Amar Kumar Mandal

I started out as a backend developer, and for two years that meant real production work implementing end-to-end encryption, multi-factor auth, microservices talking over a Kafka cluster, the whole system monitored on Prometheus and Grafana so we'd catch failures before users ever felt them. I genuinely liked the system-design side: drawing service boundaries, thinking about scale, making distributed system work in tandem.

What I liked less was that the day-to-day slowly became routine: another API, another feature. I wanted harder problems.

The shift came during my master's. My research kept pulling me toward machine learning: my first accepted paper looks at the privacy–utility tradeoff in differentially private classifiers, and the more I dug in, the more I realized the problems I actually wanted to spend my time on lived at the intersection of ML, math, and security. It's challenging in the way backend stopped being: real problem-solving, not routine.

So that's where I am now: an Erasmus Mundus scholar in Applied Cybersecurity (CyberMACS) at Kadir Has University in Istanbul, bringing the engineering discipline I built shipping production systems to machine learning that's private and secure by design.