Vitae

Current Position
  • June 2017 - present. Postdoc at University of Oslo, Wearable sensors monitoring and machine learning. Development of personalized monitoring systems for mental healthcare applications. Analyze sensor data (smartphones, VR, wrist bands, physiological sensors) with machine learning for episode prediction. Development of algorithms to provide personalized assistance based on current behavior.

Education
  • January 2013 – May 2016. Ph.D. in Information Technologies and Communications at Tecnológico de Monterrey, Mexico; Collective Contextual Intelligence Research Group. Research topic: Long-term Activities Recognition and Model Personalization from Wearable Sensors Data.
  • January 2011 – December 2012. M.Sc in Intelligent Systems at Tecnológico de Monterrey, Mexico. With honors. Thesis: Human Activity Recognition using Smartphone's Sensors.
  • August 2003- December 2007. Computer Systems Engineering at Tecnológico de Monterrey Campus Toluca, Mexico. With honors.

Research Experience and Work

  • June 2017-Present. Postdoc fellow at Robotics and Intelligent Systems Group, department of informatics, University of Oslo. Research and development of patient monitoring and support systems using smartphone technology and built-in sensors as part of the Research Council of Norway funded project INtroducing personalized TReatment Of Mental health problems using Adaptive Technology (INTROMAT).
  • August 2016-May 2017. Independent Data Analysis Consultant for Tecnologico de Monterrey University. Developed machine learning algorithms and analysis of real-world sensor data to monitor older adults' behavior. Implemented modules for fall detection, sleep monitoring and activity recognition from a wrist-band sensor data. The project was carried out by industry and academic partners. The algorithms were implemented and tested in R programming language. I implemented working prototypes on android devices and a Microsoft Band. The final prototype was implemented in hardware by the hardware specialists.
  • 2011-Present. Collective Contextual Intelligence Research Group at Tecnologico de Monterrey. Collaborating with a team of researchers to make use of wearable sensors’ data to infer users’ context such as current physical activity, location, etc.
  • June-November 2014. Research stay at CREATE-NET Mobile and Ubiquitous Technologies group, Trento, Italy. Conducted experiments with data collected from smartphones’ sensors in an unconstrained environment to detect stress levels in working environments. Analyzed accelerometer data to infer social interactions, specifically, detect if two persons are walking in synchrony.
  • June 2014. EIT ICT Labs Health and Wellbeing Summer School. Lapland, Finland. Worked with a multidisciplinary team and proposed a system for health care interventions in workplaces based on environmental and wearable sensors.
  • August 2014. EIT ICT Labs Summer School on Health and Wellbeing. Eindhoven, Holland.
  • 2009–2010. Huawei Technologies. Worked as a Software Engineer supporting and developing IT systems for a mobile phone carrier company. Specifically, I worked on the back-end system for the SMS service used in Mexico and Latin-America. The system provides core functionality to store and process SMS messages. Main technologies used: Java, Oracle database, Servlets, JSPs.
  • 2008. HSBC Bank. Programmer. Analyzed, designed and implemented different modules for the Internet Personal Banking system where customers can do common banking operations. This system is the main bank interface that provides digital services to customers such as electronic money transfers, contacts management, payments, etc. Main technologies used: Java, Servlets, JSPs.


Main Programming Languages
  • Java, R, python (basic).

Completed Workshops, Courses and MOOCs (Massive Open Online Courses)

* with distinction

Awards 

  • 2016 IEEE eta kappa nu membership
  • 2013 Full tuition financial support for the Ph.D. Program
  • 2012 Best GPA in the Intelligent Systems Master Program
  • 2011 Full tuition financial support for the Master in Intelligent Systems Program