Hi! My name is Tomo. I'm 19 years old and grew up in the greater boston area. I am a current second year at Northeastern University, and I'm a passionate Data Science student at Northeastern University, driven by a deep interest in machine learning, knowledge assembly, and data engineering. I am an ML/AI Research Assistant at the Gyori Lab for Computational Biomedicine, where I get to apply my interests and knowledge of artificial intelligence to real-life biomedical applications.
For Gyori Lab, currently I am trying to find methods to extract genetic mutations from clinical trial inclusion/exclusion criteria. In this way, we could theoretically create BioEntities that reflect these genetic mutations, and provide better oncogenetic precision medicine to patients with cancer. Outside of the lab, I had finished a project on providing an implementation on a ConvLSTM layer for Apple's array framework library known as MLX. I am in the process of writing documentation, and cleaning up my code in order to publish it as a real library.
Contributed to the TrialSynth project by integrating clinical trial data across multiple registries into a computable knowledge graph, by standardizing biomedical entities into unique concept identifiers.
Taught groups of around 20 students, ages 11-14, how to code in Python, Java, and Scratch through an interactive environment.
Recreated Suzuki et. al's work on "Residual Learning of Video Frame Interpolation Using ConvLSTM." Leveraged PyTorch's nn.Module library to build a model from scratch, and created a custom DataLoader for training.
Developed the Convolutional LSTM structure as dicussed in Shi et al.'s work of "Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting." for Apple's array framework library MLX, which utilizes the shared memory pool for Apple Sillicon CPU's and GPU's for efficient training.