I recently completed my MS in Electrical and Computer Engineering at Northeastern, specializing in Machine Learning. My journey has taken me through 2.5 years of research at the Traverso Lab at MIT and Harvard Medical School, where I focused on integrating multimodal biosignal trajectories for advancing personalized medicine through continual learning. My exploration extended to hardware acceleration techniques and innovative preprocessing methods in biological systems, emphasizing the revision of continual learning principles to address inefficiencies in existing approaches.Currently seeking entry-level machine learning roles in the San Francisco Bay Area, I am passionate about leveraging multimodal data to uncover interdisciplinary solutions. I thrive on challenging the status quo and reevaluating our assumptions, steadfast in my belief that interdisciplinary research is key to unlocking novel insights and advancements.Let's connect to discuss how we can drive progress together by rethinking and integrating diverse perspectives in machine learning!