Curriculum Vitae

Ariel Ghislain Kemogne Kamdoum

PhD researcher in Biostatistics developing interpretable biostatistical, machine-learning, and representation-learning methods for genomic discovery, complex disease analysis, and precision medicine.


Profile

I develop novel biostatistical and representation-learning methods to identify genetic factors underlying complex diseases such as cancer and cardiovascular disorders, with a strong emphasis on interpretability and mechanistic insight. My research bridges statistical genetics, deep learning, and explainable AI to improve our understanding of disease biology and heritability.


Research Interests

Biostatistics Statistical Genetics Artificial Intelligence Machine Learning Deep Learning Computer Vision Optimization Bioinformatics Mathematical Modelling

Publications

Peer-Reviewed Publications

2026
Journal Article

MOKA: a pipeline for multiomics bridged SNP-set kernel association test

David Enoma, Dinghao Wang, Ariel Ghislain Kemogne Kamdoum, Rodrigo Ortega Polo, Quan Long, Jingni He.

G3: Genes | Genomes | Genetics, Volume 16, Issue 2, February 2026, jkaf296.

Preprints and Benchmark Contributions

2026
Preprint

COMPOSITE-Stem

Waters, K., Nuzzi, L., Looram, T., Tomasiello, A., Kemogne Kamdoum, A. G., Li, B., Sileo, D., Kretov, E., Fournier-Facio, F., Soloupis, G., Kassahun, H., Wolff, H., Cai, J., Li, L., Roth, M., Naiya, M., Guo, N., Tang, Q., Wheeler, R., Sala, S., Popov, S., Dillman, S., and Li, Y.

arXiv preprint arXiv:2604.09836.

2025
Preprint

Humanity's Last Exam

Phan, L., Gatti, A., Han, Z., Li, N., Hu, J., Zhang, H., ... Ariel Ghislain Kemogne Kamdoum ... and Wykowski, J.

arXiv preprint arXiv:2501.14249.

Manuscripts Under Review

2026+
Under Review

gVAE: Stable and interpretable representation learning for high-dimensional genomic cohorts with moderate sample sizes

Kemogne A., Weeraman J., Ganeshiny S., Wang D., Chernenkoff S., Enoma D., Li C., Linzhi Cai, Chekouo T., Zhang Q., Long Q.

Manuscript under review.

2026+
Under Review

GEVAT: a representation-learning framework for complex trait association mapping

David O. Enoma, Hongjiang Chu, Dinghao Wang, Li Shu, Ariel Ghislain Kemogne Kamdoum, Janith Weeraman, Lang Wu, Paul M. K. Gordon, A. P. Jason de Koning, Paul D. Arnold, M. Ethan MacDonald, Weijia Cai, Linzhi Cai, Rodrigo Ortega Polo, Quan Long, and Chen Cao.

Manuscript under review.

More publications and citation updates are available on Google Scholar .


Education

2022–Present

PhD in Biostatistics

University of Calgary, Canada

Supervisor: Dr. Quan Long, Assistant Professor of Bioinformatics, Cumming School of Medicine; Department of Biochemistry and Molecular Biology; Department of Medical Genetics; Department of Mathematics and Statistics, University of Calgary.

Co-supervisor: Dr. Thierry Chekouo Tekougang, Assistant Professor, Department of Mathematics and Statistics, University of Minnesota.

2019–2021

M.Sc. in Machine Intelligence

African Master’s in Machine Intelligence, Ghana

Essay project: Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions.

Supervisor: Dr. Moustapha Cissé, Founder and Director of AMMI and former Head of Google AI Center in Accra, Ghana.

2018–2019

M.Sc. in Mathematical Sciences

African Institute for Mathematical Sciences, Senegal

Grade: Very Good Pass.

Essay project: Abelian Extension and Crossed Module for Lie Algebras.

Supervisor: Dr. André Saint Eudes Mialebama Bouesso, Marien Ngouabi University, Brazzaville, Congo.

2016–2018

M.Sc. in Mathematics

University of Dschang, Cameroon

Rank in class: 1st / 14. Grade: Very Good Pass.

Essay project: (Co)homologie des espaces de configuration.

Supervisor: Dr. Calvin Tcheka, University of Dschang, Cameroon.

2012–2016

B.Sc. in Mathematics and Computer Science

University of Dschang, Cameroon

Rank in class: 2nd / 100.


Scholarships, Grants, and Awards

  • Alberta Innovates Graduate Scholarship, $31,000/year for three years, University of Calgary, 2023–2026.
  • Indigenous and Black Momentum Scholarship in Science, $25,000, University of Calgary, 2022–2023.
  • Graduate Assistant Teaching Excellence Award, Department of Mathematics and Statistics, University of Calgary.
  • Student Research Presentation Award (Honourable Mention), Statistical Society of Canada Annual Meeting, 2026.
  • FIRST Jobs: TechBOOST Internship, Technology Alberta, AI Systems Intern at VirtuClinic, 2024–2025.
  • University of Dschang Special Academic Excellence Award.
  • Best Graduating Student of Master 2 in Algebra, Department of Mathematics and Computer Science, University of Dschang, 2018.
  • Laureate at AIMS Senegal, 2018.
  • Mastercard Foundation Scholar, AIMS Senegal, 2018–2019.
  • Google and Facebook Scholarship, AMMI Ghana, 2019–2020.
  • Laureate at AMMI Ghana, 2019–2020.
  • AIMS Mathematical Sciences for Climate Resilience Internship Program, May–October 2021.

Conferences and Forums

  • SSC 2026, Statistical Society of Canada, McMaster University, Hamilton, Ontario, Canada.
  • NeurIPS 2024, Vancouver Convention Centre, Canada.
  • BIRS Workshop, Novel Statistical Approaches for Studying Multi-omics Data, Banff International Research Station, Canada, July 2025.
  • CIMPA, Centre International de Mathématiques Pures et Appliquées, Yaoundé, Cameroon, 2018.
  • 7th Heidelberg Laureate Forum, Germany, 2019.
  • Future of Science Conference, Kigali, Rwanda, 2019.
  • 11th Gene Golub SIAM Summer School, Theory and Practice of Deep Learning, South Africa, 2021.
  • 8th Heidelberg Laureate Forum, digital participation, 2021.
  • Hausdorff School, Foundational Methods in Machine Learning, Bonn, Germany, 2022.
  • BioNet Conference, University of Calgary, Canada, 2025. Oral talk and poster presentation.
  • BMB Advance Conference, University of Calgary, 2023. Talk on representation learning and transfer learning in genetics and omics.

Skills

Languages

English, French

Programming

Python, R, Java, MATLAB/Octave, SQL, NoSQL

Machine Learning

PyTorch, deep learning, optimization, computer vision, bioinformatics

Data and Systems

MongoDB, MySQL, Metabase, Git, GitHub, Excel, LaTeX


Online Certifications

  • Machine Learning, Stanford University, Coursera.
  • Introduction to Data Science in Python, University of Michigan, Coursera.
  • Applied Machine Learning in Python, University of Michigan, Coursera.
  • Natural Language Processing in TensorFlow, DeepLearning.AI, Coursera.
  • Mathematics for Machine Learning: Linear Algebra, Imperial College London, Coursera.
  • Introduction to Deep Learning, NRUHSE, Coursera.
  • Technical Support Fundamentals, Google, Coursera.
  • Business Metrics for Data-Driven Companies, Duke University, Coursera.

Work Experience

2024–Present

Prompt Engineer / AI Quality Control

Center for AI Safety, Outlier, and Scale AI Labs

Collaborating on improving large language model capabilities in reasoning, summarization, and general knowledge. Contributed to Humanity’s Last Exam, a multimodal benchmark designed to evaluate frontier AI systems on complex academic questions.

Oct. 2024–Dec. 2025

AI Technical Lead and Business Development

VirtuClinic Corporation, Alberta, Canada

Developed AI-powered automation systems and AI digital agents, including Digital Health Advisors, to enhance healthcare and wellness services. The work focused on lead management, patient engagement, business analytics, operational efficiency, and digital health innovation.

2022–Present

Graduate Teaching Assistant

Department of Mathematics and Statistics, University of Calgary

Provided teaching and instructional support, including tutorial delivery, laboratory supervision, office hours, grading, assignment support, and preparation of instructional materials.

2022–Present

Teaching Assistant in Deep Learning and Neuroscience / Production Team Member

Neuromatch Academy

Supported students in deep learning and computational neuroscience through technical mentoring, project guidance, and problem-solving support during the Neuromatch Academy summer school.

May–Oct. 2021

Data Scientist Intern

ICRISAT-MANOBI Africa, Senegal

Worked on digital solutions and data-intelligence services for African water and agricultural sectors, including monitoring and evaluation, dashboarding, data exploration, and decision-support analytics.

Jun.–Dec. 2020

Freelance Teacher in Data Science and Machine Learning

Hamoye Tutor Franchise Program, Lagos, Nigeria

Planned and structured learning experiences, including curriculum mapping, lesson planning, individual learning support, and group-learning facilitation.

Jun.–Dec. 2020

Data Engineer / MLOps Intern

Hamoye AI Labs

Supported machine-learning deployment workflows, including model production, testing, optimization for low latency, scalability, and data-processing readiness.

May–Jun. 2020

Global Intern in Data Analysis

TakenMind Inc.

Worked on data analytics and finance-related projects involving large-scale data management, machine-learning model building, and insight generation.


References

PhD Supervisor

Dr. Quan Long

Assistant Professor, Department of Mathematics and Statistics; Department of Biochemistry and Molecular Biology, University of Calgary.

Email: quan.long@ucalgary.ca

Reference

Dr. Paul Taylor

Staff Scientist, National Institutes of Health, USA.

Email: paul.taylor@nih.gov