#  Optimization of Reduced-Order Turbulent Transport Models for High-Fidelity Agreement in Fusion Tokamak Simulations 

 



    ![flyer](/sites/g/files/omnuum986/files/styles/hwp_5_4__480x385/public/2026-02/Made%20in%20UPM%202026%20Pablo%20Lara.png?itok=S9eNrRnT) 

 



 

####  calendar\_today Date and Time 

 **March 17, 2026** 

 06:00PM EDT 

####  pin\_drop Location 

 **RCCHU Conference Room**  

 [26 Trowbridge St.  
Cambridge, MA 02139  
United States



 ](<https://www.google.com/maps?q=US MA Cambridge 02139 26 Trowbridge St.>) 



 

 [ Zoom Link arrow\_circle\_right ](https://zoom.us/j/94704478785?pwd=qWG3yiNx6hpYJANansSWZ8SzeRekKM.1) 

 



 

**Pablo de Lara** is a final-year Energy Engineering student at ETSIME, UPM, currently conducting research at the Plasma Science and Fusion Center (PSFC) at MIT. His academic path includes research in wave optics at UPM’s Department of Energy and Fuels and professional experience at Sener, where he worked as an electrical engineer developing practical AI-driven automation tools.

At MIT, Pablo focuses on one of the most computationally demanding challenges in nuclear fusion: turbulent transport modeling in tokamaks. High-fidelity gyrokinetic simulations require millions of CPU hours, limiting their routine application. His research aims to bridge the gap between high-fidelity simulations and computationally efficient reduced-order models.

Within the PORTALS framework, Pablo performs systematic parameter-space scans of the Trapped Gyro-Landau Fluid (TGLF) model across different plasma regimes and reactor configurations to achieve predictive agreement with high-fidelity CGYRO simulations. His work contributes to accelerating fusion research by improving accuracy while dramatically reducing computational cost.

   ![flyer](/sites/g/files/omnuum986/files/styles/hwp_1_1__720x720_scale/public/2026-02/Made%20in%20UPM%202026%20Pablo%20Lara.png?itok=lsW43oo-) 

 



 

 



 

 

 Share on:- [     Facebook ](#)
- [     Twitter ](#)
- [     Linkedin ](#)
 


 Save: [ Add to calendar calendar\_today ](https://rcc.harvard.edu/node/1577786/event-feed.ics)  Copy link link