FigureAsia 35 Under 35 · Science
Sneha Goenka
Age 32 · Bioinformatics compilers and algorithms · India / United States
Designer of compilers that turn recursive biological algorithms into high-performance implementations.
- Approximate age at the edition eligibility date
- 32
- Field
- Computational science
- Country or region
- India / United States
- FigureAsia U35 Assessment
- 90.3 / 100
Profile
Career and documented record
Biological sequence algorithms often begin with a clean recurrence and end in years of architecture-specific optimisation. Sneha Goenka's 2026 FILTR framework separates that process into recursion, pruning and scheduling, then compiles the specification into optimised C++.
Across the reported bioinformatics benchmarks, generated implementations ranged from near parity with expert code to substantially faster performance. The important point is not a single 30-fold peak; it is that a reusable compiler can explore optimisation choices that have traditionally depended on scarce manual expertise.
Goenka's research sits between algorithms, compilers and biology. It makes scientific computing itself a research object, with the potential to shorten the path from a new dynamic-programming idea to a performant tool other scientists can use.
FigureAsia selection
Why Sneha Goenka is on the list
Goenka is selected for attacking an invisible but material limit on biological research: the cost of turning an algorithm into efficient software. FILTR is a completed systems contribution with clear benchmarks, reusable abstractions and consequence across more than one sequence-analysis task.
Verified work
The 2025–26 record
FILTR
Introduced a recursive compiler framework separating algorithm, pruning and hardware schedule.
Bioinformatics benchmarks
Reported performance from 0.95× to 30× expert implementations across tested workloads.
Independent laboratory
Established a Princeton programme at the intersection of algorithms, compilers and genomics.
Field context
The work in its field
Bioinformatics depends on dynamic programmes whose theoretical form can be far removed from efficient execution. Compilers can broaden access to optimisations now concentrated in a small number of expert teams.
FigureAsia U35 Assessment
Assessment breakdown
90.3out of 100
Substantive 2025–2026 contribution
17.4 / 20
Introduced a recursive compiler framework separating algorithm, pruning and hardware schedule.
Verified scientific impact
13.4 / 15
FILTR addresses a cross-cutting computational bottleneck and reports concrete performance across multiple biological workloads.
Originality and distinction
9 / 10
The distinction lies in compiling recursive rules, pruning logic and execution schedules as separable objects.
Field influence
9.1 / 10
Within computational science, the work matters because it shifts a live question in bioinformatics compilers and algorithms rather than merely attracting attention.
Individual agency
9.1 / 10
Goenka leads the research programme and is a principal author of the framework, with implementation credited to the team.
Durability and trajectory
4.6 / 5
As Assistant Professor of Electrical and Computer Engineering at Princeton University, Goenka has a platform to carry the work into its next stage.
Asian significance and global relevance
4.6 / 5
Indian scientist educated at IIT Bombay and now leading computational research at Princeton.
Evidential validity and reproducibility
7.3 / 8
Benchmarks are stated as ranges against named baselines and do not imply universal acceleration.
Advance in scientific knowledge
6.5 / 7
The work shows how domain-specific recursion can be transformed without hard-coding every optimisation.
Translational or methodological utility
4.6 / 5
It can reduce engineering time and expand access to high-performance sequence analysis.
Responsible research stewardship
4.7 / 5
Generated speed remains subordinate to correctness, transparent baselines and reproducible code paths.