Roberto Alonso

Working in the Data landscape: Data Science & Data Engineering & Data Management

Conducting work around Anomaly Detection using Machine Learning and Graph Analytics: - Built Proof of Concepts using core Machine Learning and Data Mining methods in the context of anomaly detection. Developed mostly in Python - Developed a graph analytical tool based on the requirements set by our investor. Developed in Java and used Elasticsearch as storage mechanism. - Gave insights about potential Data Science solutions in the intersection between graphs and cybersecurity.

Worked on the detection of patterns and anomalies in graphs: - Designed a novel graph mining model to detect insightful patterns in graphs arising in e-commerce, German laws (the BGB), and citations, among others. The model was developed in Java - Built a predictive model to identify a suitable time period in the context of anomaly detection on DNS servers - Successfully guided Master students throughout their research papers

Worked in the area of anomaly detection in computer networks: - Built a social network based model to spot anomalies on DNS servers. From this work two research papers were published. - Developed scripts in Perl, Matlab and Python to effectively visualize attacks in network traffic - Evaluated several times as outstanding lecturer according to student opinion polls

- Developed and deployed a system to capture on-line resumes and generate reports. Developed in ASP.NET and MS SQL - Developed webpages in Flash. My solutions involved creativity as they were intended for high school students

Computer networks and graph mining