Anish Chhaparwal Email & Phone Number

▪Boosted the impact of Qure.ai's lung health products on over 4 million lives annually across 50+ countries by developing Computer Vision algorithms, which were independently confirmed to match or outperform radiologists in top medical journals such as Nature and The Lancet▪ Principal architect of a scalable end to end training framework used to train over 100 models for 20+abnormalities on chest X-rays, streamlining collaboration in the team & reducing training time by 40%▪ Enhanced data usability by processing over 50 million medical records via Extract, Transform, Load (ETL) pipelines, culminating in a curated trainset of 3.2 million and a testset of 300k entries▪ Safeguarded business continuity by mapping critical data across 15+ devices (external hard drives & NAS) and backing up over 450 TB of data▪ Streamlined the experiment tracking process and enhanced record-keeping by logging various metrics, image samples, and segmented outputs into ClearML, consequently establishing a reliable audit trail▪ Developed a post-training module that enabled selecting, pruning, and exporting of model ensembles into TorchScript and ONNX, improving deployment flexibility across various runtime environments▪ Presented “deep learning algorithm for early detection of malignant lung nodules” at the InternationalAssociation For The Study Of Lung Cancer 2022

Bengaluru, Karnataka, India

▪ Implemented a machine learning solution to mitigate duplication of car components in CAD software, reducing validation time per vehicle from 18 to 15 hours, benefiting over 1500 virtual builds, annually▪ Collaborated with business unit leaders to devise a custom work allocation tool, boosting operational efficiency by enabling comprehensive analysis of performance metrics for 800 employees across 12 teams. Earned the 'Work of Wonder' award for this innovative solution amidst complex resource constraints

▪ Employed data analysis and trend identification techniques to pinpoint and resolve critical quality issues on the factory assembly line, yielding a 20% reduction in supplier defects and enhancing throughput efficiency▪ Awarded the 'Individual Excellence' award among 50 graduate engineer trainees for effective root cause analysis and resolution of supplier quality issues during the launch of Chevrolet Beat