Treffit.fi -- Acquired by City Digital Group:

End-to-End Machine learning pipeline for Automated image processing + entity extraction based on

Resnet50 Neural network architecture

End-to-End Machine learning pipeline for semantic similarity based automated spam banning system based on auto-encoders and, Locality Sensitive Hashing for efficient retrieval at scale

[Python, Numpy, Tensorflow, AWS Lambda]

Aller miscellaneous/other:

• Dating related, recommendation system

• MariaDB -> AWS parquet based pipeline to leverage Athena Columnar database for analytics

• MSSQL to snowflake transpiler in order to fully migrate MSSQL based internal services into snowflake

• Python pandas based wrapper to guarantee a lower expense in snowflake, by caching existing results.

• Docker based airflow deployments and automatic pipeline-creation from custom files in s3

• Thorough training of 4 different staff members in topics ranging from python to machine learning, snowflake and, airflow

• - Acquired by Epic Games

Co-lead the preparations and implementations for the Kamu Junction challenge 2017 on Europe's Largest Hackathon: https://hackjunction.com/challenges/play-beautiful [https://junction2017.devpost.com/]

As part of the core business, work to aid in the detection of cheaters & binary data corruption machine learning models Included:

Recurrent Neural Network LSTM based multiclass classification for repeated user fingerprinting.

Gradient boosted trees based Aimbot Detection,

Recurrent Convolutional Autoencoder based Similarity-based information retrieval engine for binary-data similarity.

In order to deal with anomalous events in our live user data:

Kafka streaming data anomaly detection engine algorithms included:

• Convex Hull based anomaly detection

• Bayesian Changepoint shift detection

• Kolmogorov smirnof test among others

To deal with large scale data -> approximate & streaming algorithm based online learning:

• Streaming statistics generation at O(1) space complexity

• Streaming clustering algorithms

• - Acquired by SimpleView

Machine Learning Models included:

Network connectivity models for user engagement.

Long short term memory based Price optimization for hotel booking data enriched with environmental and event data present in the UK's most thorough destination database

Data Engineering:

Defined the specification for a message queue based data pipeline to feed and enrich a large Graph Database for user engagement and click-through Analytics

General:

Weekly presentations and constant client interaction with numerous UK government Tourism Entities.

Quantitative Petri-net :

Developed a Quantitative petri-net network with a Gillespie Algorithm implementation (Monte Carlo simulation) in order to understand signaling network connectivity effects for NFkB-NrF2 crosstalk.Involved

modeling networks, and resulted in predicting mechanism of drug action without physical experiments