Adithyan Sujithkumar Email & Phone Number

California, United States

Redwood City, CA, US

Member of the Core Platform team as a Backend Engineer

• One of primary contributors for awpy package (15k downloads and 300 stars on Github), providing data parsing, analytics and visualization for Counter-Strike: Global Offensive (CSGO) data
• Developed graph-based game metric to quantify and analyze ‘map control’ (how much space is each player/team ‘taking up’)
• Created and deployed popular map control visualizations to CS:GO community on Twitter (55k+ impressions) & Github

Seattle, WA, US

• Part of Aurora Storage team developing two new features: Enhanced Binlog, improving overall performance and reliability when enabling binary logging, and Change Data Capture (CDC) Streams, CDC streaming feature for.
• Worked on product development by introducing features to broaden product’s functionality, RCA issues in complex, multi-threaded system, creating various operational workflows, and leading effort to grow and maintain.
• Worked on product testing by leading effort to perform integration testing with multiple Aurora features

Berkeley, CA, US

• Developed transformer-based methods for super-resolution to convert videos in near-real time on CPUs
• Sped up previous models 3x through use of smaller convolutional layers, depthwise convolutions, and other efficient methods and helped develop academic dataset to quantitatively evaluate SR models (Nvidia DLSS.

Philadelphia, PA, US

• Interned within the Philadelphia Phillies R & D department; Developed novel defensive metrics to evaluate infielder performance
• Experimentation was done in Python (scipy, numpy, pandas, scikit-learn) and daily data ingestion was done through a MySQL server
• Developed metrics are now used during holistic infielder evaluation processes for various purposes, such as player development or acquisition

Berkeley, CA, US

• Conducted eye tracking on mice videos to investigate the phenomenon of blindsight through Unity “virtual reality” environments
• Replaced previous geometry-based eye tracking software used by PI with Deeplabcut pose estimation model
• More effectively extracted eye tracking data by 70%; Overall eye tracking model accuracy: ~95%

Berkeley, US

We used Google Earth Engine satellite imagery to identify planting periods in farms around the US with Python and scikit.learn.My work was to create an image processing method to separate unique subplots within farms and classify these subplots as farming or background regions.I utilized edge detection filters to identify unique subplots and leveraged.

Bellevue, Washington, US

I explored numerous machine learning models for the company to implement into their stack and pipeline.One of these models was productionized and beta-tested with potential clients through AWS Sagemaker and Lambda.I also helped conduct ML interviews for Bungee as they searched for their first permanent ML/AI hire.

Berkeley, US

As a member of the New Member Education Program (NMEP) within the Machine Learning @ Berkeley group (ML@B), I spend on average about 15 hours a week learning the various principles and foundational knowledge for a variety of machine learning algorithms and topics.I worked with my group on implementing an end-to-end machine learning pipeline utilizing.

Oak Ridge, TN, US

During the summer after my senior year of high school I worked on a project in the Computational Data Analytics Research group to predict and simulate traffic flow through the usage of various machine learning methods, such as 3D convolutional neural networks.

Oak Ridge, TN, US

I continued my work within the ISML division on a project involving identifying mitochondria in an electron microscopy dataset. My work included creating an ML pipeline to greatly accelerate the process of obtaining training and testing data for use in a convolutional neural network (accelerate the process from a few weeks to a few minutes).

Oak Ridge, TN, US

I worked as a research intern in the Imaging, Signals, and Machine Learning (ISML) division. In collaboration with St. Jude Children's Hospital, I worked on a project to identify firing neurons in the auditory cortex of a mice's brain through the usage of machine learning and neural networks.

Bachelor Of Science - Bs, Electrical Engineering And Computer Science

Education record