Harsh Dave / Computer science · Statistics · Computational genomics

I like complicated systems. I build useful ways through them.

I’m Harsh—a computer scientist, statistician, computational genomics researcher, and builder. I follow questions across software, data, biology, AI, sports, and the everyday systems I want to make more useful.

“I rarely accept ‘that’s just how it works’ without asking several more questions.”

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In the lab

Positive selection in Mycobacterium tuberculosis

Ioerger Lab · Texas A&M

Away from the screen

Lifting, badminton, soccer, basketball, teaching, and trying too many new tools.

Now / Texas A&M

Computational genomics in the Ioerger Lab.

I’m pursuing an M.S. in Computer Science while studying positive selection in Mycobacterium tuberculosis using Python, Bayesian modeling, and high-performance computing across approximately 4,000 genes.

How I work

Build the system. Find the signal. Explain why.

01

Build systems

Turn an unfinished question into software people can actually use—from local-first personal tools to AI, data, and cloud systems.

02

Find signal

Use statistics, reproducible analysis, and explicit uncertainty to separate evidence from noise.

03

Explain why

Make the machinery legible—whether it is a model, a research pipeline, a sports argument, or a daily routine.

Independent systems / 07

Built around friction I kept noticing.

Seven working systems, each with one clear job. The full portfolio keeps the deeper project and experience record.

01DaymarkFlexible habit tracking for imperfect routines.Personal tool 02SlateA daily plan beside the flexible work that fills it.Planning 03PickLedgerA public record for accountable sports predictions.Data product 04MtbScopeComparison-first tools for tuberculosis genomics.Research software 05SiftResearch reading with claims kept close to their sources.Research tool 06FareLow-friction nutrition logging with durable history.Personal data 07GymTraining programs, sets, and progress without the noise.Training
Portfolio The deeper record: experience, research, projects, education, and the thinking that connects them. Enter →

Still curious

The same instinct, applied in different places.

Biology Disease, evolution, drug resistance, and useful research interfaces.

AI systems The routing, accelerators, context, and failure modes behind an answer.

Movement Lifting, sport, technique, recovery, competition, and measurable progress.