Hello World! I'm Neha. I hail from a pure Computer Science background and you can tell that about me by my obsessive use of binary logic in everyday life. Jokes apart, I'm a researcher in the field of medical image analysis because I love to segment and analyze MRI, CT, and all kinds of scanned images of the brain. I develop deep learning models to achieve better performance and higher segmentation accuracy. Basically, my Neural Nets emulate the functioning of the human brain in order to analyze a scan of the actual brain so that we can better understand and identify issues with it.
I'm currently a Software Engineer at Envestnet Yodlee, Bengaluru. As a part of the Site Reliability Engineering team, my day-to-day professional life includes developing monitoring dashboards, enabling synthetic monitoring, writing scripts in python and shell, and analyzing as well as resolving incidents within the SLA.
Apart from my academic and professional life, I am passionate about sustainability and I run my own business venture, Gaia. At Gaia, we curate sustainable, ethically-sourced, organically-grown products from local artisans and small businesses into handmade boxes of joy we like to call “Eco-friendly Hampers.” Developing & maintaining the website, managing the operations & delivery, sourcing & curating the products, creating & posting the blog content, styling & marketing the products for Gaia are just some of the things that keep me going every day!
Used Wordpress, Woocommerce and CSS to build an e-commerce website for a self-owned sustainable living brand, Gaia. Gaia is a green venture that offers eco-friendly gift hampers comprising of local and biodegradable products curated from all over India.
Built a composite deep neural network conflating fractal networks and the U-Net model for state-of-the-art segmentation results. Publication: CSNet: A New DeepNet Framework for Ischemic Stroke Lesion Segmentation, Computer Methods and Programs in Biomedicine, Elsevier.
Designed an EBGAN model exhibiting higher stability than regular GANs and demonstrating better segmentation performance.EBGAN employs an energy function to discriminate between the real and synthetically generated samples, analogous to probabilistic GANs
PIRNet, based on a novel technique called Pyramid Pooling, together with the combination of inception blocks and residual connections, has been applied to the task of brain MRI segmentation of cerebrospinal fluid, gray matter, white matter, and background over several loss functions.