  Understanding the inner working of the quark-gluon plasma requires complete
and precise jet substructure studies in heavy ion collisions. In this
proceeding we discuss the use of quark and gluon jets as independent probes,
and how their classification allows us to uncover regions of QCD phase space
sensitive to medium dynamics. We introduce the telescoping deconstruction (TD)
framework to capture complete jet information and show that TD observables
reveal fundamental properties of quark and gluon jets and their modifications
in the medium. We draw connections to soft-drop subjet distributions and
illuminate medium-induced jet modifications using Lund diagrams. The
classification is also studied using a physics-motivated, multivariate analysis
of jet substructure observables. Moreover, we apply image-recognition
techniques by training a deep convolutional neural network on jet images to
benchmark classification performances. We find that the quark gluon
discrimination performance worsens in \textsc{Jewel}-simulated heavy ion
collisions due to significant soft radiation affecting soft jet substructures.
This work suggests a systematic framework for jet studies and facilitates
direct comparisons between theoretical calculations and measurements in heavy
ion collisions.
