  The directionality information of incoming neutrinos is essential to
atmospheric neutrino oscillation analysis since it is directly related to the
oscillation baseline length. Large homogeneous liquid scintillator detectors,
while offering excellent energy resolution, are traditionally very limited in
their capabilities of measuring event directionality. In this paper, we present
a novel directionality reconstruction method for atmospheric neutrino events in
large homogeneous liquid scintillator detectors based on waveform analysis and
machine learning techniques. We demonstrate for the first time that such
detectors can achieve good direction resolution and potentially play an
important role in future atmospheric neutrino oscillation measurements.
