In this workgroup we will investigate the computational capabilities of DYNAP-SE heterogeneous neurons for compressing time series data. Our focus is on exploring how these neurons can efficiently compress both periodic and aperiodic signals using few spikes per neuron, enabling low-latency pattern detection. We will optimize the DYNAP-SE neuromorphic chip with gradient-free optimization methods to use analog circuit variability for signal compression applications.