Halil Kilicoglu, Ph.D. (he/him) is a professor in the School of Information Sciences (iSchool). He specializes in natural language processing (NLP), artificial intelligence/machine learning (AI/ML), and knowledge representation with biomedical applications.
Prof. Kilicoglu uses data-driven analytical techniques and knowledge-based semantic approaches to extract and organize knowledge buried in textual artifacts to accelerate biomedical discovery and innovative clinical applications. His latest work includes the development of automated methods to assess research rigor, transparency, and integrity of biomedical publications.
In addition to affiliations with National Center for Supercomputing Applications, Carl R. Woese Institute for Genomic Biology, Beckman Institute for Advanced Science and Technology, and the Personalized Nutrition Initiative, Professor Kilicoglu recently joined the Interdisciplinary Health Sciences Institute (IHSI) affiliate program.
Prof. Kilicoglu has been involved with IHSI for the last several years. He has participated in the National Institutes of Health (NIH) Grant Writing Series and connected with IHSI’s Biostatistics, Epidemiology, and Research Design (BERD) team for a grant proposal.
More recently, Prof. Kilicoglu deepened his connection with IHSI as a member of the inaugural cohort of the Emerging Research Leaders Academy (ERLA). Along with other mid-career faculty and researchers, Prof. Kilicoglu participated in this program to further develop his leadership and team science skills to pursue major grants, lead campuswide initiatives, and strengthen Illinois’ research impact.
Prior to joining the iSchool faculty in 2019, Prof. Kilicoglu was a research scientist at the National Library of Medicine, National Institutes of Health (NLM/NIH), where he led the Semantic Knowledge Representation project. His research has been funded by the NIH, the Agency for Healthcare Research and Quality (AHRQ), and The U.S. Department of Health and Human Services Office of Research Integrity.
Can you describe a goal you are currently pursuing?
In one of my projects, we are currently developing AI-based models and tools to assist medical journals and reviewers in checking the transparency and rigor of randomized controlled trial (RCT) publications. While RCTs are considered the best kind of evidence for determining the efficacy and safety of clinical interventions (drugs, devices, etc.), their reporting is found to be suboptimal, leading to concerns about the reliability of the evidence they present. By providing AI-based tools to check submitted manuscripts quickly and at scale, we are hoping to contribute to improved quality and reliability of published RCTs.
How has the focus of your research changed or evolved since you first started in the field?
I was trained as a computational linguist. Initially, my research focused more on basic research on linguistically-based approaches to natural language semantics. While this interest continues to some extent, most of my ongoing projects these days focus on development and application of AI and machine learning-based methodologies to real-world problems in health and medicine.
How is most of your research funded? Do you have any advice for working with these sponsors?
My current research funding is from NIH and AHRQ. These agencies prioritize projects with clear potential to improve healthcare, so it is essential to clearly outline how the research (basic or applied) will contribute to that goal.
What is something you want your colleagues to know about you or your research?
My work is multidisciplinary and I bring my computational expertise to collaborations with domain experts across fields. I am broadly interested in developing automated methods to enhance research planning, execution, and reporting, with the goal of making science more innovative and trustworthy.
What would you like to know about other researchers?
I am always eager to learn about what other researchers are working on and explore whether/how technological innovations might help address some of their challenges and bottlenecks.
IHSI affiliates demonstrate leadership and commitment to improving human health. The IHSI affiliate program is designed for those who wish to deepen their relationship with IHSI and contribute to its mission of catalyzing interdisciplinary health research that addresses personal, public, and planetary health challenges. Affiliates enjoy increased visibility and opportunities to engage with and benefit from IHSI staff, other affiliates, and networks, both across campus and with external partners, and to help shape health research, innovation, and translation.
The IHSI Affiliate Program is currently open by invitation only. To become an IHSI affiliate, please contact your collaborators at IHSI, or request an invitation by emailing healthinstitute@illinois.edu. Please visit the IHSI Affiliate page for more information.