Learning Machine Learning 2018

Pavlos Protopapas received his PhD in theoretical physics from the University of Pennsylvania. While at Penn he served as the associate director of the National Scalable Cluster Project (NSCP), one of the initial attempts at large-scale distributed computing on a grid-like model. An active collaborator and mentor in the astrostatistics research community, Protopapas holds a research appointment at the Harvard-Smithsonian Center for Astrophysics and also served as senior scientist/project leader for the Time Series Center, a project launched by the Harvard Initiative in Innovative Computing. His research interests lie in planetary transits, the outer solar system, photometric variability, microlensing; in computer science he is interested in large databases and data mining in astronomy, with emphasis on feature extraction, anomaly detection, and similarity searches in time series. At IACS he teaches and advises students as a Lecturer in Computational Science. Together with Efthimios Kaxiras he created Applied Math 207, an IACS core course in stochastic optimization methods popular with students across the social science, science and engineering disciplines.

 

Astrophysicist at the Harvard-Smithsonian Center for Astrophysics and deputy end-to-end scientist for NASA’s Chandra Observatory X-ray Center Data System. BSc in Physics from Universidad Nacional de Colombia. MSc and PhD in Astronomy from Leiden University, the Netherlands. Strong background in multi-wavelength astronomy, statistics, stochastic optimization and astronomical instrumentation. Research interest focuses on the physical properties of star-forming regions both in the Milky Way and in nearby galaxies using ultraviolet to far-infrared observations, as well as the properties of variable astronomical sources derived using machine-learning algorithms for automatic classification and outlier detection. Extensive experience in instrumentation as the responsible for the testing and wavelength characterization of the JWST Mid-Infrared Instrument. Teaching experience includes three semesters as lead TA of the graduate level applied math course “Stochastic Optimization and Monte Carlo Methods”, taught at Harvard University.

Juan is an Assistant Professor at Universidad del Rosario, Colombia, Department of Applied Mathematics and Computer Science. He obtained a PhD in Computer Science from the University of Antwerp, Belgium, in 2010. He was a Research Associate in performance analysis at Imperial College London, UK, Department of Computing, and a Research Fellow in stochastic modeling at the University of Melbourne, Australia, School of Mathematics and Statistics. He is an Associate Investigator of the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). His interests center around the performance analysis of computer systems, especially on software applications, cloud and cluster computing, and optical networking.

Luis Felipe received the PhD. degree in Electrical and Computer Engineering at The Ohio State University, USA, in 2016. He is an Assistant Professor at Universidad de los Andes, Colombia, since 2016. His current research interests include design and analysis of interconnected dynamical systems, large-scale processing of signals, and humanitarian engineering.

Germán received the B.S. degree in electronics engineering from Universidad de Nariño, Pasto, Colombia, in 2008, the M.S. degree in electronics engineering from Universidad de los Andes, Bogotá, Colombia, in 2008, and the Ph.D. degree from Ecole des Mines de Nantes, Francia and Universidad de los Andes in 2016. He was a postdoctoral Fellow with the Research Group in Control and Automation Systems at Universidad de los Andes. He is currently an Assistant Professor in the Department of Applied Mathematics and Computer Sciences at Universidad del Rosario, Bogotá, Colombia. His current research interests include distributed optimization, population dynamics, and game theory.

Dora is a Teaching and Research Fellow at Universidad del Rosario. She obtained the Bachelor degree in Statistics from Universidad Nacional, Colombia, and the Master's degree in Statistics from the Federal University of Pernambuco, Brazil, in 2015. There, she joined the signal processing group and worked in the field of computational constrained DFT estimates. Her current interests are in the areas of data analysis, programming, and graphical design.

*May be subject to change