Anannye Naik
CS @ Durham University — AI • Algorithms • Quantitative Systems
Exploring the intersections of computer science, mathematics, and engineering — designing solutions that balance innovation and scale.
About me
Expertise in mathematical modelling: automation, data-driven engineering, and large-scale optimisation. I’ve accelerated analysis from hours to minutes, strengthened high-demand infrastructure, and surfaced hidden patterns in complex data.I love working where quantitative methods and engineering meet, delivering results that are precise, resilient, and scalable across all domains.
Highlights
Automation & AI
For IBM, built large-scale automation pipelines that turned days of preparation into hours, increased coverage from partial to near-complete, and multiplied productivity more than tenfold. At scale, the impact modelled tens of millions in savings — not only in saved time but in opportunities uncovered that would otherwise stay hidden.Systems & Reliability
For Intec, engineered networks and platforms that supported an entire University and global operations, maintaining near-perfect availability through algorithms while serving tens of thousands of daily users. The improvements doubled throughput, cut costs significantly, and raised compliance to enterprise standards — proof that resilience and efficiency can go hand in hand.Scalability & Efficiency
Designed automated workflows that changed how teams worked: hours of preparation reduced to minutes, rework and meetings cut drastically, and insights delivered in a fraction of the time. At scale, this meant faster analysis and sharper decisions: significant financial upside and efficiency across entire departments.
Education
I currently read BSc, MEng Computer Science at Durham University.I was awarded for outstanding academic performance: International Excellence, and SAT Top Scholar.Grades (eq.): A*A*A*A*A*; SAT: 98th percentile.Focus includes quantitative modelling, supported by strong foundations in Mathematics and Physics.Alongside my studies, I take part in societies spanning Mathematics, Physics, Astronomy, Finance, and Computing — reflecting interests that range from abstract problems to practical systems and financial applications.
Astrophysics
My personal interest, one that lies in its complexity: galaxies and data resist easy simplification, where uncertainty is not a flaw but a fact. Working within those mathematical constraints sharpens the value of structure, proof, and transparency. In my technical work, I aim for the same philosophy: systems should be simple where possible, complex where necessary, and stable when stretched to scale.
Music
Music has always been a core rhythm in my life. I play guitar—to explore patterns, tones, and discipline for their own sake. It’s a practice that balances the abstract with the creative, and one I value as much for the process as the sound.
