Name: Joed Ngangmeni
Pronouns:
Institution: Howard University
Department: Computer Science
Biography:
I’m Joed Ngangmeni, a 3rd year PhD student at Howard University, where I also got a Bachelor’s in Computer Science with a concentration in Mathematics, studying Artificial Intelligence with the goal of reducing bias in machine learning algorithms for military and civilian applications. Since the beginning of my matriculation, I have devoted myself to pursuing higher education and that effort led me to participate in the SRP program last summer as an intern at Sandia National Labs. Unfortunately, that internship came to a close due to time constraints and school resuming but I would love to participate again. I am in the secondary stages of my degree, where I am done with courses and am just focusing on research and my dissertation.
Academic Status: PhD Student
Year in program: 3rd
Research Area/Department: Computer Science; Data Science; Machine Learning/AI
Other, specify:
Major/Specialty: Artificial Intelligence/Machine Learning
Degrees Earned or in Progress: PhD/Artificial Intelligence/2024 Bachelors/Computer Science/2021
What courses or academic preparation have you completed to prepare for a summer internship experience?
- Publishing a research article on the development of better Uncertainty Quantification methods that specifically address Model Form Error through the use of Random Forest modeling – Participation in SRP this past summer – Extensive Machine Learning and Artificial Intelligence courses – Participation in DOE program reviews – both the Predictive Science Academic Alliance Program (PSAAP III) Review at UT Austin and the one at the University of New Mexico – Participation in both Artificial Intelligence for Science and Security (AI4SES 3) in Bowie, Maryland, and AI4SES 2 in Davis, California
Have you published any research or worked on research/technical projects? Yes
Where has your research been published or where have you conducted research/technical projects? Sandia National Lab Kathryn Maupin – kmaupin@sandia.gov Dan Turner – dzturne@sandia.gov
Please describe your research/academic interests:
I am working on reducing bias in machine learning algorithms for military and civilian applications. So far, the only publication I have is in progress to be published as a Sandia Report about developing better Uncertainty Quantification methods where my specific target was Model Form Error through the use of Random Forest modeling.
Computational and Data Science Areas:
Computer Science; Data Analytics and Visualization; Machine Learning and AI
Research Synergy:
I am interested in developing my dissertation topic which, as of right now, is centered around developing a Generative Adversarial Network that is robust to noisy, missing, or faulty data. I have some interest in sparse data because it is remarkably prevalent and tends to affect the accuracy of machine learning algorithms. Since my actual research goal is the reduction of bias in machine learning algorithms for military and civilian applications, the range of projects I can work on is very broad and would have applicability in all corners of the machine learning spectrum. I have slight experience with probabilistic methods and Bayesian distributions but hope to learn more about them. I have also worked on understanding Uncertainty Quantification methods where my specific target was Model Form Error through the use of Random Forest modeling.
Motivation:
I made so much progress in my research when I participated in this program this past summer, so I firmly believe that it will allow me to get more experience and to move further in my academic journey, maybe even to complete my dissertation.
Lightning Talk Title: Continuous Random Forest for Bias Mitigation in Machine Learning Algorithms