Trained at the University of Michigan, Danny is an experienced data scientist and machine learning (ML) engineer with a specialization in time-series analyses, signal processing, and computer vision. More often than not, he has had to lead projects where their full potential of their data had been underutilized. Due to this, he excels in identifying data and modeling needs, and then developing solutions for teams without existing frameworks. His passion for software engineering allows him to deliver mature, reliable, and maintainable solutions. As an example at the University of Michigan, he designed and implemented custom infrastructure capable of processing more than 1TB a day of data. He currently works for a leading FinTech company in Tokyo, enhancing their product offerings with in-house document Al models.
Education
Danny received his PhD in Behavioral and Computational Neuroscience from the University of Michigan, Ann Arbor, where his research focused on how electrical brain activity relates to behavior and diseases. These topics spanned from addiction, spatial navigation, and epilepsy. He also graduated from the University of California, Irvine with a B.S. in Biological Sciences and Computer Science.
