Hussein S. Al-Olimat, PhD

Hussein S. Al-Olimat is an NLP Scientist with more than 3 years of experience in building industry-level NLP solutions at Healthcare and Knowledge Graph companies. He obtained his PhD. in Computer Science from Wright State University in 2019 and was part of the Kno.e.sis research center working on multi-disciplinary projects in the areas of healthcare and decision support. In his dissertation titled Knowledge-enabled Information Extraction, he pursued multifaceted syntactic, semantic, and pragmatic information extraction techniques. His research has resulted in publications in top venues (such as COLING, SIGSPATIAL, SIGIR, and ASONAM), was recognized by the Computing Community Consortium (CCC) as a Blue Sky vision idea, and was patented in the USA.

Updates

• Our work was featurized by The Computing Community Consortium - CCC as an innovative idea– link
• I successfully defended my Ph.D. dissertation on Nov 2019.
• Our paper “Towards Geocoding Spatial Expressions” won a Blue Sky Idea prize by the The Computing Community Consortium - CCC.
• Our vision paper “Towards Geocoding Spatial Expressions” was accepted for publication in SIGSPATIAL 2019.
• In May 2019, I got the “Outstanding Student Award” from the CES Department at Wright State University.
• In April 2019, our demo paper was accepted at SIGIR 2019. To appear.
• In March 2019, our US. patent titled “Machine Assisted Learning of Entities” was granted.
• Our DisasterRecord paper was accepted at ARIC workshop at SIGSPATIAL 2018.
• I presented our two papers LNEx and SpExtor at COLING 2018 in Santa Fe, NM.
• I will be presenting with Amir Yazdavar our tutorial on Location Extraction @ ISCRAM - 2018 in May 2018 in Rochester, NY. Tutorial Website
• I presented our depression detection paper in ASONAM 2017 in Sydney, Australia on August 2017. Slides
• Our paper titled “Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media” was accepted in ASONAM 2017.
• In June 2016, our poster titled “Analyzing Depressive Symptoms in Twitter” was accepted and will be presented in the 23rd NIMH Conference on Mental Health Services Research, MHSR 2016: Harnessing Science to Strengthen the Public Health Impact.