Research Papers Understanding and Classification, March 2019 - now, with iGEM
Using NLP and information retrieval methods to select phylogenomics research papers containing timetree of rarely described species.

Pilot of a Cognitive Computing System to Analyze Immunization Data, September 2017 - May 2018, funded by Centers for Disease Control
- Modeling complex data with textual and spatio-temporal dimensions. Using NLP techniques to understand documents and social media textual data. Technologies used: word2vec/Glove, NLP, Tensorflow, Python, Django, PySpark, Java, SQLite.

E-commerce Image Classification using Deep Learning, November - December 2017
- Classifying user-provided images (~10 million) from e-commerce website into 5000 categories (ResNet, DenseNet, Python, TensorFlow, TfLearn).

Grocery Sales Forecasting, November - December 2017
- Data integration and feature selection followed by PCA and linear, SVM and ANN regression (TfLearn and Scikit-Learn) to obtain best prediction.

Methylation Variation in Colon Cancer, April - May 2017
- Understanding methylation variation in cancer patients using statistical modeling, complex networks and multi-layer clustering (Python, R). Working with little samples and a lot of features dataset.

Language detection using Deep Learning, July 2015
- Learning RNN and LSTM models to detect language of wikipedia corpus (Python, Lasagne, Theano, Java).