The next generation water-Cherenkov detector Hyper-Kamiokande (Hyper-K), is currently under
construction in Japan and it is expected to be ready for data taking in 2027. Thanks to its
huge fiducial volume and high statistics, Hyper-K will contribute to many investigations such as
CP-violation, determination of neutrino mass ordering and potential observations of neutrinos
from astrophysical sources. To increase the sensitivity of the detector, Hyper-K will have a
hybrid configuration of photo-detectors: thousands of 20-inch photo-multipliers tubes (PMTs)
will be combined with modules containing 3-inches PMTs arranged inside a pressure-resistant
vessel, called multi-PMT modules. Many efforts are on-going to reduce the expected dark counts
for a detector geometry which includes both photo-detector modules. Machine learning-based
techniques are being developed to reduce the detector’s overall dark rates, which could have a
significant impact on Hyper-K’s sensitivity to low-energy neutrinos.