Hussein S. Al-Olimat, PhD
Dr. Hussein S. Al-Olimat is a experienced NLP Scientist with a strong track record of building industry-level NLP solutions for healthcare and knowledge graph companies. He obtained his PhD in Computer Science from Wright State University in 2019, where he was a member of the Kno.e.sis research center and conducted multi-disciplinary research in the areas of healthcare and decision support. His dissertation, titled “Knowledge-enabled Information Extraction,” focused on advanced syntactic, semantic, and pragmatic information extraction techniques. Dr. Al-Olimat’s work has been published in top venues such as COLING, SIGSPATIAL, SIGIR, and ASONAM, and has been recognized by the Computing Community Consortium (CCC) as a Blue Sky vision idea. Additionally, his work has been patented in the United States.
Updates
- Our work for cohort creation to study cancer patients in collaboration with CancerLink and AstraZeneca teams is out Natural language processing-optimized case selection for real-world evidence studies
- 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.