(Fall 2022) Project Lead - GeoKnowr

• Leading a deep learning project of a team of 6 to develop a end-to-end GeoGuessr location prediction interface using both classification and regression

• Building new models using few-shot representation learning and Meta-RL, and improving existing models performances such as Google PlaNet CNNs

(Fall 2021) Machine Learning Engineer - Inflection

• Worked with Launchpad internal team on Alexa voice conversion (VC) model that takes in any sample voice and converts voice assistance to the speaker’s voice

• Feature engineered vector representations of model inputs with low-level Python libraries such as Pyworld, Pysptk, and speech synthesis libraries like nnmnkwii

• Trained CNN models on audio files converted as MFCCs with filterbanks, Reduced training time with time-warped parallel data and Mel Cepstrum predictors

• Automated generation of summary reports from iShares time series data, deployed into production within a month and achieve high evaluation metrics

• Implemented few-shot ML models for natural language generation using dual weights LSTM, Hidden Markov Models, and PLM

• Improved model scalability with customized GPT, eicient data generation, and Tableau API integration for augmented analysis and data insight derivations

• Delivered a customizable NLG model which removed the need for a third party solution costing over $300k