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Daniel Zeiberg is a PhD student at Northeastern University’s College of Computer and Information Science, advised by Rose Yu. He received his BSE in Computer Science from the University of Michigan, where he did undergraduate research developing methods to predict the onset of Acute Respiratory Distress Syndrome with Jenna Wiens. His main area of research is Machine Learning, and he is interested in researching methods that can process irregularly sampled time series.


  • BSE in Computer Science, University of Michigan

About Me

  • Hometown: Mount Laurel, NJ
  • Field of Study: Machine Learning
  • PhD Advisors: Rose Yu

What are the specifics of your graduate education (thus far)?

I will be starting my PhD this fall, being advised by Rose Yu. I previously did undergraduate research at the University of Michigan with Jenna Wiens, developing methods to predict the onset of Acute Respiratory Distress Syndrome (ARDS) in hospital patients.

What are your research interests?

I am interested in developing time series methods and researching applications of novel methods.

What’s one problem you’d like to solve with your research/work?

I would like to research methods that can handle irregularly sampled time series.

What aspect of what you do is most interesting?

What I, and I think others should, find most interesting about my research is that I develop applications that have a positive impact on people.

What are your research or career goals, going forward?

I am a bit unclear on what I want to do, but I currently want to eventually do industry research and product development.

Where did you grow up or spend your most defining years?

South Jersey

Where did you study for your undergraduate degree?

Did my undergrad at University of Michigan. I liked Michigan’s school spirit, as I came from a small high school.