With recent advancements in the field of additive manufacturing, the design domain for development of complicated cooling configurations has significantly expanded. The motivation of the present study is to develop high performance impingement cooling designs catered towards applications requiring high rates of heat removal, e.g. gas turbine blade leading edge and double-wall cooling, air-cooled electronic devices, etc. In the present study, jet impingement is combined with strategic roughening of the target surface, to achieve high heat removal rates. Steady state experiments have been carried out to calculate the heat transfer coefficient for jet impingement onto different target surface configurations. The jet-to-jet spacing (x/d = y/d) was varied from 2 to 5, and jet-to-target distance (z/d) was varied from 1 to 5. The target surface configurations featured cylindrical, cubic and concentric shaped roughness elements, fabricated through binder jetting process. The baseline case for the roughened target surface was a smooth target. Heat transfer and pressure drop experiments were carried out at Reynolds numbers ranging from 2500 to 10,000. Further, numerical simulations were carried out to model flow and heat transfer for all configurations at a representative Reynolds number. Through our experiments and numerical results, we have demonstrated that the novel "concentric" roughness shape was the best in terms of fin effectiveness and Nusselt numbers levels, amongst the investigated shapes. The concentric-shape roughened target resulted in fin effectiveness up to 1.6, whereas the cubic- and cylindrical-shape roughened targets yielded in fin effectiveness up to 1.4 and 1.3, respectively. Further, it was experimentally found that the addition of micro-roughness elements does not result in a discernable increment in pressure losses, compared to the impingement on the smooth target surface. Hence, the demonstrated configuration with the highest heat transfer coefficient also resulted in highest thermal hydraulic performance. (C) 2018 Elsevier Ltd. All rights reserved.