Daniel Ajuzie

I am a computational systems scientist with over 6 years of expertise in mathematical modeling, algorithm development, and large-scale optimization. I have a proven record of driving revenue uplift and operational efficiency in domains including biological research, energy, and airline operations. I specialize in using advanced computational methods such as Mixed Integer Programming (MIP), stochastic optimization, and machine learning to solve complex, real-world problems. My technical skills span multiple programming languages, including Python, MATLAB, R, and SQL, and I am experienced in deploying serverless applications in cloud environments like AWS.

I have a strong background in biological modeling, particularly in the areas of bacterial stress response and biofilm modeling, and have successfully led several high-impact projects in the airline industry. As a researcher and mentor, I am dedicated to translating complex data into actionable insights and supporting the growth of others in the field

I am a computational systems scientist with over 6 years of experience in mathematical modeling, algorithm development, and optimization. My expertise spans multiple domains, including biological research, energy, and airline operations. In my recent role as a Visiting Researcher at UW-Madison, I led the development of multi-phenotype MIP ensemble modeling pipelines, achieving significant improvements in prediction accuracy and coverage. I also built scalable pipelines using Python and MATLAB for aligning simulations with experimental data. Previously, as a Graduate Research Assistant at the University of Houston, I worked on modeling bacterial iron and oxidative stress, improving in vitro and in silico agent-based models. I also lectured on core modeling concepts in biology and supported students as a mentor. My work in airline optimization involved developing a Gurobi-based MIP that projected significant revenue increases and operational improvements, including reducing turnaround times and improving on-time departures. I have a proven ability to solve complex optimization problems, develop efficient algorithms, and work with cross-functional teams to implement solutions in real-world applications.

Ph.D. in Biomedical Engineering, University of Houston (GPA: 3.90) – Specialized in computational modeling and optimization for biological systems.
B.S. in Electrical Engineering, University of Ibadan (GPA: 3.47) – Strong technical foundation in engineering principles