Animated diagram: a terminal runs the command infer "Tanaya Datar". It extracts a numeric feature vector, x, from the name, then feeds x through a three-layer feedforward neural network drawn inside a brain outline. Neurons and connections activate layer by layer in a left-to-right wave, and the terminal decodes the network's output into three predicted labels: ML, Bioinformatics, and Genomics.
infer.sh
$ ▌
Brain outline containing a feedforward neural network with three hidden layers A numeric feature vector, extracted from a name by the terminal, is carried into the first layer of a three-layer neural network drawn inside a brain silhouette. Neurons and connections light up layer by layer, then three arrows leave the last layer's neurons, decoded as predicted labels: ML, Bioinformatics, and Genomics.

whoami

Tanaya Datar

🏆 1st Place — WISE Life Sciences Case Competition, 14th Annual National Conference

I work at the intersection of bioinformatics, machine learning, and cancer genomics — building computational tools to make sense of high-dimensional biological data, from single-cell transcriptomes to gene regulatory networks, in pursuit of a clearer picture of how disease develops.

I bridge the gap between data and discovery. The animation above visualizes this process: my name is converted into an input vector and processed through a neural network, surfacing the core pillars of my expertise: bioinformatics, machine learning, and genomics.

See my projects →

currently

Research

Cancer research using bioinformatics and computational biology approaches to study brain tumours.

Building

AI-driven cellular morphological profiling approaches to extract biological insights from imaging data.

Reading

Sequence-to-function models and deep learning frameworks for advancing computational biology.