the potential risk of spreading the virus, many of them rely on the commitment that people make, which - unfortunately - Continue reading...

Author(s): Wilber Rojas, Edwin Salcedo, Guillermo Sahonero

SIMBig, Lima, Peru

Oral presentation

A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting Journal Article

Abstract: Maintenance of critical infrastructure is a costly necessity where developing countries often struggle to deliver timely repairs. The transport system acts as the arteries of any economy in development, and the formation of potholes on roads can lead to injuries and loss of lives. Recently, several countries have enabled pothole reporting platforms for their citizens, so that repair work data can be centralised and visible for everyone. Continue reading...

Author(s): Edwin Salcedo, Mona Jaber, Jesús Requena Carrión

Journal of Sensor and Actuator Networks


Teaching (2022)

IMT-344 Computer Vision, Lecturer @UCB (Spring & Fall semester)

My mission is to prepare students to thrive in the Innovation Age by teaching them to think at three levels:

WHAT: What is the basic concept?​
SO WHAT: What is its relevance and what is it related to?
NOW WHAT: What can I do with what I have learned to find solutions to unmet needs?

I aim to help students understand the fundamental theory of computer vision algorithms and implement the concepts with recent technologies such as OpenCV, PyTorch and TensorFlow. I combine a variety of learning activities (paper discussions, synchronous tutorials, lectures, quizzes, a final project) to enhance students' learning experience and outcomes. As a result, students have managed to develop a covid-19 detection system from X-Ray images, a virtual board for remote math classes, and a machine vision system to differentiate bad and good quality coffee grains.

BootCamp in Computer Vision for the SDGs, Lecturer @UCB (Spring semester)

IMT-354 Final Degree Project, Supervisor @UCB (Spring & Fall semester)

  • "Prediction of the steering angle of the steering wheel for an autonomous vehicle based on attention strategies", Melissa Chiri
  • "System for monitoring drowsiness and distraction in car drivers using artificial vision", Rodrigo Herrera

Tutoring / Teaching (Past)

AI-based Chatbot Development with Natural Language Processing, Lecturer @GAMLP (2-Week Workshop), Sept 2021

DAC-520 Computer Vision for Industrial Applications, Lecturer @UCB (Postgraduate course), 2021

IMT-344 Computer Vision, Lecturer @UCB (Spring & Fall semester), 2021

IMT-354 Final Degree Project, Supervisor @UCB (Spring semester), 2021

  • "Domotic Home for Pets", Freddy Magne
  • "Computing the Risk of Spreading COVID-19 by using Computer Vision", Wilber Rojas

DIT-500 Internet of Things, Lecturer @UCB (Postgraduate course), 2020

SIS-111 Programming Fundamentals, Lecturer @UCB (Spring semester), 2020

DAA-530 Unsupervised Machine Learning, Lecturer @UCB (Postgraduate course), 2020

TA Work (Past)

COM-3505 Internet of Things, Teaching Assistant @The University of Sheffield (Fall term), 2018

INF-105 Programming I, Teaching Assistant @UCB (Fall semester), 2013

MAT-132 Calculus I, Teaching Assistant @UCB (Fall semester), 2013

INF-108 Programming II, Teaching Assistant @UCB (Spring semester), 2013


I'm currently based in La Paz, Bolivia 🇧🇴

I actively collaborate organising workshops, mentoring, and giving talks in the following communities:


I'm always looking to expand my network and connect with like-minded people. Get in touch!