Dr. Juan Camilo Orduz
Mathematician & Data Scientist
I have a PhD and Master degree in Mathematics from Humboldt Universität zu Berlin under the supervision of Prof. Jochen Brüning. My graduate studies were supported by the Berlin Mathematical School. Here I share my experience. Before coming to Berlin I did two bachelor degrees: Mathematics and Physics at Universidad de los Andes.
My research interests are differential geometry, topology and geometric analysis, in particular variants of the Atiyah-Singer Index Theorem for singular spaces. Currently I’m working in topics around data analysis, statistics and machine learning.
I am also interested in education and knowledge sharing.
You can find the code associated with the blog posts on this GitHub repository.
01/04/2018-. Data Scientist, TD Reply GmbH, Berlin, Germany.
- Sales forecast ARIMA + ML • Media Mix modeling and ROI optimization • Product lifecycles analysis • Social media text data mining: n-gram networks, topic modeling and time development • Social network analysis • Geolocation modeling • Scalable automatic data integration from various sources via APIs • Dynamic data visualization • Member of the ProBonoProData Team supporting and sharing knowledge with NPOs.
01/07/2017-01/04/2018 Junior Data Scientist, TD Reply GmbH, Berlin, Germany.
01/01/2017-30/06/2017 Trainee - Data Analyst, GoEuro, Berlin, Germany.
- Integrate provider data from various sources into the search engine • Normalize and geo-reference data from different sources • Automate and define new tools to scale and increase efficiency for the data quality program.
2014-2015 Student Representative, Berlin Mathematical School, Berlin, Germany.
- Member of the organization committee of the 3rd−BMS Student Conference.
2008-2010 Teaching Assistant, Universidad de los Andes, Bogotá, Colombia.
- Courses: Linear Algebra, Basic Physics II, Riemannian Geometry.
- 01/2018-03/2018 Data Scientist, CorrelAid Network, Dashboard Project for Projekt Seehilfe e.V.
- 03/2011-08/2011 Mathematics Teacher, ColombiaCrece, Bogotá, Colombia.
- 06/2007-08/2007 Camp Counselor, Skylake Yosemite Camp, Wishon, CA 93669, USA.
2014-2017 PhD in Mathematics (Magna Cum Laude), Humboldt Universität zu Berlin, Berlin, Germany.
Advisor: Prof. Jochen Brüning
Title of the Thesis: Induced Dirac-Schrödinger on quotients of semi-free circle actions.
2011-2014 M.Sc. Mathematics, Humboldt Universität zu Berlin, Berlin, Germany.
2005-2011 B.Sc. Mathematics (Cum Laude), Universidad de los Andes, Bogotá, Colombia.
2005-2011 B.Sc. Physics (Cum Laude), Universidad de los Andes, Bogotá, Colombia.
- Spanish: Native proficiency.
- English: Full professional proficiency.
- German: Professional working proficiency.
Publications & Preprints
- The \( S^1 \)-Equivariant signature for semi-free actions as an index formula, J Geom Anal (2018)
- Induced Dirac-Schrödinger operators on \( S^1 \)-semi-free quotients, ArXiv (2017)
Notes & Expository Articles
- \(S^1\)-Equivariant Dirac operators on the Hopf Fibration (2018)
- \(L^2\)-Cohomology and the Hodge Theorem, BMS Student Conference (2016)
- \(C^*\)-Algebras and the Gelfand-Naimark Theorems, BMS Student Conference (2014)
- The Signature Theorem, Villa de Leyva Summer School (2013)
- What is a Dirac Operator?, What is Seminar (2012)
- Introduction to the Chern Class (Dirac’s Monopole), Index Theory Seminar (2012)
- Introduction to the Moment Map, Villa de Leyva Summer School (2011)
Data Analysis and Machine Learning
- Machine Learning (Coursera) Tools: matlab
Deep Learning Specialization (Coursera) Tools: numpy, tensorflow, keras.
- Neural Networks and Deep Learning
- Improving Deep Neural Networks
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
Applied Data Science with Python Specialization (Coursera) Tools: scipy, numpy, pandas, matplotlib, scikit-learn, nltk, networkX.
- Introduction to Data Science in Python
- Applied Plotting, Charting & Data Representation in Python
- Applied Machine Learning in Python
- Applied Text Mining in Python
- Applied Social Network Analysis in Python
- Econometrics: Methods and Applications (Coursera) Tools: pyton: statsmodels (python).
- Bayesian Statistics: From Concept to Data Analysis (Coursera) Tools: R.
- Bayesian Statistics: Techniques and Models (Coursera) Tools: R and JAGS.
- Information Visualization: Programming with D3.js (Coursera)
- Functional Programming Principles in Scala
- Functional Program Design in Scala
- Parallel Programming
- Big Data Analysis with Scala and Spark
- Functional Programming in Scala Capstone Protect
Selected Talks and Events
07/2018 On Laplacian Eigenmaps for Dimensionality Reduction, PyData Berlin 2018, Berlin, Germany.
08/2017 Introduction to Bayesian modeling with PyMC3, Python Users Berlin (PUB), Berlin, Germany.
07/2017 Workshop on Loop Spaces, Supersymmetry and Index Theory, Chern Institute of Mathematics, Tianjin, China.
07/2017 PyData Berlin, Hochschule für Technik und Wirtschaft, Berlin, Germany.
08/2016 Focus Program on Topology, Stratified Spaces and Particle Physics, The Fields Institute for Research in Mathematical Sciences, Toronto, Canada.
06/2015 Summer School: Geometric and Computational Spectral Theory Université de Montréal, Montreal, Canada.
09/2014 Trimester Program: Non-commutative Geometry and its Applications, Hausdorff Research Institute for Mathematics, Bonn, Germany.
- Sports, music and photography.