University of Manchester Research Profile.

Google Scholar Research Profile.

Grants

Call for small projects – Data Science Institute, University of Manchester, UK. (£10,000) Project: Developing novel data science methodology for analysing gait patterns for the early detection of cognitive decline.

Partnership research projects

(1) Deep and frequent phenotyping; combinatorial biomarkers for dementia experimental medicine (UK). Medical Research Council, grant ref 1511HQ003/Jl3, 2016. (£6,301,078). PI: Simon Lovestone (University of Oxford). Partnership universities: Oxford, Cambridge, Imperial College London, Manchester, Edinburgh, Newcastle, and more.

International Journals

(1) (NEW!) Omar Costilla-Reyes, Ruben Vera-Rodriguez, Patricia Scully, and Krikor B Ozanyan. Analysis of spatio-temporal representations for robust footstep recognition with deep residual neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, January 2018.

(2) Omar Costilla Reyes, Patricia Scully, and Krikor B. Ozanyan. Thinking and walking: A deep learning approach to detect age-related differences in dual tasks from healthy adults. PLOS Medicine. March 2018 (under review)

(3) Omar Costilla-Reyes, Patricia Scully, and Krikor B Ozanyan. Deep neural networks for learning spatio-temporal features from tomography sensors. IEEE Transactions on Industrial Electronics, PP(99):1–1, 2017.

(4) Omar Costilla Reyes, Patricia Scully, and Krikor B. Ozanyan. Temporal Pattern Recognition in Gait Activities Recorded with a Footprint Imaging Sensor System. IEEE Sensors Journal, 16(c), dec 2016.

International Conferences (with research manuscript published)

(1) Omar Costilla-Reyes, Patricia Scully, and Krikor B Ozanyan. Towards floor sensors to flag cognitive decline thresholds. In Proc. of Movement, Brain, Body and Cognition international conference 2018 (in press).

(2) Omar Costilla-Reyes, Patricia Scully, and Krikor B Ozanyan. Age-sensitive differences in single and dual walking tasks from footprint imaging floor sensor data. In Proc. of 2017 IEEE Sensors Conference IEEE, 2017.

(3) Omar Costilla-Reyes, Zachary Coldrick and Bruce Grieve. Unsupervised learning for spectral data analysis as a novel sensor for identifying rodent infestation in urban environments. In Proc. of 2017 IEEE Sensors Conference IEEE, 2017.

(4) Omar Costilla-Reyes, Ruben Vera-Rodriguez, Patricia Scully, and Krikor B Ozanyan. Spatial footstep recognition by convolutional neural networks for biometric applications. In Proc. of 2016 IEEE Sensors conference. IEEE, 2016.

(5) Omar Costilla-Reyes, Patricia Scully, and Krikor B Ozanyan. Temporal pattern recognition for gait analysis applications using an “intelligent carpet” system. In Proc. of 2015 IEEE Sensors conference. IEEE, 2015.

(6) Omar Costilla-Reyes and Kamesh Namuduri. Dynamic wi-fi fingerprinting indoor positioning system. In Indoor Positioning and Indoor Navigation (IPIN), 2014 International Conference on, pages 271– 280. IEEE, 2014.

(7)  Omar Costilla-Reyes, Rajeev Azad, Garima Saxena and Joseph Helsing. Comparison of Machine Learning Algorithms for Identifying Cancer Types, MidSouth Computational Biology and Bioinformatics Society, 2014 international conference on, 2014.

(8) Omar Costilla-Reyes. What can machine learning infer about the way you walk?  In Euroscience open forum (ESOF) 2016.

(9) Patricia Scully, Jose Cantoral-Ceballos, John Vaughan, Omar Costilla-Reyes, et all. iMagiMat Smart Carpet: POF Layer to Detect Gait and Mobility. in Proceedings of 24th International Conference on Plastic Optical Fibres. (POF 2015).