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smart-scheduling

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Python optimization framework for municipal water utility demand response. Models a three-facility system (GWTP, WWTP, lift station) as a triple-battery against ERCOT day-ahead prices using MILP (Pyomo/GLPK) and NMPC (do-mpc/CasADi/Ipopt). ENG 573 Capstone, UIUC MEng Energy Systems, Spring 2026.

  • Updated May 1, 2026
  • Python

An AI-driven 🤖 task management ecosystem featuring natural language processing 🧠 and real-time collaboration 🔄. Built by a team of SDIA Master’s students 🎓, this project integrates distributed task logic, smart categorization, and productivity analytics to optimize workflow. Designed for scalable 📈 and high-performance ⚡ task synchronization.

  • Updated Feb 18, 2026
  • Java

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