Innovative technology is increasingly used in autism research. Such applications include active and passive monitoring combined with machine learning to facilitate screening, novel treatment approaches, and expanded outcome assessments. Technological approaches offer quantitative, objective assessments that can be acquired remotely in natural settings. Moreover, because they do not rely solely on expert clinical ratings, they are scalable and permit acquisition of large data sets to produce automated classification algorithms. This panel will describe several contemporary methods and applications of technology in autism research. The first presentation discusses how computer vision analysis can be used to quantify early autism symptoms, discover novel biomarkers, and monitor behavior over time. The next presentation describes research extending the use of computer vision analysis to studies of social interaction and coordination. The subsequent presentation focuses on automated detection and characterization of stereotypical motor movements and their relationship to physiological arousal. The final presentation provides an overview of a multimodal system, which includes both active and passive digital monitoring, for outcome assessment in clinical trials. The discussant will focus on the future challenges and potential impact of technology on autism research, and its application to novel treatment approaches, including the use of robots.