This paper presents the JU-USAAR English-German domain adaptive machine translation (MT) system submitted to the IT domain translation task organized in WMT-2016. Our system brings improvements over the in-domain baseline system by incorporating out-domain knowledge. We applied two methodologies to accelerate the performance of our in-domain MT system: (i) additional training material extraction from out-domain data using data selection method, and (ii) language model and translation model adaptation through interpolation. Our primary submission obtained a BLEU score of 34.5 (14.5 absolute and 72.5% relative improvements over baseline) and a TER score of 54.0 (14.7 absolute and 21.4% relative improvements over baseline).