Akshay Veeragandham

A proactive computer science student proficient in Java and Python seeks an internship to apply strong programming skills and theoretical knowledge. Has completed projects in artificial intelligence and machine learning, demonstrating problem-solving capabilities. Aims to contribute to real-world applications while gaining valuable industry experience.

Music Library (Jan 2024-Feb 2024)

• Using Java and a VM, created a library holding multiple types of music. From the library, the user is able to retrieve different types of music based on genre, length, and number of streams. Done during project week in my CS 400 (Programming 3) class at university.

ML Research on Autonomous Electric Cars (Oct 2022 - May 2023)

• I have read documentation and explored literature reviews to learn about methods to solve autonomous driving. Along with a small team, I have been researching deep reinforcement learning to train a reward model that enables a Raspberry-Pi car to drive autonomously under real-life conditions.

DonationConnect (Jun 2022 - Jun 2023)

• I have engaged my friends to create a solution that combats misinformation about charities. Then, we started to develop a website donationconnect.org that organizes data about reliable charities. I have designed and coded a webscraping algorithm using Python and created a database to collect and store 100+ charities’ data on the internet.

Invoice Automation (Internship) (Jun 2022 - Jul 2022)

• As part of an internship, I have explored product lifecycle to understand how to take a product from ideation to the deployment stage. Then, I designed a framework for the process of creating invoice PDFs from large volumes of payment data in excel and developed automation using Python and Pandas, saving 240 hours per invoice. Along the way, I have learned Django to enable scalable automation in a web application.

Autonomous Cars in a Video Game (Dec 2021 - Jan 2022)

• I have learned many ML models such as neural networks. Then, I developed autonomous cars in a video game by creating an ML model to detect the road, turns, and acceleration with 70% accuracy. As an ambassador for Inspirit AI, I have spread knowledge to students and schools through blogs and videos.

Optimizing Wind Turbine Energy Output (Nov 2021 - Dec 2021)

• I have designed a data manipulation & pre-processing framework and created a plan for ML model implementation. Then, I coded a scalable random forest model using Python to analyze the most influential features that affect wind turbine energy output at an accuracy of 91%.

Healthcare Chatbot (Jul 2021 - Aug 2021)

• Then, I created a plan with a list of actions and detailed procedures for them along with timelines. Finally, I coded the project using an NLP to analyze users’ words and understand their requests with multi-threading to support 9999 customers simultaneously.

Facial Emotion Detector (Jun 2021 - Jun 2021)

• I have learned many AI models such as regressions and computer vision. Then, I developed an emotion detector by creating a computer vision model to detect emotion based on tracker movements and improved the accuracy of the model to 65%.