Me
carlostorres[at]ece[dot]ucsb[dot]edu
carlos[dot]torres[dot]ee[at]gmail[dot]com
I obtained a PhD degree (link to defense deck) from the Department of Computer and Electrical Engineering (ECE) at the University of California Santa Barbara (UCSB) as a member of the Vision Research Laboratory under the advisement of Prof. B. S. Manjunath. I have an M.S. in Electrical and Computer Engineering also from UCSB and a B.S. in Electrical Engineering and BioEngineering from San Jose State University.
I left my position with Procore Technologies in Carpinteria as Data Scientist and Machine Learning Researcher to join Mayachitra Inc., as a Principal Investigator and Senior Researcher where I develop new methods and solutions for activity and event analysis, uncertainty estimation, satellite imagery object detection, and smart multimodal distributed sensor networks.
Resume & Curriculum Vitae (CV):
PhD Thesis Scope
My research focused on multimodal data analytics for healthcare applications by combining computational abilities with the healthcare system. In particular, I developed unobtrusive systems and statistical analysis methods and algorithms to autonomously monitor patients and healthcare environments. My research aimed to provide tools for objective identification and evaluation of medical therapies, protocols, and workflows along with their effect on patient health. The developed methods use statistical analysis and real-world datasets collected by an inexpensive multimodal multiview sensor network. These sensors continuously collected data in a medical ICU without disrupting patients or care practices. The technical areas of my research involved coupled optimization, Hidden Markov Models, and conditional random fields.
Press Coverage
Spotlight Profile at UCSB-ECE 2015
MESH in the news Fall 2017
Research Interest
I am involved in multiple research projects in topics ranging from agriculture and water management and analysis to wound care, augmented reality, medical data analytics, and construction management. My attention is easily captivated by real-world data and problems. I seek to create robust autonomous systems that are adaptively aware of their surroundings. I am interested in the development of hardware and and software solutions (massive data!) that give systems the ability to autonomously analyze their surroundings and execute complex tasks in “natural” human environments. I am also interested in real-life problems where perfectly labeled data may not actually exist and where the impact levels are vast.
