Vansh Kumar Email & Phone Number

Dallas, Texas, US

Led a team to build a telehealth platform & patient apps to facilitate measurement-informed care for individuals with Substance Use Disorder

Dallas, Texas, US

Mountain View, CA, US

TL of a team of 3-4 engineers focused on improving video ads forecasting quality for the media planning use case. Work includes:- Setting OKRs / providing technical direction and mentorship- Monitoring and improving forecasting quality through a large variety of efforts- Increasing user trust in forecasting tools- Adding forecasting support for new.

Mountain View, CA, US

Working as a Google.org fellow with the Morehouse School of Medicine, serving as TL for the project. Setting technical direction and planning work for a distributed team of ~7-8 engineers. Helped build and launch healthequitytracker.org

Mountain View, CA, US

Mountain View, CA, US

Mountain View, CA, US

Worked with two classmates from Caltech and UChicago to create a website for college applicants to connect with current undergraduates at their dream school. Built with Ember JS, Ruby on Rails, and node JS. Validated business ideas by interviewing customers and iterating.

Mountain View, CA, US

Data mining in Python and Java to determine what makes ads more successful than others. Tested unsupervised learning (k-means, PCA), supervised learning (SVM), and recommendation (collaborative filtering using weighted alternating least squares) techniques

Pasadena, CA, US

An essential function of computer vision algorithms is to perform object classification within images. A specific problem within the field of object classification is bird species classification, a task which is difficult even for humans. The goal is not to just develop an algorithm in order to solve this specific problem, but rather to extend the.

Fairfax, Virginia, US

Pulse-coupled neural networks (PCNNs) are a specific kind of neural network that are meant to emulate the function of a cat's visual cortex. The network model underneath PCNNs is a linking-field model that allows the network to sustain pulse bursts. In the context of an object recognition application, given that a neuron corresponds to a pixel in the.

Fairfax, Virginia, US

Neural networks are a well-known machine learning technique. Machine learning through neural networks is the process of teaching a network to recognize a set of training vectors and training outputs by producing the correct output for each vector. This produces generalized behavior, so the network can recognize similar vectors that it has never been shown.

Bachelor Of Science (B.S.), Applied Computational Mathematics And Computer Science (Double Major)

Education record