SuraMed (AI Radiology)
SuraMed is an AI radiology company built for the Arab world, focused on developing advanced clinical imaging tools tailored to hospitals, clinics, and radiology centres across …
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1 min read
Professional Summary
Mohammed Khalilia (محمد عبد الستار قاسم) is a researcher, computer scientist, and data scientist with a PhD in Computer Science from the University of Missouri. Following his doctorate, he joined Georgia Tech’s Computational Science and Engineering school and Emory University as a Postdoctoral Fellow, where his research spanned predictive modeling, relational cluster analysis, and health and nursing informatics.
He then spent nearly five years at Amazon, working across Amazon Web Services (AWS) and Amazon Studios in natural language processing (NLP), speech synthesis, and computer vision. In 2018, he was part of the team that launched Comprehend Medical, Amazon’s NLP service for clinical and biomedical text. At Qualtrics, he developed the company’s first fine-tuned large language model, trained synthetic sampling model, and worked on conversational machine learning, and active learning.
He is also an adjunct professor at Birzeit University, where he teaches NLP courses for doctoral students.
Education
PhD Computer Science
2007-01-01
2014-05-15
University of Missouri-Columbia • USA
BS Computer Science
2001-08-31
2006-12-31
University of Missouri-Columbia • USA
Interests
Machine learning
Natural Language Processing
Biomedical/health informatics
Predictive modeling
Large Language Models
Featured Projects
Synthetic Panels
Recruiting the right participants for a study can be difficult. You may not get the exact demographics you need, and the shorter the deadline, the less sure you can be that …
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1 min read
Data Anonymization using NER
Customers own their data, and while a data use agreement permits the use of anonymized data, raw data cannot be used for model training. The anonymization tools are rule-based, …
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1 min read
Insight Explorer
Insights Explorer is an AI-powered text analytics tool that uses your open-ended feedback to identify top themes, create headlines, and generate helpful summaries. This feature can …
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1 min read
Wojood - Arabic NER
Wojood consists of about 550K tokens (MSA and dialect) that are manually annotated with 21 entity types (e.g., person, organization, location, event, date, etc). It covers multiple …
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1 min read
Comprehend Medical
Amazon Comprehend Medical is a HIPAA-eligible natural language processing (NLP) service that uses machine learning that has been pre-trained to understand and extract health data …
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1 min read
Featured Publications
Multi-Channel Volume Level Equalization Based on User Preferences
Systems, devices, and methods are provided for multi-stem volume equalization, wherein the volume levels of each stem may be adjusted non-uniformly. Audio may be diarized into a …
mohammed-khalilia
Service architecture for entity and relationship detection in unstructured text
Techniques for entity and relationship detect from unstructured text as a service are described. A service may receive a request to identify entities within a provided unstructured …
thiruvarul-selvan-senthivel
Facial Feature Location-based Audio Frame Replacement
Played audio frames included in first audio content may be received over one or more networks. The first audio content may further include a replaced audio frame. The first audio …
mohammed-khalilia
Video Frame Replacement Based on Auxiliary Data
The popularity of videoconferencing has increased rap idly in recent years. Video conferencing tools may allow multiple people at multiple different locations to interact by …
gregory-johnson
Wojood: Nested Arabic Named Entity Corpus and Recognition using BERT
This paper presents Wojood, a corpus for Arabic nested Named Entity Recognition (NER). Nested entities occur when one entity mention is embedded inside another entity mention. …
mustafa-jarrar
Joint Entity Extraction and Assertion Detection for Clinical Text
Negative medical findings are prevalent in clinical reports, yet discriminating them from positive findings remains a challenging task for in-formation extraction. Most of the …
parminder-bhatia
Recent Publications
(2025).
$Wojood^{Relations}$: Arabic Relation Extraction Corpus and Modeling.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.
(2025).
Active Learning for Multidialectal Arabic POS Tagging.
Findings of the Association for Computational Linguistics: EMNLP 2025.
(2025).
WojoodOntology: Ontology-Driven LLM Prompting for Unified Information Extraction Tasks.
Proceedings of The Third Arabic Natural Language Processing Conference.
(2025).
Konooz: Multi-domain Multi-dialect Corpus for Named Entity Recognition.
Findings of the Association for Computational Linguistics: ACL 2025.
(2024).
ArabicNLU 2024: The First Arabic Natural Language Understanding Shared Task.
Proceedings of the Second Arabic Natural Language Processing Conference.