Rodrigo Rivera-Castro
For more information please visit http://www.rodrigo-rivera.com
Graduated from: Technical University of Munich (Bsc. Information Systems), Center for Digital Technology and Management (Hons.deg. Technology Management), CEMS MIM (Master in Management), Higher School of Economics (Master in Big Data Systems)
Research interests: machine learning, time series, causality, topological data analysis, optimal transport
Thesis title: Topological Data Analysis of Time Series Data for Generation of Topological Summaries for Machine Learning Methods
Publications:
– Rivera, R. et al.: Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods. J. Phys. Conf. Ser. 1117, 1, 012010 (2018).
– Rivera, R., Burnaev, E.: Forecasting of commercial sales with large scale Gaussian Processes, arXiv:1709.05548, (2017).
– Rivera-Castro, R. et al.: An industry case of large-scale demand forecasting of hierarchical components. Accepted at ICMLA2019.
– Rivera-Castro, R. et al.: Demand forecasting techniques for build-to-order lean manufacturing supply chains. Accepted at ISNN2019.
– Rivera-Castro, R. et al.: Topological Data Analysis for Portfolio Management of Cryptocurrencies. Ac- cepted at ICDM2019.
– Rivera-Castro, R. et al.: Topological Data Analysis of Time Series Data for B2B Customer Relationship Management. Accepted at IMP2019.
– Rivera-Castro, R. et al.: Topology-based Clusterwise Regression for User Segmentation and Demand Fore- casting. Accepted at DSAA2019.
– E-energy: Trend Report 2009 (ISBN 978-3-9812203-5-3).
Conferences:
IEEE ICMLA 2019: Oral presentation in the main track
IEEE ICDM 2019: Oral presentation at the Workshop on Blockchain Data Analytics
IEEE DSAA 2019: Oral presentation in the main track
IMP 2019: Oral presentation in the track of machine learning applications in marketing
ISNN 2019: Poster presentation
Big Data Moscow 2018: Oral presentation
ICDM 2017: Oral presentation at the Workshop on Data Mining for Service
