⮕ As a Product Manager at Vydia, a gamma. company, I lead strategic initiatives to empower music businesses by building cutting-edge scalable audio technology. Vydia is an all-in-one platform experience, including global distribution + monetization (digital, physical, merch), publishing administration, sync licensing, rights management, royalties, data analytics, data engineering & infrastructure, and more to come.⮕ Previously, I held software development roles such as Data/ML Engineer, Audio Lead on applied machine learning teams. I both worked professionally and conducted independent research on a variety of generative AI applications (music, sound effects, environmental sound, text-to-speech voice-over synthesis), in addition to more traditional machine learning applications such as representation learning and auto-tagging. As a machine learning & music informatics researcher, I published my machine/deep learning audio research in multiple mediums. As primary author, my research "Representation Learning for the Automatic Indexing of Sound Effects Libraries", was accepted for publication at the prestigious 23rd International Society for Music Information Retrieval conference hosted in Bengaluru, India (ISMIR, https://bit.ly/3CyB1wf). The paper details rigorous multi-task learning experiments in contrastive/triplet metric learning to maximize embedding vector distance. At WellSaid Labs, I co-authored research publications and blog posts with my work on deep learning audio feature controllability and speech enhancement (clarity, acoustics, noise reduction). This flagship text-to-speech model learns a separate mapping network that maps from contextual annotations (cues) to a latent space 𝒲 that controls the generator.⮕ I hold a Master of Science from Georgia Tech where for 2.5 years, I intensively studied in the Computer Science, Electrical & Computer Engineering, and Music Technology departments, to conduct digital signal processing & machine/deep learning research for audio applications in Dr. Alexander Lerch's Music Informatics Lab. I hold a Bachelor of Music from the renowned Berklee College of Music where I developed an eye for the music business and an ear for music creation and sound design. To supplement my formal academic education and professional experience, I also have certifications inclusive of Product Costing (Stanford), Foundations of Databases & SQL Programming (University of Washington), IBM Data Engineering, and a variety of YouTube Rights Management courses (Asset Monetization, Content Ownership, Rights Management).