PhD Thesis Proposal
Calendar of Events
S Sun
M Mon
T Tue
W Wed
T Thu
F Fri
S Sat
0 events,
0 events,
0 events,
1 event,
PhD Thesis Proposal
Towards Pragmatic Time Series Intelligence
Abstract: The widespread adoption of time series machine learning (ML) models faces multiple challenges involving data, modeling and evaluation. Data. Modern ML models depend on copious amounts of cohesive and reliably annotated data for training and evaluation. However, labeled data is not always available and reliable, and can also be dispersed across different locations. We [...]
1 event,
PhD Thesis Proposal
Improved Surface Estimation for use in Virtual Fixtures during Retinal Surgery
Abstract: Retinal surgery procedures require surgeons to manipulate very delicate tissues with little room for error. During epiretinal membrane surgery, to reduce chances of recurrence, surgeons may have to remove the 10 µm thick internal limiting membrane from the retinal surface. An experimental procedure to treat retinal vein occlusion is retinal vein cannulation. During this [...]
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
0 events,
1 event,
PhD Thesis Proposal
3D Perception In-The-Wild
Abstract: State estimation is a fundamental component of embodied perception. Contemporary autonomous vehicle (AV) benchmarks have advanced techniques for training 3D detectors, particularly on large-scale data. Notably, although prior work has nearly solved 3D object detection for a few common classes (e.g., pedestrian and car), detecting many rare classes in-the-tail (e.g., debris and stroller) remains [...]
0 events,
0 events,
0 events,
0 events,
0 events,
1 event,
PhD Thesis Proposal
Differentiable Convex Modeling for Robotic Planning and Control
Abstract: Robotic simulation, planning, estimation, and control, have all been built on top of numerical optimization. In this same time, modern convex optimization has matured into a robust technology delivering globally optimal solutions in polynomial time. With advances in differentiable optimization and custom solvers capable of producing smooth derivatives, convex modeling has become fast, reliable, [...]