Kevin Dai

A third-year Chemical Engineering student at the University of Toronto, I am passionate about advancing battery technologies, sustainable energy systems, and AI-driven materials design. My academic journey and hands-on research experiences have equipped me with a strong foundation in electrochemistry, data analytics, and engineering project leadership. Technical Skills: • Proficient in Python, MATLAB, and machine learning libraries (PyTorch, scikit-learn, XGBoost). • Experienced with electrochemical testing methods (CV, GCD, EIS) and material characterization (SEM, EDS, XRD). • Skilled in technical writing, data visualization, and cross-functional collaboration. Professional Highlights: • Researcher, ATOMS Lab: Built ML models predicting lithium-ion battery degradation with R² > 0.9, analyzing 10,000+ electrolyte–anode datapoints. • Researcher, Green Technology Lab: Fabricated and tested N/S-doped supercapacitor electrodes achieving >90% capacitance retention after 1,000 cycles. • Power Division Lead, UofT Chemical Vehicles Team: Directed battery prototyping for Zn-Air, Al-Ag₂O, and Zn-Ag₂O chemistries; authored 5+ SOPs and managed a team of 12+. • Contract Machine Learning Engineer, Outlier: Evaluated model accuracy, designed supervised and unsupervised models, and designed problem sets to train advanced AI models. What Sets Me Apart: I combine deep technical expertise in batteries and energy systems with practical leadership experience in engineering design competitions and research labs. My ability to bridge experimental electrochemistry, AI/ML modeling, and systems-level planning allows me to tackle energy challenges from both scientific and engineering perspectives. I am driven to contribute to the transition toward sustainable, high-performance energy storage solutions. I’d love to connect on LinkedIn. You can also reach me at kevindai2025@gmail.com.