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Machine Learning Engineer
I'm a machine learning engineer building efficient on-device models for EMG, handwriting, and conversational AI.
United StatesMachine Learning Engineer at Meta
Led the end-to-end ML lifecycle from EMG research to production model inference, culminating in the launch of the MetaNeuralBand device. Spearheaded research and production of on-device quantization, sparsity, compression, and power optimization for EMG and handwriting models.
Machine LearningQuantizationPyTorchExecuTorchArmInference Optimization
Led the development of a proactive, ML-driven latent goal-solving service scaling to 200+ TPS, doubling system throughput through lazy caching and rule engine optimizations. Launched an industry-first contextual understanding solution under Alexa's NLU service for multi-turn interactions.
Machine LearningNLUCachingOptimization
Pursuing a Master of Science in Computer Science with a focus on Machine Learning, NLP, and Optimization theory.
Graduated with a Bachelor of Science in Computer Engineering, achieving a cumulative GPA of 3.74.
Earned a Bachelor of Engineering in Computer Engineering with a concentration in Computer Engineering and a minor in Electrical Engineering, achieving a cumulative GPA of 9.15/10.
Researched kernel learning algorithms over convex spaces and designed memory-efficient structures to extract a 150GB DNS census bipartite graph.
Convex
Developed a hierarchical model to extract sports events and tag entities from Twitter's streaming API, curating a dataset of 1,000+ classified tweets.
NLPHierarchical ModelingData Curation
Created a patentable Face detection based Auto-Focus algorithm with Non-linear regression Bayesian.
Autofocus
Researched fast numerical methods to compute the n root of a number.
Numerical MethodsRoot Finding
Profile sourced from Himalayas.