Master of Computer Science
University of Adelaide · GPA 6.71/7
Deepening my work in algorithms, distributed systems and intelligent systems while teaching algorithms and data structures.
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I like problems that refuse to be solved casually.
I work across algorithms, performance engineering and applied machine learning. The common thread is optimisation: finding where time, memory or information is being lost—and designing a better way through.
RGBUILD
MEASURE
REFINE
MEASURE
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WORKING THESIS / HOW I THINK
Strong engineering is not a stack of adjectives. It is a chain of decisions you can defend.
I care about the moment a difficult problem becomes understandable: when the right representation exposes structure, a bound cuts away impossible work, or an experiment replaces intuition with evidence.
That mindset moves with me—from exact C++ solvers and cache design to retrieval pipelines and production platforms.
01 / ALGORITHM ENGINEERING↗
PACE 2026 Solver Suite
Three specialised C++ solvers built around one difficult phylogenetic optimisation problem.
Heuristic · Exact · Lower bound02 / PERFORMANCE ENGINEERING↗
Adaptive Range Cache
Ranged-key storage with adaptive replacement, tested across different memory budgets.
99% hit rate at a 30% cache ratio03 / PUBLISHED RESEARCH↗
GasOptiScan
An IEEE-published static-analysis pipeline for finding loop-fusion opportunities in EVM bytecode.
9.6% lower gas on average across evaluated casesTHREE MODES / ONE ENGINEERING MINDSET
How I contribute.
I move between implementation, analysis and experimentation without losing sight of the result.
01
SYSTEMS
↗Build for the real workload.
I turn operational constraints into software that is observable, maintainable and fast enough to matter.
Production platforms · C++ · backend systems02
ALGORITHMS
↗Make the search space explain itself.
I use reductions, bounds and carefully chosen representations to make difficult combinatorial problems tractable.
Exact · heuristic · lower-bound solvers03
INTELLIGENCE
↗Evaluate before claiming.
I treat machine learning as an experimental discipline: clear baselines, measurable behaviour and honest limitations.
Retrieval · ML · empirical evaluationTRAJECTORY / SELECTED MILESTONES
Learning by building.
Building by testing.
Performance-focused engineering
C++ · data systems · adaptive caching
Designed ranged-key storage and adaptive replacement strategies that reached a 99% hit rate at a 30% cache ratio.
Published systems research
GasOptiScan · IEEE
Built a static-analysis pipeline for EVM bytecode that identified loop-fusion opportunities and reduced gas use by 9.6% on average.
B.Tech in Computer Science
IIIT Tiruchirappalli · GPA 8.41/10
Built the foundations in algorithms, systems and software engineering that still shape how I approach technical work.
NEXT / RESEARCH & ENGINEERING
Let's work on something difficult enough to be interesting.
I'm open to research collaborations, PhD conversations and performance-focused software roles.
Start a conversation ↗