Afeez Fakunle
Data Scientist @ Microsoft
About
Innovative and results-oriented data scientist and artificial intelligence engineer and researcher with knowledge in computer vision, natural language processing, reinforcement learning, and applications and experience working in fast-paced environments.
United States
San Jose
Consumer Electronics
Artificial Intelligence (AI), Statistical Modeling, Retrieval-Augmented Generation (RAG), Agentic AI Development, Agentic Automation, Brain-computer Interfaces, MNE python, Pandas (Software), EEGLAB, Robot Operating System (ROS), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Multi-modal AI, Vision-Language Models (VLMs), Multi-modal Data Augmentation, Performance Optimization, Transfer Learning, Experimentation and Evalaution, Generative AI
Experience
Data Scientist
Microsoft
Mountain View, California, United States
Machine Learning Intern
Apple
Sunnyvale, California, United States
Vision Pro - Software Performance team
Machine Learning and AI Researcher
Santa Clara University
California, United States
-Enhanced LLaVA pre-training with MixGen multi-modal data augmentation, boosting performance by 0.3% on the OKVQA visual question answering task and improving overall model accuracy. -Implemented de-noising methods based on VAEs achieving a 19% increase in SNR and a 12% reduction in RMSE over ICA, enhancing fetal ECG signal clarity and diagnostic reliability in pre-natal care.
Research And Teaching Associate
Lead City University
Ibadan, Oyo, Nigeria
-Supervised a faculty research project leading to generation of electric power for University use by harnessing solar energy, reducing electric power cost by 15%. -Prepared graphical-oriented lecture notes and courseware for EEE 408 (Digital Signal Processing) and EEE 313 (Computer Aided Design), enhancing students' performance by about 60% and 65% respectively compared to last academic year.
Automation Engineer
Guinness Nigeria
Lagos
-Led a conveyor improvement project with precise drive pulley and belt installation and optimized motor speeds using VFDs and PLCs, cutting machine downtime by 10%. -Executed electrical maintenance schedules, reducing intermittent machines overhauling and maintenance costs by about 20%.
Robotics and AI Research Fellow
Applied Artificial Intelligence and Robotics Research Lab
Obafemi Awolowo University
-Attained a 50% reduction in joint torque error (RMSE) for a stroke rehabilitation robot with carefully designed system identification experimental procedures. -Reduced robot task completion time by 20% in a human-robot interaction environment through the implementation of optimal iterative learning control.
Education
Santa Clara University
Electrical and Computer Engineering
Afeez Fakunle's Contact Information
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