ikeGPS
Colorado, USA (Remote)
Artificial Intelligence Engineer (contract)
December 2024 - Present
Currently working on developing and fine-tuning computer vision models for object detection, segmentation, and keypoint prediction using MMDetection library.
Created data generation pipeline for synthetic dataset using the Unity Perception package.
KIS.AI
Hyderabad, India
AI/ML Intern
May 2024 - July 2024
Implemented end-to-end NLP pipelines for Named Entity Recognition (NER), Knowledge Graphs (KG), using SpaCy Transformers; leading to reduction in computation costs and increased inference speeds by 35%.
Duodecimal
Hyderabad, India (Hybrid)
Deep Learning Engineer Intern
October 2023 - March 2024
Designed proof-of-concept (POC) to transition from traditional sensor based systems to AI camera-based solution. Deployed POC to multiple manufacturing chains, leading to 40% increase in production efficiency.
Mahindra University
Hyderabad, India
Research Assistant
January 2023 - December 2023
- Developed new approach for underwater image dehazing using superpixel segmentation with UNTV model in YCbCr color space to achieve superior transmission maps and image enhancements.
- Accepted for paper presentation at International Conference on Video and Image Processing (ICVIP'23) at Kyoto University, Japan.
Center for Sustainable Infrastructure and Systems (CSIS), Mahindra University
Hyderabad, India
Research Assistant
October 2022 - May 2023
- Created a solution to calculate damaged area and severity percentage from images using deep-learning based segmentation algorithms achieving accuracy of 65% - 75%.
- Accepted for Paper presentation at Stanford University at International Workshop on Structural Health Monitoring (IWSHM'23).
- One of fourteen presenters for Prototyping Round (IWSHM'23).
Hewlett Packard Enterprise (HPE)
Kent Ridge, Singapore
Deep Learning Intern
June 2022 - July 2022
Gained hands-on experience in cloud-based Machine Learning (ML) deployment. Built an ML pipeline to train and evaluate classification models like VGG and ResNet. Deployed the best-performing model on Microsoft Azure for real-time predictions. Achieved 84% accuracy on an MRI dataset.
National University of Singapore (NUS)
Kent Ridge, Singapore
Academic Intern
June 2022 - July 2022
Explored Brain Cancer Classification project using CNNs: VGG-16, VGG-19, and ResNet, achieved 84% accuracy. Implemented data augmentation methods to avoid over-fitting and increase model generalization.
