Doctor of Philosophy (Ph.D.)
Atmospheric Sciences
Howard University
Expected 2026
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Staff
Staff
Ayanna Jones ( she, her, hers)
Assistant Director
Department/Office
- Research and Education for Promoting Safety
School/College
- College of Engineering and Architecture (CEA)
Biography
Ayanna Jones, M.Sc. is a materials scientist and computational researcher specializing in machine learning-assisted materials design, thermodynamic simulation, and data-constrained ecosystem modeling. She is in the process of completing her Ph.D. in Atmospheric Sciences at Howard University, where her dissertation applies molecular dynamics and machine learning to engineer phase change materials for battery thermal management. Her research has taken her from Argonne National Laboratory, where she synthesized and characterized novel PCM composites, to NASA's Jet Propulsion Laboratory, where she developed Bayesian model-data fusion frameworks for terrestrial carbon cycle modeling as a NASA Maximizing Student Potential Graduate Research Fellow. She holds an M.S. in Chemistry from Emory University and an M.S. in Earth and Atmospheric Sciences from Georgia Tech, and earned her B.S. in Chemistry, Magna Cum Laude, from Clark Atlanta University. Beyond the lab, Ayanna is the co-founder and President of BlackInChem, a nonprofit recognized with the Royal Society of Chemistry Inclusion and Diversity Prize, reflecting her long-standing commitment to expanding access and representation in the chemical sciences.
Education & Expertise
Education
Master of Science (M.S.)
Chemistry
Emory University
2023
Master of Science (M.S.)
Earth and Atmospheric Sciences
Georgia Institute of Technology
2018
Bachelor of Science (B.S.)
Chemistry
Clark Atlanta University
2016
Research
Research
Specialty
Materials Informatics, Molecular Dynamics Simulations, Remote Sensing Integration, Clean Energy Applications, Artificial IntelligenceAccomplishments
Accomplishments
Ernest E. Just Life Sciences Society Award for Outstanding Leadership and Service in the Life Sciences
United Negro College Fund (UNCF)
Royal Society of Chemistry Inclusion and Diversity Prize
Royal Society of Chemistry
Quayle Spectrum Scholar Award
Department of Chemistry, Emory University
Maximizing Student Potential Fellowship
NASA Jet Propulsion Laboratory
Quayle New Student Award
Department of Chemistry, Emory University
Centennial Scholars Fellowship
Laney Graduate School, Emory University
Women In Natural Sciences Fellowship
Laney Graduate School, Emory University
Provost Academic Excellence Scholarship
Clark Atlanta University
A prestigious merit award for incoming freshman which covers all academic and housing expenses for four years
Featured News
Featured News
Kamin Science Center (2025)
Read: Q&A with Ayanna Jones
Emory University 2036 Podcast (2023)
Listen: A Future Where #BlackInChem Isn't An Anomaly
Bustle (2020)
Read: How One PhD Student Tackles STEM’s Lack Of Representation Head On
Nature Chemistry (2020)
Publications and Presentations
Publications and Presentations
CARDAMOM Framework for Data‐Constrained Terrestrial Ecosystem Modeling
A Review of the CARDAMOM Framework for Data-Constrained Terrestrial Ecosystem Modeling, Global Change Biology, 2025
This review examines CARDAMOM (CARbon DAta MOdel fraMework) and its associated DALEC process-based model suite, tools purpose-built for fusing ecological observations with terrestrial ecosystem models. Unlike most process-based models, which use observations only for benchmarking, CARDAMOM applies a Bayesian, Markov Chain Monte Carlo approach to directly assimilate diverse data—from in situ measurements to satellite observations—into model parameters and carbon pool states. This allows it to capture spatially variable ecosystem responses to environmental change with a flexibility few other tools offer. The review discusses key challenges, including data quality limitations, parameter equifinality, and trade-offs between model complexity and predictive skill, along with potential solutions like incorporating additional observational constraints. It closes with community recommendations for integrating emerging datasets and machine learning methods, deepening collaboration across remote sensing, field, and modeling communities, and expanding CARDAMOM's use in localized ecosystem monitoring and decision-making.