diff --git a/resumes/resume_en.tex b/resumes/resume_en.tex
index b2c3e96..aab21b0 100644
--- a/resumes/resume_en.tex
+++ b/resumes/resume_en.tex
@@ -211,23 +211,23 @@
 \resumeItem{Created a bespoke OpenAI Gym environment incorporating FFT-based audio processing and trained a PPO agent to perform adaptive noise cancellation in real time, achieving processing speeds exceeding 5,200 FPS for high-fidelity audio performance}
 \resumeItemListEnd
 \resumeSubHeadingListEnd
- 	\vspace{-7pt}
-	
+\vspace{-7pt}
+
 \section{\color{blue}PUBLICATIONS}
-	\resumeSubHeadingListStart
-	
-        \resumeProjectHeading
-        {\textbf{Network-Aware Adaptive Semantic Image Transmission in Edge-Cloud Communications}}{MECOM 2025}
-            \resumeItemListStart
-                \resumeItem{Proposed an adaptive JSCC framework that couples Swin-Transformers with real-time network telemetry to optimize image transmission over dynamic 5G/6G core networks (Published, IEEE Xplore)}
-            \resumeItemListEnd
-        
-        \resumeProjectHeading
-        {\textbf{Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic Transcoding}}{CCECE 2024}
-            \resumeItemListStart
-                \resumeItem{Utilized transformer-based edge-to-cloud models to achieve a $30\times$ bandwidth reduction and $30\%$ improvement in end-to-end latency for high-speed data systems (Published, IEEE Xplore)}
-            \resumeItemListEnd
-	\resumeSubHeadingListEnd
+\resumeSubHeadingListStart
+
+\resumeProjectHeading
+{\textbf{Network-Aware Adaptive Semantic Image Transmission in Edge-Cloud Communications}}{MECOM 2025}
+\resumeItemListStart
+\resumeItem{Proposed an adaptive JSCC framework that couples Swin-Transformers with real-time network telemetry to optimize image transmission over dynamic 5G/6G core networks (Published, IEEE Xplore)}
+\resumeItemListEnd
+
+\resumeProjectHeading
+{\textbf{Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic Transcoding}}{CCECE 2024}
+\resumeItemListStart
+\resumeItem{Utilized transformer-based edge-to-cloud models to achieve a $30\times$ bandwidth reduction and $30\%$ improvement in end-to-end latency for high-speed data systems (Published, IEEE Xplore)}
+\resumeItemListEnd
+\resumeSubHeadingListEnd
 
 
 \end{document}