Manuel Reyes-Gomez's Email Addresses & Phone Numbers

📖 Summary

Dr. Manuel Reyes-Gomez’s main interests are in the design of structural novel statistical models that follow the underlying structure of signals and systems, permitting them to automatically adapt to the signal changes while capturing important patterns on the signal evolution. Dr. Reyes-Gomez has vast experience in working with complex custom made probabilistic models, for which full inference is intractable, by the use of approximation techniques such as variational learning and belief propagation. Dr. Reyes-Gomez has worked on a wide range of domains from Finance, Education, Telecommunications, Energy Production, Computational Biology, Speech Recognition, Audio and Image Processing, Search Query Understanding to Information Retrieval. Dr. Reyes-Gomez holds several American patents and has over 30 publications on top research journals and conferencesChief Data Scientist and Co-Founder @ Oversees the design and implementation of Big Data and Predictive Analytics solutions for a wide range of industries, such as Finance, Telecommunications, Energy, Security and Education Principal investigator for the National Science Foundation, Small Business Innovation Research Grant # 1345533, "A PERSONALIZED SEARCH ENGINE FOR EDUCATIONAL RESOURCES" From November 2012 to Present (3 years 2 months) Senior Applied Researcher @ Senior Applied Researcher (Bing) September, 2007 – August 2014 Writing production code for the implementation of algorithms based on principles from fields such as probabilistic modeling, information theory, data mining and machine learning for a wide range on problems. I have both designed my own custom made learning algorithms based on the graphical models framework and used libraries for well-known algorithms such as boosted trees, logistic regression, SVMs, neural networks, etc. Non-exhaustive lists of projects I have worked on are the following: - Search Queries Segmentation and Classification - Automatic inference of consolidated business listings. (From information for a local business coming from several sources, infer the best possible consolidated business listing to show on the Bing Local vertical portal) - Automatic validation of business listings. - Automatic discovery and characterization of business chains entities and their locations. - Automatic detection of closed businesses - Automatic discovery of thousands of business aggregators websites such as Yelp, including small obscure local ones that might aggregate only plumbers in the upstate New York Area - Automatic discovery of business websites - Automatic retrieval of business references on hyper local blogs - Automatic classification of restaurant listings by cuisine type - Local queries classification and parsing Microsoft Research, Redmond, WA, USA Group: Machine Learning and Applied Statistics Researcher April, 2005 – September 2007 Design and implementation of novel models and algorithms for audio analysis focusing on scene analysis and source separation applications. Designing machine learning models to characterize the multiple processes involved with the immune system. These models are later used to predict if particular patients will react or not to specific pathogens. From April 2005 to June 2014 (9 years 3 months) Greater Seattle AreaGraduate Research Assistant @ From August 2000 to April 2005 (4 years 9 months) Research Intern @ From January 2004 to August 2004 (8 months) Research Intern @ From 2002 to 2002 (less than a year) Lead Project Engineer @ From February 1997 to August 1998 (1 year 7 months) Ph.D., Electrical Engineering @ Columbia University in the City of New York From 2000 to 2005 M.S., Electrical Enigineering @ Columbia University in the City of New York From 1998 to 2000 BS, Electrical engineering @ Fundación Universidad de las Américas Puebla From 1989 to 1994 Manuel Reyes-Gomez is skilled in: Machine Learning, Algorithms, Computer Vision, Pattern Recognition, Natural Language Processing, Distributed Systems, Python, Computer Science, Image Processing, Artificial Intelligence, Software Engineering, Information Retrieval, Big Data, Signal Processing, LaTeX