Hi, my name is
I'm a chemical engineering student passionate about process automation and optimization. I specialize in integrating process control, dynamic modeling and machine learning to design efficient industrial systems. By combining knowledge of materials and energy balances with data‑driven algorithms, I strive to drive continuous improvement while collaborating closely with cross‑functional teams and clients.
Hello! I'm William, a graduating Chemical Engineering major from UC San Diego. I specialize in building automation and optimization systems that leverage process control, dynamics, and data science. My cross‑disciplinary foundation spans materials and energy balances, process dynamics, and machine learning—tools I use to design intelligent, efficient processes. I'm committed to continuous improvement and value clear communication with both teams and clients.
Through hands‑on projects such as ammonia synthesis and direct air capture plant designs, I've honed skills in simulation, equipment sizing and economic analysis. My work focuses on optimizing process integration through advanced heat exchange networks, control strategies and predictive modeling. These experiences have strengthened my ability to translate complex data into actionable engineering solutions.
My technical expertise spans:
Sep 2023 - Jun 2025
Apr 2021 - Aug 2023
July – August 2024
With the Chandra Asri team on the UCC1 polyethylene line—summer 2024.
Senior capstone project designing a scalable DAC system capable of removing 1 million metric tons of CO₂ annually from the atmosphere. Complete process engineering with economic analysis achieving $39,770 capital savings through optimization.
Comprehensive four-quarter capstone project designing a complete ammonia synthesis plant using the Haber-Bosch process. Achieved 943.2 kmol/h NH₃ production with 48.9% efficiency improvement through advanced heat integration.
Analyzed thermal performance of 7-plate stainless steel heat exchanger by determining empirical Nusselt correlation coefficients. Developed predictive models with R² > 0.98 correlation for design optimization.
Investigated effects of operating pressure on water and salt transport in RO configurations. Achieved 68% water recovery with comprehensive selectivity analysis for desalination optimization.
Optimized liposome nanoparticle fabrication using extrusion method. Achieved minimum particle size of 109.8 nm with 51% reduction and polydispersity index of 0.082 for pharmaceutical applications.
Investigated photocatalytic degradation of methylene blue using TiO₂ catalyst and UV light. Applied pseudo-first-order kinetics with maximum rate constant of 0.0797 s⁻¹ achieved through H₂O₂ optimization.
05. What's Next?
I'm currently seeking opportunities in process automation, optimization and control engineering. If you're looking for a problem solver who blends chemical engineering principles with modern data analytics and machine learning, I'd love to connect. Feel free to reach out to discuss how I can contribute to your projects or team.
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