Dhruv Makwana is an AI Engineer with 6 years of hands-on experience building and deploying deep learning systems across computer vision, NLP, and multimodal applications, grounded in a strong academic record (B.E. Computer Engineering, 9.16/10). He has shipped production solutions that materially cut fraud and manual effort—e.g., a cheating detection system with 95% accuracy that reduced misconduct by 90% and an agentic LLM-powered chatbot that halved reporting time for law enforcement workflows. Dhruv blends research and product delivery, with publications in WACV, ICDAR and Elsevier on topics from low-light enhancement to nuclei segmentation, and practical expertise optimizing models for cloud, edge, and embedded platforms using TFLite, TensorRT and mixed precision. His prior work spans edge AI, pose estimation for robotic pick-and-place, and time-series fault diagnosis with near-state-of-the-art accuracy, reflecting both algorithmic depth and systems-level performance tuning. An active open-source contributor, he has contributed backend connector implementations to the popular Airbyte data-integration project, demonstrating comfort in engineering at scale beyond core ML components. Based in Ahmedabad, he’s focused on trustworthy, efficient AI systems and seeks collaborations that move cutting-edge research into reliable production.
6 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 9.16/10 CGPA, Bachelor of Engineering - BE, Computer Science, 9.16/10 CGPA at LJ institute of engineering and technology
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Role in this project:
Back-end Developer
Contributions:50 reviews, 2 commits, 76 PRs in 19 days
Contributions summary:Dhruv primarily contributed to building new data integration connectors for the Airbyte platform. Their work involved implementing new data sources, like Gutendex and The Guardian API, integrating them into the existing framework. This involved creating source definitions, setting up acceptance tests, and handling data extraction pipelines. The user also made improvements to existing connectors, such as adding functionality to the Jira and Zenefits connectors.
Contributions:33 commits, 39 pushes, 1 branch in 7 months
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