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Dr Raimundo Sanchez
Dr

Raimundo Sanchez

Email: 
Phone: 
+61 7 344 33778

Overview

Background

I build quantitative systems for understanding how humans move, perform, using data from wearable sensors in real-world conditions.

My work sits at the intersection of machine learning, signal processing, and sports and health science. I develop the analytical infrastructure that makes large-scale, free-living sensor research feasible: pipelines for IMU and GNSS data, predictive models for physical activity and pain dynamics, and validation frameworks for wearable devices.

At UQ, I contribute to the CIPHeR program (NIH/NHMRC-funded), investigating mechanisms of chronic low back pain through longitudinal modelling of movement, sleep, stress, and pain. I also lead Metric Trails, an applied R&D initiative developing high-precision geospatial standards for trail and mountain running.

My background spans academia and industry. Before UQ, I led data science teams at LATAM Airlines and built research programs in wearable analytics and geospatial modelling at Adolfo Ibáñez University in Chile, where I supervised 19 postgraduate theses.

I work across disciplines, with physiotherapists, sports scientists, engineers, and clinicians, and across an international network of collaborators in Australia, Chile, Norway and Spain.

Availability

Dr Raimundo Sanchez is:
Available for supervision
Media expert

Qualifications

  • Bachelor (Honours) of Industrial Engineering, Universidad Adolfo Ibáñez
  • Doctor of Philosophy of Systems Engineering, Universidad Adolfo Ibáñez

Research interests

  • Real-world wearable validation

    I develop methods to validate and benchmark wearable-derived signals in free-living conditions, focusing on data quality, uncertainty, and reproducibility. This includes IMU, GNSS, and heart rate/HRV, and practical frameworks to compare devices, algorithms, and protocols in the real world.

  • Field biomechanics and endurance movement

    I investigate human locomotion in outdoor environments, with a focus on trail and mountain running. This includes field-based biomechanics, sensor-based movement analysis, and study designs that capture real-world variability in terrain, pacing, fatigue, and movement strategies.

  • High-precision GNSS and terrain analytics

    I develop geospatial methods to improve measurement accuracy for outdoor locomotion research. This includes high-precision GNSS workflows and terrain analytics to reduce bias in distance, elevation gain, speed, and gradient, supporting safer, fairer, and more reproducible trail and mountain metrics.

  • Robust time-series ML for wearables

    I build applied machine learning approaches for wearable time-series that remain reliable under missing data, drift, and confounding. My focus is on feature engineering, model evaluation, and interpretability for real-world health and performance applications.

Research impacts

My research impact is grounded in the principle that decision-makers should understand and trust the systems they rely on.

At UQ, I provide the quantitative infrastructure that makes complex sensor-based research feasible. The CIPHeR program is a five-year NIH/NHMRC-funded study of chronic low back pain that relies on analytical pipelines I designed to process and model longitudinal wearable sensor data from free-living participants. Without this infrastructure, the core analysis of the study would not be possible.

In parallel, I developed the only published method for high-precision terrain standardisation in trail and mountain running research. Using multi-band GNSS and multimodal geospatial processing, the method achieves a mean separation of 50 centimetres between repeated 1 km trajectories on complex mountain terrain, establishing the measurement foundation the field has been missing.

At LATAM Airlines, I led development of an in-house revenue management system that priced every seat across the entire LATAM network, 365 days forward. It replaced PROS OnD, an industry-standard tool costing USD 2M per year, because that system made assumptions analysts could not verify, so they overrode it constantly. The in-house model was built on the same assumptions as LATAM's strategic planning. Analysts trusted it. Revenue execution improved 10x and revenues increased approximately 3% versus control flights.

Works

Search Professor Raimundo Sanchez’s works on UQ eSpace

27 works between 2016 and 2026

21 - 27 of 27 works

2020

Journal Article

Comparative evaluation of wearable devices for measuring elevation gain in mountain physical activities

Sánchez, Raimundo and Villena, Marcelo (2020). Comparative evaluation of wearable devices for measuring elevation gain in mountain physical activities. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 234 (4), 312-319. doi: 10.1177/1754337120918975

Comparative evaluation of wearable devices for measuring elevation gain in mountain physical activities

2020

Journal Article

Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso (Use of digital devices to follow a Trail Runner. Case study)

Sánchez, Raimundo and Nieto-Jimenez, Claudio (2020). Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso (Use of digital devices to follow a Trail Runner. Case study). Retos (38), 582-586. doi: 10.47197/retos.v38i38.77105

Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso (Use of digital devices to follow a Trail Runner. Case study)

2020

Journal Article

Use of digital devices to follow a Trail Runner. Case study Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso

Sánchez, Raimundo and Nieto-Jiménez, Claudio (2020). Use of digital devices to follow a Trail Runner. Case study Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso. Retos, 83, 582-586. doi: 10.47197/retos.v38i38.77105

Use of digital devices to follow a Trail Runner. Case study Uso de dispositivos digitales en el seguimiento de un Trail Runner. Estudio de caso

2020

Journal Article

Use of digital devices to follow a Trail Runner. Case study

Sanchez, Raimundo and Nieto-Jimenez, Claudio (2020). Use of digital devices to follow a Trail Runner. Case study. Retos-Nuevas Tendencias En Educacion Fisica Deporte Y Recreacion (38), 582-586.

Use of digital devices to follow a Trail Runner. Case study

2017

Journal Article

Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition

Rodríguez-Valdecantos, Gustavo, Manzano, Marlene, Sánchez, Raimundo, Urbina, Felipe, Hengst, Martha B., Lardies, Marco Antonio, Ruz, Gonzalo A. and González, Bernardo (2017). Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition. Applied Soil Ecology, 120, 44-54. doi: 10.1016/j.apsoil.2017.07.015

Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition

2016

Journal Article

Identifying an optimal analysis level in multiscalar regionalization: A study case of social distress in Greater Santiago

Garreton, Matias and Sánchez, Raimundo (2016). Identifying an optimal analysis level in multiscalar regionalization: A study case of social distress in Greater Santiago. Computers, Environment and Urban Systems, 56, 14-24. doi: 10.1016/j.compenvurbsys.2015.10.007

Identifying an optimal analysis level in multiscalar regionalization: A study case of social distress in Greater Santiago

2016

Conference Publication

Today's agenda: Building LATAM: Our history

Jovel, Carlos and Sánchez, Raimundo (2016). Today's agenda: Building LATAM: Our history. Airline Group of the International Federation of Operations Research Societies (AGIFORS).

Today's agenda: Building LATAM: Our history

Supervision

Availability

Dr Raimundo Sanchez is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • Real-world validation and benchmarking of wearable signals

    Develop a practical validation framework for wearable-derived signals in free-living settings, focusing on data quality, uncertainty, and reproducibility. The project will benchmark IMU, GNSS, and heart rate/HRV metrics across devices and protocols, and produce a reusable analysis pipeline. Outcomes include validation datasets, benchmark metrics, and recommendations for robust study design. Suitable for candidates with Python/R, time series, and interest in real-world wearables.

  • Field biomechanics in trail and mountain locomotion using wearables

    Quantify movement strategies in outdoor terrain using wearable sensors, linking biomechanics to terrain, pacing, fatigue, and performance. The project will combine IMU-based movement features with GNSS-derived context, with field protocols designed for ecological validity. Outcomes include validated features for outdoor locomotion research and guidance on best-practice field measurement. Suitable for candidates with biomechanics or sensor analytics background.

  • High-precision GNSS and terrain analytics for reproducible trail metrics

    Improve measurement accuracy of distance, elevation gain, speed, and gradient in outdoor locomotion by combining high-precision GNSS workflows and terrain analytics. The project will evaluate sources of bias in common tools and propose reproducible standards and pipelines for research-grade trail measurement. Outcomes include methods, datasets, and practical standards for field studies and events. Suitable for candidates with geospatial analytics, GNSS, or applied modelling.

  • Robust time-series ML for activity classification and anomaly detection

    Develop robust ML methods for wearable time-series to classify activity types and detect anomalies under real-world noise, drift, and mislabeling. Use GNSS and optional IMU/HR features to build models that generalize across users and environments, with emphasis on evaluation and interpretability. Outcomes include deployable modelling recipes and validation results relevant to fitness and health platforms. Suitable for candidates with ML and feature engineering skills.

Supervision history

Completed supervision

Media

Enquiries

Contact Dr Raimundo Sanchez directly for media enquiries about:

  • artificial intelligence
  • data science
  • fitness trackers
  • GPS tracking
  • health wearables
  • hiking
  • human movement
  • mapping
  • mountain
  • movement tracking
  • physical activity
  • running science
  • sensor data
  • smartwatches
  • sports technology
  • terrain
  • trail running
  • wearable technology

Need help?

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communications@uq.edu.au