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Current Positions

• Associate Professor at UTHealth (University of Texas Health Science Center at Houston)

• Member at Tibyan Organization for Artificial Intelligence

• Visiting Professor at University of Tripoli

My past employers include Addis Ababa University, OHSU, Trapit, Mayo Clinic, Starkey Laboratories, Honeywell Research, and Medtronic. For more details (and up-to-date info), check out my LinkedIn profile.

Objectives

I'm trying to empower people to improve society through the wise use of digital data. That means I want to develop a whole ecosystem for data science: business, education, and research. Right now, the thrust is in Libya, where despite an ongoing instability there is an educated and energetic middle-class population, alongside a dearth of businesses in advanced information technologies.

Research Interests

There are some foundational interests that guide the research directions I take on:

• Computational semantics. I am interested in distributional/geometric models of semantics and in ontological semantics. Each type of representation may provide complementary benefits in NLP applications. I am also interested in compositionality and similarity in these semantic frameworks.

• Lesser-resourced languages. During my time in Ethiopia (2017-2018), I began to work on deep learning NLP for Semitic languages. This interest and collaborative work has continued, and will likely expand over time, especially since I live somewhere where the majority language is not English.

• Clinical information extraction/retrieval. Much of the important information in electronic medical records (EMR) is in free-text clinical notes rather than form fields. With clinical NLP, this information may be accessed and used to improve patient care. I am also interested in implementing the systems that make this information available to clinicians and researchers, hence my interest in information retrieval.

I secured and led an NLM-funded R01 (at OHSU) focused on information retrieval. I also had an NIAID-funded R21 (with Mayo Clinic) on aggregating patient information over time.

Teaching

I offer some introductory material on Natural Language Processing through Libya AI's Facebook Page and YouTube Channel.

In Winter Term 2016, I taught CS 562/662 Natural Language Processing at OHSU. I wrote a blog post about my experiences, advocating for a new teaching framework called techied.

In Spring 2018, I taught ITSC-5C22 Social Network Analysis at Addis Ababa University, and wrote another blog post about this very cross-cultural teaching experience.

I have also taught CS 555/655 Analyzing Sequences at OHSU.

Feel free to clone/use/fork my techied repository and build off of it!

Resources

• cTAKES: Apache Clinical Text Analysis and Knowledge Extraction System. Originally developed at Mayo Clinic, this is a customizable UIMA-based pipeline that takes clinical text as input and gives lots of different clinical IE/NLP output.

• NLTK: Natural Language Toolkit. Easy-to-use toolbox for natural language processing, written in Python. Includes great introductory material for those new to NLP. Good stuff, but I am not a developer.

• keras: The deep learning toolkit that I typically use, now incorporated into TensorFlow.

Other links

• Computational Semantics in Clinical Text (CSCT), a workshop that I organized.

• Some important wisdom.

• A secondary passion.