Oct 2024 – Apr 2025 · 6 mos · United States

• Unmanned Systems Lab @ Texas A&M
• Working on building pipelines and optimizing models for off-road semantic segmentation to enhance perception in autonomous vehicles

Aug 2023 – Jul 2024 · 11 mos

• Worked with Prof. Kursuncu at GSU and Prof. Ponnurangam on multimodal hateful memes detection.
• Developed an MMBT model using deep learning, NLP, and knowledge graphs to analyze memes, achieving 81% accuracy.

Aug 2023 – Feb 2024 · 6 mos · Hyderabad, Telangana, India · On-site

• Collaborated with Prof. Karthik Vaidyanathan to develop adaptive software systems using reinforcement learning methodologies to reduce server cost and enhance user experience.
• Automated server adjustments and dimmer value changes using Q-Learning and Proximal Policy Optimization. Current model surpasses existing baselines.

May 2023 – Jul 2023 · 2 mos

• Built a scalable Zoom recording portal on Oracle Cloud.
• Achieved 95% transcript accuracy by integrating an advanced speech-to-text model.
• Used BRIO LLM for summaries, cutting review time by 70%.

Nov 2022 – May 2023 · 6 mos · Dubai, United Arab Emirates · Remote

• Worked on smart contracts to fractionalize real estate using ERC20 and ERC721 tokens.
• Built a proof-of-concept full-stack interface to interact with the smart contract.
• Explored ERC1400 tokens to increase security.

Apr 2022 – May 2023 · 1 yr 1 mo · Hyderadabad

• Worked under Prof. Ashok Das on the application of blockchain in the Internet of Drones(IoD) environment. Used CBOR Object Signing and Encryption to allow authentication and access control between drones.

Jan 2022 – Apr 2022 · 3 mos · Remote

• Automating Visual Merchandising by creating dynamic forms to take input from owners and running ML algorithms to check if store design is complying with requirements.
• Using MERN stack, Image Similarity Algorithms, Object Detection Algorithms

Apr 2018 – Feb 2019 · 10 mos · Remote

• 'Smart Dividers'- A unique solution to traffic and tailgating which would revolutionise travel by creating a road system in which moving road dividers, controlled by ML algorithms, allow for smart land allocation based on traffic density on either side of the road.
• Led 8-month research and design thinking period with 4-person team to discover causes of traffic in Dubai.
• Built virtual prototype of AI-driven dividers to divide roads according to density of traffic as a solution to the problem identified through research.
• Pitched idea to NUS and NTU university professors in Singapore and the Road and Transport Authority in Dubai.
• Received recognition for Best Presentation and Research Methodology out of 15 design projects.