Jackson Liscombe
About Jackson Liscombe
Jackson Liscombe is a Senior Scientist with a PhD in Computer Science, recognized for his contributions to research on multimodal dialog-based speech and facial biomarkers, including work on speech biomarkers for ALS.
Work at Modality.AI
As a Senior Scientist at Modality.AI, Jackson Liscombe focuses on advancing research in speech and multimodal dialogue systems. His work involves developing technologies that enhance communication through the integration of speech and facial biomarkers. This research contributes to the understanding of how these modalities can be utilized in various health assessments.
Education and Expertise
Jackson Liscombe holds a PhD in Computer Science, which provides a strong foundation for his research in speech technology and biomarker analysis. His academic background equips him with the skills necessary to explore complex problems in the field of spoken dialogue systems and health-related speech analysis.
Background
Jackson Liscombe has a diverse research background that includes significant contributions to the study of speech biomarkers in various medical conditions. He has been involved in projects related to ALS and Parkinson's Disease, focusing on how speech patterns can serve as indicators for these conditions. His work also includes research on multimodal dialog systems.
Achievements
Jackson Liscombe has presented his research at notable conferences, including the International Workshop on Spoken Dialogue Systems Technology and the American Speech-Language-Hearing Association (ASHA) Convention. He received the ASHA Meritorious Poster award for his research on Lyme Disease. Additionally, he has co-authored papers addressing ALS and schizophrenia, contributing to the academic discourse in these areas.
Research Contributions
Jackson Liscombe has contributed to the development of a telehealth platform aimed at assessing Parkinson's Disease. His research on speech biomarkers for ALS highlights the potential of using speech analysis as a diagnostic tool. He has also explored the implications of multimodal dialog systems in enhancing communication for individuals with speech-related challenges.