
Cody
PhD candidate
Expertise
Biomedical Engineering
Polygence mentors are selected based on their exceptional academic background, teaching experience, and unique ability to inspire the next generation of innovative thinkers and industry leaders.
Biomedical Engineering
Semiconductors, Manufacturing, Mathematics, 3D modeling / Design, CAD, Prototyping, Quantum Dots, Display Technology
Plasma Physics, Aerospace, Mechanical Engineering, Applied Mathematics, Computational Fluid Dynamics
Biology, Biomedical Sciences, Bioengineering, Biomedical Engineering
Cell & Tissue Engineering, Cancer (Immuno Oncology), IF Imaging, Digital Pathology, Immunology, Pharmacology, Bioluminescence, Surgical Imaging Technologies, Medical Technologies
Tissue engineering, cancer immuno-engineering , drug delivery.
Biology, Immunology, Cancer Biology
Designing, engineering, and testing cancer immunotherapies, biological and bioengineering research
Plasma-assisted catalysis, sustainable chemicals production, renewable energy research
Mathematics (algebra, pre-calc & calc), Advanced Mathematics (differential equations, linear algebra), applications and concepts in Electrical Engineering, Probability and Data Science
Electrical Engineering, Circuit Design, Electricity and Magnetism, Integrated Circuits, Integrated Photonics
Artificial intelligence(ML/NLP/DL), Computer vision & graphics
Engineering, Business, Renewable Energy, Energy, Technology, Startups
Biomedical Engineering
robotics, machine learning/data science, philosophy, photography, organismal/mathematical biology
Aerospace Engineering, Systems Engineering, Engineering Management, Process Engineering
Global Health, Mental Health, Women's and Children's Health, Health Systems, International Relations, Sustainability, Epidemiology, Biostatistics, Algebra, Cell Culture, Tissue Engineering, Cell Biology, Reproductive Rights, Sub-Saharan African Development
Membrane separation/membrane synthesis, online scheduling and optimization, reaction chemistry, heat/mass transport, and thermodynamics.
physics of living systems; quantitative data analysis; computational projects; biological theory; applied mathematics
Beginner-friendly AI projects focused on foundational concepts and practical applications, including dataset exploration and prediction tasks, as well as engineering and robotics projects involving control systems, embedded systems, and hands-on problem-solving.