Ph.D. Candidate in Computer Science
Saint Louis University
Pioneering cross-modal neuromorphic computing with 603× energy efficiency breakthrough. Advancing brain-inspired AI systems for edge computing and autonomous applications.
I am a Ph.D. candidate in Computer Science at Saint Louis University, specializing in neuromorphic computing and cross-modal artificial intelligence. As leader of Project Phasor, I conduct groundbreaking research on memory mechanisms in spiking neural networks across different sensory modalities.
My research has achieved extraordinary recognition, including a 2025 Congressional invitation to advise on neuromorphic computing policy, membership in the NIH BRAIN Initiative, and international media coverage for achieving 603× energy efficiency improvements over traditional neural networks.
With 8 peer-reviewed publications and presentations at premier conferences (NeurIPS, ICML, AAAI, CVPR), my work bridges neuroscience, artificial intelligence, and public policy to advance energy-efficient AI systems for real-world deployment.
Cross-Modal Neuromorphic Computing
Leading multi-institutional research investigating memory mechanisms in spiking neural networks across visual and auditory modalities. First comprehensive cross-modal ablation study demonstrating modality-specific specialization and design principles for neuromorphic hardware.
Brain-Inspired Computing
Contributing to the nation's largest neuroscience research program, applying neuromorphic computing principles to advance understanding of brain function and develop transformative neurotechnologies for AI systems.
Congressional Testimony
Invited expert witness to United States Congress (2025) on neuromorphic computing policy. Advised on national AI strategy, technological competitiveness, and applications for national security and edge computing systems.
arXiv:2512.18575 | December 2025
First comprehensive cross-modal ablation study of memory mechanisms in SNNs. Achieved 603× energy efficiency with >97% sparsity and 94.41% cross-modal accuracy. Featured in Quantum Zeitgeist.
XAI4Science Workshop @ NeurIPS 2025
Women in Machine Learning Workshop @ NeurIPS 2025
DeepMath Conference 2025
NICE 2026 Conference
Master's Thesis, African University of Science and Technology, 2021
Conference Presentations: NeurIPS 2025 (3 papers), ICML 2025, AAAI 2026 (accepted), CVPR 2024 (2 workshops), DeepMath 2025, Open Neuromorphic 2024, Telluride Workshop 2024
Invited to United States Congress to advise on neuromorphic computing policy and national AI strategy
Research featured in Quantum Zeitgeist for achieving 603× energy efficiency breakthrough
Selected for premier federal neuroscience research program advancing brain-inspired technologies
Leading multi-institutional neuromorphic computing research with NCSU, Luxmuse AI, and independent researchers
Competitive research funding for graduate studies at African University of Science and Technology
Email: blessing.effiong@slu.edu
Office: School of Science and Engineering
Saint Louis University
St. Louis, Missouri, USA