Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in2 using sophisticated 2-D signal-processing algorithms. TDMR achieves high areal densities by reducing the size of a bit to the order of the size of a magnetic, resulting in 2-D inter-symbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Further, a variations in servo motor speed and mechanical jitter in read-write head results in timing errors both in cross-track and down-track directions. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D timing errors, 2-D ISI and combat noise comprising jitter and electronic components. In this poster, we present following contributions of our work so far towards TDMR read channel architecture 1) We proposed a 2-D Soft-output Viterbi algorithm (SOVA) as an extension to the well known 1D SOVA; 2) We empirically characterized the jitter noise using a Voronoi-based granular media model; 3) We developed a data-dependent noise-prediction (DDNP) algorithm to handle the media noise seem in TDMR;  4) we also developed techniques to design 2-D separable and non-separable targets for generalized partial response equalization for TDMR that can be used along with a 2-D signal detection algorithm; 5) we proposed a joint 2-D timing recovery and signal detection scheme using 2-D SOVA to handle the 2-D timing errors.