Summary
Chris Kalahiki is a Computer Scientist and PhD candidate at Clemson University with a decade of experience applying machine learning and software engineering to real-world problems. His research and development work spans computer vision, transfer learning, and AI safety—fusing TensorFlow/Keras expertise with systems-level skills in profiling CPU/GPU usage and automated load balancing for multiscale simulations. He has taught applied data science and software foundations, and brings practical full‑stack and cloud experience from industry roles involving AWS, Kubernetes, and SQL/.NET ecosystems. Chris is motivated by trustworthy, interpretable AI and pursues solutions that bridge theoretical insight with production-ready pipelines, often approaching problems from both algorithmic and systems perspectives.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Clemson University
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Louisiana Tech University