he went on to accomplish graduate degrees in Applied Mathematics and Operations Research & Financial. from City College and Princeton University, respectively. More recently, Dr. Ekwedike completed his post-graduate studies at Princeton under the school’s Presidential Fellowship, achieving a Ph.D. in Operations Research & Financial Engineering. In the process, he learned a great deal about advanced probabilistic modeling techniques, which are of great value in finance for making optimal decisions under volatile market uncertainty. Additionally, Emmanuel completed his dissertation on solving the resource allocation problem eciently using the combination of probabilistic modeling and machine learning.He published the 300-page dissertation under the title, Optimal Decision Making via Stochastic Modeling and Machine Learning: applications to resource allocation problems and sequential decision problems. Over the past decade, Emmanuel continued to shape his career through diverse research positions. He has developed statistical methods and parameters for weather forecasting at City College, innovated flexible learning methodologies involving feedback-based tree search algorithms for solving sequential decision problems at Tencent America, created predictive machine learning models for real-world problems and integrated them into application programming interfaces (API) to uncover share actionable insights as a Princeton Ph.D. Fellow, and so much more. In his current role as a Machine Learning Research Scientist at Peraton Labs, he enjoys building scalable gradient-based Trojan detection for AI systems designed for Natural Language Processing (NLP) and computer vision tasks, among other projects. Dr. Ekwedike has delivered powerful speeches on these topics at sundry institutions and events, from his alma mater, Princeton University, to UC San Diego, Rutgers University, Wayfair, the International Conference on Machine Learning (ICML), and the INFORMS Business Analytics Conference. Additionally, this acclaimed researcher has contributed to peer-reviewed scientific literature. As an avid learner, Emmanuel makes it a point to maximize his performance and capabilities by staying ahead of emerging developments, trends, and information. He uses his ever-expanding knowledge and skills to help small businesses implement AI and ML technologies to automate operations and drive growth. He also develops ML algorithms for these clients and teaches them how to train these programs themselves. Those he works with rave about his ability to articulate important information from complex research to achieve a basic yet thorough understanding of the content for nonprogrammers. Emmanuel’s uncanny communication and interpersonal skills, zest for collaboration, impeccable leadership and management, and highly innovative problem-solving abilities are what truly sets him apart from his competitors. He is highly experienced in real-world application of his mastery. Inspired by diversity, he finds valuable lessons in culture-rich, international travel, which inspires him to build useful context around data. Ekwedike firmly believes that our ability to understand people is what brings data to life, creating a global approach to this field of science. He strives to extract meaningfulness from every project he takes on while catering to his clients’ needs and delivering a positive impact. ..close