Skillocity Research Teams

Research Teams

At Skillocity, we are highly passionate towards research to uplift humanity as a whole. We appreciate all researchers around the globe and to contribute to the world, we started Research Teams. Under this program, we constituted some research problems we found interesting and impactful and invite high school students to work with us. Both the team leads have prior experience with published research papers.

Students not only learn the research process but also research ethics and finding the right journal as we noticed misinformation causing students to ‘publish’ plagiarized papers in predatory journals.

Problem Statements

In this research group we aim to use Probability Theory, Stochastic and Markov models to study the dynamics of Indian monsoons. Interannual variability in rains in the tropical and subtropical regions are being studied and stochastic, statistical modeling is being done to understand the elements of Indian monsoons and make quantitative estimations for the same.

Team: Pranav Sawant, Anshuman Shukla, Gurnoor Singh Gujral

Over 3,564 accidents occurred in India past year were a direct cause of potholes on roads. This raises concerns over road condition in India. While the government tackles it the traditional way, a fix is needed in the cars itself. This team is working on optimizing camera video feed pipeline based live feature detection on Indian roads to alert the driver in real time. To tackle night-time driving, the model needs to be optimized to detect features in low light coupled with the vehicle’s night lights.

Team: Anshuman Shukla, Pranav Sawant, Koninika Patil

Player movement analysis feedback system based on score prediction is an important aspect to train players. Such systems are usually costly and do not exist for Tennis specifically. Given the poor situation of tennis training in India, we aim to develop a deep learning model to provide feedback and help improve a player’s performance at the lowest operational cost. The team utilizes custom recorded database to create this model.

Team: Pranav Sawant, Anshuman Shukla, Koninika Patil

JWST has been producing highly important data in a large quantity made available publicly using the MAST platform. Important results are being announced each month such as the most redshifted galaxy at z=14. Star Cluster formation is a gateway to understanding dynamics and gas constituents in the early universe potentially paving the way to understand galactic and stellar evolution. This team uses the MAST data to analyze and compare trends with previously discovered star clusters.

Team: Anshuman Shukla, Pranav Sawant, Mollie Adams

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