Doing master thesis with the Machine Learning Group at Ericsson Research, Stockholm. Thesis is on “Deep learning for Anomaly Detection on Temporal Data”.
Part of another project on anomaly detection and predictive maintenance using sensor data from manufacturing production line.
Using LSTMs, autoencoder, Gaussian Process and Bayesian optimization.
Built a dynamic search ranking framework to rank search results by balancing listing relevance, agent lead demand and paid subscriptions.
Developed the search backend using Apache Solr, and named entity recogniton.
Executed machine learning projects including click-through rate prediction, and spam classification.
Worked with Java, R, mongodb, Apache Solr.
Part of Oracle FUSION Middleware development team. Oracle Fusion is Oracle’s cloud based suite of enterprise solutions.
Worked on Fusion Product Information Management tool which is part of from the Fusion Supply Chain Management family. PIM’s customers included Boeing, Posco, GE.
Build a CNN based deep learning model to learn and break captchas.
The project was done as part of deep learning course at KTH with Tharidu and Dominik.
Trained the model on a dataset of 200,000 captchas on Nvidia Tesla K80 GPU an AWS EC2 instance.
Tensorflow was used as the deep learning library.
The model achieved an accuracy of ~98%.
The project was done as part of Visualization course at TU/e, with Pat.
Developed an interactive D3.js website (live website).
Intuitive & iteractive graphs and maps to understand asylum request data.