Applied Data Scientist & Trustworthy AI Researcher

Advancing trustworthy AI through interdisciplinary research, mentoring the next generation of innovators, and developing intelligent technologies that improve education, healthcare, and society.

Learn More Get In Touch

Scientist

Educator

Researcher

Hi, I'm Dr. Jamell Dacon

Applied Data Scientist & Trustworthy AI Researcher

Morgan State University

I am a (Tenure-Track) Assistant Professor in the Department of Computer Science at Morgan State University, where I serve as the Director & Lead Principal Investigator of the Machine Intelligence and Data Science (MINDS) Lab, and a faculty at the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS).

I am a computer scientist focused on trustworthy AI for education, health, and language justice. My research develops robust, interpretable, and equitable AI systems for high-stakes human domains, with work spanning NLP, learning analytics, clinical decision support, and computational social science. My work is driven by a commitment to advancing equitable AI research that addresses real-world challenges and promotes social good.

News & Updates

I am always interested in collaborating on interdisciplinary research, innovative AI initiatives, educational programs, and projects that drive meaningful scientific and societal impact.

Curriculum Vitae

06, 2026 - Honored to be invited to serve as a Keynote Speaker and Session Chair of the EDM #7: Tutoring & Personalization at the International Conference of Educational Data Mining (EDM), in Seoul, South Korea.
06, 2026 - Honored to be invited as both a panelist and a keynote speaker at the June Workshop #1 on Writing Proposals Leveraging AWS Technologies hosted by the Howard AI Network Powered by AWS.
05, 2026 - Honored to be selected as the first recipient from Morgan State University in the inaugural CRA x Microsoft Trustworthy AI Fellowship 2026-2027 cohort.
04, 2026 - Honored to be selected by Morgan State University for the Google Career Launchpad Faculty Cohort to earn a Generative AI Leader Certification and lead student-facing AI curriculum.
04, 2026 - Honored to be selected to participate in the 2026 Faculty Development Summer Institute (FDSI), hosted by the Atlanta University Center (AUC) Data Science Initiative in Atlanta, Georgia.
04, 2026 - Excited to share that our paper, “Prescriptive Persistence: Quantifying the Breakdown in Human-AI Pedagogical Co-Regulation in ELL Writing Feedback” has been accepted to the 13th 2026 ACM Learning @ Scale Conference, in Seoul, South Korea [PDF].
03, 2026 - Excited to share that our paper, “The Semantic Gap in Behavioral Embeddings: Why Linear Methods Fail for Educational RAG in Mathematics” has been accepted to the International Conference of Educational Data Mining (EDM), in Seoul, South Korea [PDF].
01, 2026 - Excited to share that our paper, “Optimizing Insulin Dosing for Type 1 Diabetes with Thyroid Dysfunction Using Q-Learning: A Personalized Approach to Chronic Disease Management” has won the Best Paper Runner Up Award at the Bridge Program - AI for Medicine and Healthcare at The 40th Annual AAAI Conference on Artificial Intelligence in Singapore.

11, 2025 Excited to share that two of our papers have been accepted to the AI for Medicine and Healthcare AAAI Bridge Program at The 40th Annual AAAI Conference on Artificial Intelligence in Singapore.
- “Optimizing Insulin Dosing for Type 1 Diabetes with Thyroid Dysfunction Using Q-Learning: A Personalized Approach to Chronic Disease Management” [PDF].
- “Manifold-Informed Cohort Discovery (MICD): A Framework for Uncovering Latent Risk Signals in Imbalanced Healthcare Data” [PDF].
10, 2025 - Excited to share that our paper, “BIO-DQNA: Meta-Learning and Contrastive Reinforcement Learning for Personalized Comorbidity Management in Type 1 Diabetes and Hypertension” has been accepted to the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2025 in Wuhan, China [PDF].
08, 2025 - Invited and honored to be selected as Morgan State Faculty along with 14 Morgan State students to visit the Bloomberg LP Headquarters in New York City, NY.
05, 2025 - Honored to be selected to participate in the 2025 Faculty Development Summer Institute (FDSI), hosted by the Atlanta University Center (AUC) Data Science Initiative in Atlanta, Georgia.
03, 2025 - Honored to be selected as a keynote speaker at Yale’s “Call to Create” event to discuss Linguistic Justice in AI at Yale University, New Haven, Connecticut.
03, 2025 - Excited to share that 3 of our abstracts have been accepted for poster presentation at the Center for Equitable Artificial Intelligence and Machine Learning Systems 2025 National Symposium on Equitable AI.
02, 2025 - Honored to be selected as an AIM-AHEAD & NCATS HDSTP Mentor.
02, 2025 - Invited and honored to be selected as 1 of the HBCU Faculty to attend the NSF Funded STEAMSEAS HBCU Faculty Expedition application March 16-23, 2025 from Port Everglades, FL to Woods Hole, MA, on the RV Neil Armstrong.
01, 2025 - Honored to be selected as a mentor for the National Institutes of Health (NIH), AIM-AHEAD and the National Center for Advancing Translational Sciences (NCATS) Health Data Science Training Program (HDSTP) from January to July 2025.
01, 2025 - Excited to share that 3 of our abstracts have been accepted for poster presentation at the 2025 Society of Epidemiologic Research (SER) Mid-Year Meeting.
- “Towards Data-Driven Diabetes Care: Identifying Key Biomarkers and Risk Factors for Type 2 Diabetes through AI Models”
- “Improving Hypertension Prediction and Management through AI: A Focus on Socioeconomic, Environmental, and Demographic Influences”
- “Exploring Socioeconomic and Demographic Factors in Coronary Artery Disease: Using AI and Knowledge Graphs to Identify Healthcare Inequalities”

10, 2024 - Officially launched my research lab, the Machine Intelligence and Data Science (MINDS) Lab headquartered at Morgan State University.
09, 2024 - Highlighted in a City University of New York monthly newsletter title, “CUNY Calls Out! CUNY Pays Off!”.
09, 2024 - Invited to serve as an in-person panelist at Morgan TechFest.
08, 2024 - Started an Advisory position for the Society for the Advancement of Computer Science (SACS) at Morgan State University.
07, 2024 - Awarded a Chan Zuckerberg Initiative (CZI) Award (subaward) from Boston University.
04, 2024 - Highlighted in Medgar Evers College’s Campus News in an article title, “From track star to doctor: Jamell Dacon’s Medgar Made journey”.
04, 2024 - Awarded the 2024-2025 Faculty Research Initiative Grant by the Thurgood Marshall College Fund (TMCF) and the Novartis US Foundation.
02, 2024 - Awarded a U.S. Army DEVCOM Army Research Laboratory 2024 U.S. Department of Defense (DoD) HBCU/MI Summer Faculty Research Fellowship Award.
02, 2024 - Awarded an Office of Naval Research (ONR) Summer Faculty Research Program (SFRP) Award.
02, 2024 - Invited and honored to be selected as 1 of 5 HBCU Faculty/Research Professionals to serve as an in-person Technical Advisor for the Research Affinity Cohort (RAC) Program hosted at Clark Atlanta University in Atlanta, Georgia in June 2024.

11, 2023 - Higlighted in a Michigan State University news article title, “Graduate Voice: Jamell Dacon Shares His Doctoral Journey”.
11, 2023 - Awarded a Capacity Building mini grant for Research at Minority-Serving Institutions (CyBR-MSI: IRR).
09, 2023 - Started a Tenure-Track Assistant Professor of Computer Science position at Morgan State University.

Vitae

View my academic background, research experience, publications, awards, and professional service.

Professional Experience

My professional experience spans research, teaching, mentorship, and interdisciplinary collaboration across artificial intelligence, machine learning, computational linguistics, healthcare AI, and computing education.

2023 - Present

Assistant Professor (Tenure-track)

Morgan State University

Assistant Professor of Computer Science & Research Faculty at the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS). Research focuses on developing robust, interpretable, and human-centered AI systems for complex societal domains—including healthcare, education, and the social sciences—to improve decision-making, and drive large-scale societal impact.

Service Research Teaching

2022 - 2023

Research Scientist

Google LLC

Research interests span Multi-modal Machine Learning, Natural Language Processing, and Computational Linguistics, with a focus on developing human-centered AI systems to identify communicative trends between language and canonical features.

Research Optimization Collaboration

2022

Machine Learning Scientist

Agile Analytics Team, Kimberly-Clark

Specialized in predictive modeling and machine learning optimization to enhance supply chain delivery productivity and model reliability.

Automation Optimization Governance

Education & Qualifications

My academic background is rooted in computer science and mathematics, with a focus on artificial intelligence, machine learning, computational linguistics, and data science. I have a strong foundation in research methodologies, interdisciplinary collaboration, and the development of AI systems for socially impactful applications.

Doctor of Philosophy

Michigan State University

Computer Science

2020 - 2023

NSF IMPACTS Graduate Research Fellowship (GRFP)

Master of Science

Michigan State University

Computer Science

2018 - 2020

University Enrichment Fellowship

Bachelor of Science

City University of New York - Medgar Evers College

Mathematics

2014 - 2018

Magna Cum Laude

Associate of Science

City University of New York - Medgar Evers College

Computer Science

2016 - 2017

Summa Cum Laude

Research Areas

My research focuses on trustworthy AI for socially consequential domains, with emphasis on education, health, language justice, and robust machine learning.

Trustworthy NLP and Language Justice

Developing methods to study bias, robustness, dialect variation, harmful language, and fairness in language technologies, with a focus on African American English and other underrepresented language varieties.

Educational AI and Learning Analytics

Developing AI systems that support teaching, learning, and student feedback, including robust educational retrieval, co-regulation, and evaluation under distribution shift.

Health AI and Clinical Decision Support

Building personalized, data-driven AI for chronic disease management, predictive analytics, and scalable health informatics in high-stakes clinical settings.

AI Robustness, Interpretability, and Distribution Shift

Developing methods that improve reliability, generalization, interpretability, and methodological rigor in AI systems used in high-stakes domains.

Publications

* equal contributor
† denotes undergraduate student researcher mentored by Dr. Jamell Dacon
‡ denotes graduate student researcher mentored by Dr. Jamell Dacon
♠ denotes a publication given as a Plenary/Oral Presentation or Spotlight Talk
♣ denotes a publication given as a Poster Presentation

Note: Publications are listed in reverse chronological order, with the most recent publications appearing first. (Highly Refereed Conference Papers i.e., acceptance based on peer review of full paper presented as oral/spotlight talks or poster presentation)

♠ DeBoris Leonard^‡*, Ricky Gole^‡* and Jamell Dacon. “Prescriptive Persistence: Quantifying the Breakdown in Human-AI Pedagogical Co-Regulation in ELL Writing Feedback”. In the Proceedings of the 13th ACM Conference on Learning at Scale (L@S) 2026. (acceptance rate 22.0%)

♠ Ricky Gole^‡ and Jamell Dacon. “The Semantic Gap in Behavioral Embeddings: Why Linear Methods Fail for Educational RAG in Mathematics”. In the Proceedings of 19th International Conference on Educational Data Mining (EDM) 2026. (acceptance rate 23.0%)

♠ Jamell Dacon, et al. “Optimizing Insulin Dosing for Type 1 Diabetes with Thyroid Dysfunction Using Q-Learning: A Personalized Approach to Chronic Disease Management”. In the Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026. (Best Paper Runner-up Award) (acceptance rate 26.0%)

♠ Jamell Dacon, et al. “Manifold-Informed Cohort Discovery (MICD): A Framework for Uncovering Latent Risk Signals in Imbalanced Healthcare Data”. In the Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026. (acceptance rate 26.0%)

♠ Jamell Dacon, Ricky Gole^‡, Anuva Nuzhat^†, Holy Agyei^†, Obaloluwa Wojuade^†, Mikayla Brown^†. “BIO-DQNA: Meta-Learning and Contrastive Reinforcement Learning for Personalized Comorbidity Management in Type 1 Diabetes and Hypertension”. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. (acceptance rate 19.0%)

♣ Mikayla Brown^†, et al. “Towards Data-Driven Diabetes Care: Identifying Key Biomarkers and Risk Factors for Type 2 Diabetes through AI Models”. Society of Epidemiologic Research 2025 Mid-Year Meeting (SER), 2025. (Non-archival) (acceptance rate 24.1%)

♣ Chelsea Minard^†, et al. “Exploring Socioeconomic and Demographic Factors in Coronary Artery Disease: Using AI and Knowledge Graphs to Identify Healthcare Inequities”. Society of Epidemiologic Research 2025 Mid-Year Meeting (SER), 2025. (Non-archival) (acceptance rate 24.1%)

♣ Chukwuemeka Obasi^†, et al. “Improving Hypertension Prediction and Management through AI: A Focus on Socioeconomic, Environmental, and Demographic Influences”. Society of Epidemiologic Research 2025 Mid-Year Meeting (SER), 2025. (Non-archival) (acceptance rate 24.1%)

Sourabh Palande, et al., Jamell Dacon, et al. “Topological data analysis across the evolution of flowering plants reveals a core gene expression backbone that defines plant form and function”. PLOS Biology, 2023. (impact factor 9.8)

♣ Jamell Dacon and Jiliang Tang. “Beyond Race and Gender: A Look at Sociodemographic Biases Toward Persons with Disabilities”. In Proceedings in the 9th International Conference on Computational Social Science (IC²S² 2023), 2023. (Non-archival) (acceptance rate 77.0%)

♣ Jamell Dacon and Jiliang Tang. “Can We Identify and Dismantle “ISMs” that Plague Our Society: An Online Approach”. In Proceedings in the 9th International Conference on Computational Social Science (IC²S²), 2023. (Non-archival) (acceptance rate 77.0%)

♠ Jamell Dacon, Haochen Liu and Jiliang Tang. “Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference”. In Proceedings in the 29th International Conference on Computational Linguistics (COLING), 2022. (acceptance rate 28.1%)

♠ Jamell Dacon. “Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English”. In Proceedings of the 2nd Workshop on Bridging Human-Computer Interaction and Natural Language Processing (NAACL), 2022. (acceptance rate unknown)

♠ Jamell Dacon, et al. “Detecting Harmful Online Conversational Content towards LGBTQ+ Individuals”. Queer in AI Workshop (NAACL), 2022. (acceptance rate unknown)

♣ Jamell Dacon and Jiliang Tang. “Examining Word Representations between #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020”. In Proceedings in the 8th International Conference on Computational Social Science (IC²S²), 2022. (Non-archival) (acceptance rate 24.1%)

♣ Jamell Dacon. “Understanding African American English on a Token-Level Beyond Accuracy”. In Proceedings in the 8th International Conference on Computational Social Science (IC²S²), 2022. (acceptance rate 24.1%)

♠ Jamell Dacon, Haochen Liu and Jiliang Tang. “Using Inference to Mitigate Linguistic Bias Against African American English”. In Proceedings in the 8th International Conference on Computational Social Science (IC²S²), 2022. (Non-archival) (Plenary/Oral Spotlights: acceptance < 3%)

♠ Jamell Dacon and Haochen Liu. “Detecting and Examining Gender Bias in News Articles”. In Proceedings in the 7th International Conference on Computational Social Science (IC²S²), 2021. (Non-archival) (acceptance rate 24.1%)

♠ Jamell Dacon and Haochen Liu. “Does Gender Matter in the News? Detecting and Examining Gender Bias in News Articles”. In Companion Proceedings in the 30th International Web Conference (WWW), 2021. (acceptance rate 22.0%)

♠ Haochen Liu^*, Jamell Dacon^*, et al. “Does Gender Matter? Towards Fairness in Dialogue Systems”. In Proceedings in the 28th International Conference on Computational Linguistics (COLING), 2020. (acceptance rate 33.4%)

Tyler Derr, Zhiwei Wang, Jamell Dacon, and Jiliang Tang. “Link and Interaction Polarity Predictions in Signed Networks”. Social Network Analysis and Mining (SNAM), 2020. (impact factor 2.7)

PREPRINTS

Jamell Dacon. “Are You Worthy of My Trust? A Socioethical Perspective on the Impacts of Widespread AI Systems on the Environment and Human Society”, 2024.

Sourabh Palande, et al., Jamell Dacon, et al. “The Topological Shape of Gene Expression across the Evolution of Flowering Plants”, 2023.

Jamell Dacon and Jiliang Tang. “What Truly Matters? Using Linguistic Cues for Analyzing the #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020”, 2021.

Contact

Feel free to reach out regarding research collaborations, speaking opportunities, interdisciplinary projects, or discussions related to artificial intelligence, data science, and computing education.

Let's Connect!

I’m always open to discussing research, innovation, mentorship, and collaborative opportunities.

Email jamell.dacon@morgan.edu

Research & Collaboration

Have questions or want to collaborate on AI research? Feel free to reach out — I’m always excited to connect with fellow researchers, innovators, and organizations.

Disclaimer

Any opinions, findings, conclusions, or recommendations expressed on this website are those of the author and do not necessarily reflect the views of any organization.