Doctoral Thesis Oral Defense - Nicole Feng
May 4, 2026 9:00AM—11:00AM
Location:
4405
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Gates and Hillman Centers
Speaker:
NICOLE FENG,
Ph.D. Candidate, Computer Science Department, Carnegie Mellon University
https://nzfeng.github.io/
In this talk, I'll discuss algorithms for generalized inside/outside and signed distance computation. By "generalized", I mean that these algorithms make geometric inferences from imperfect data comprising incomplete, inaccurate, or ambiguous observations or representations of shapes. In other words, these algorithms generalize from imperfect data and implicitly approximate the true underlying curve or surface. A theme is that generalization can often be achieved by processing globally-defined functions encoding the geometry of interest, rather than the original, defective curve or surface. For both inside/outside and signed distance computation we can unlock further control over geometry and topology by processing higher-order derivatives of these functions. Another theme is that inside/outside and signed distance computation are closely related problems; towards this end, I'll provide a formalization of their relationship that justifies the design of our algorithms.
Thesis Committee:
Keenan Crane (Chair)
Nancy Pollard
Ioannis Gkioulekas
Chris Wojtan (Institute of Science and Technology Austria)
Contact
Matt Stewart