Machine Learning

Developed time series forecasting models on NHITS and TFT architectures, improved accuracy by 30% Finetuned TimeGPT and Chronos LLMs for feature reduction, decreasing computation time by 40%

Designed a robust CV extraction pipeline with Reducto, reducing customer intake time by 60% Constructed an end-to-end automated report generation tool for pharmaceutical ingredient analysis

Extended recurrent convolutional neural networks (RCNN) for surface code quantum error correction Tuned RCNN model to achieve equivalent performance with less than 25% of original parameter count Quantized TensorFlow dense models with hls4ml for use in dedicated FPGAs, reducing load by 50%