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Schedule Interview NowMy name is Vamshi Krishna K. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Computer Vision, Machine Learning, Python, PyTorch, Deep Learning, etc.. I hold a degree in Bachelor of Technology (BTech), Master's degree. Some of the notable projects I've worked on include: MedQuAD Chatbot for Medical Question Answering, Data Visualization and Exploratory Analysis of MIMIC-III Clinical Data, Waypoint Prediction for Autonomous Driving Using NN,TransformerPlanner, Object Detection in wild using Defilters, Capsule-Vision (Exploring Self-Supervised Learning). I am based in Karimnagar, India. I've successfully completed 5 projects while developing at Softaims.
I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.
Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.
I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.
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Centre for Brain Research, IISc
The MedQuAD Chatbot project is a sophisticated AI-driven conversational agent designed to provide accurate and relevant answers to medical-related questions. This chatbot is trained using the MedQuAD
The MIMIC-III (Medical Information Mart for Intensive Care) database is a widely used dataset for clinical research, containing de-identified health data from ICU patients. This project focuses on exp
Developed neural network-based planners to predict future waypoints for autonomous driving. Designed an MLP-based planner for efficient waypoint prediction and a Transformer-based planner for enhanced
This work focuses on improving object detection performance by addressing the issue of image distortions, commonly encountered in uncontrolled acquisition environments. High-level computer vision task
Exploring Self-Supervised Learning with U-Net Masked Autoencoders and EfficientNet B7 for Improved Classification. Create robust AI models that can effectively classify abnormalities based on the prov
Bachelor of Technology (BTech) in
2017-01-01-2020-01-01
Master's degree in