Reetam Taj

Reetam Taj is a Full-Stack Developer at Arolytics. Reetam previously worked as a Machine Learning Engineer at the Department of National Defence from August 2019 to February 2020. While at the Department of National Defence, Reetam built a real-time Machine Learning based Network-based Intrusion Detection System (NIDS) to predict, detect, and classify DDoS attacks. Reetam also participated in requirement meetings to understand the business requirements and suggested the state-of-the-art solutions after conducting research. Involved in sprint planning in an Agile environment. Differentiate and classify the network traffic based on their flow using clustering techniques includes partitioning methods, density-based methods, model-based clustering, and hierarchical clustering. Analyzed the network elements graphical models, high dimensional learning, the theory of convex and non-convex optimization. Developed a dynamic and context-aware process to extract features based on the type of DDoS attack. Built a hybrid neural network to identify the malicious traffic which is undetectable by commercial IDS enabled platforms. A neural network distillation process was implemented to interpret the performance and decision factors of learning models.

Reetam Taj has a Master's degree in Computer Science from Dalhousie University and a Bachelor of Technology - BTech in Computer Science from West Bengal University of Technology, Kolkata.