Sai Navaneet

M.S. in Electronics & Electrical Engineering

I have graduated from Kyungpook National University with a Masterโ€™s degree in Electronics and Electrical Engineering, with a strong focus on automation and robotics. My background is rooted in electronic systems, control, and embedded technologies, developed through hands-on research and real-world robotic deployments.

My work centers on robotic manipulation and autonomous systems, where I develop robotics software and learning-based models that bridge perception, decision-making, and control. I enjoy transforming complex ideas into reliable, deployable robotic solutions that advance intelligent automation.

Sai Navaneet

Latest News & Updates

2025
Nov 2025
๐ŸŽ‰
MambaVLA paper accepted at CCNC 2026
MambaVLA: A Scalable and Efficient Vision-Language-Action Model with State Space Architecture
Oct 2025
๐Ÿ“Š
Submited a paper to Neural Networks Journal
DiffDAIL: Diffusion-Enhanced Vision-Guided Imitation Learning with Discrete Latent Representations
Oct 2025
๐Ÿ“Š
Presented a poster at IROS 2025
LegMamba: A Scalable and Efficient State Space model for Quadrapedal Locomotion
July 2025
๐Ÿ“š
Submited a paper to CCNC / CES 2026
June 2025
๐Ÿ†
Won Lerobot (Hugging Face) Hackathon in Daegu
July 2025
๐Ÿง 
Developing VLA Models using State Space Models like MAMBA
May 2025
๐Ÿ“Š
Submitted a paper to NeurIPS
QROOT: An Integrated Diffusion Transformer and Reinforcement Learning Approach for Quadrupedal Locomotion
April 2025
๐Ÿ“š
Submitted a paper to Engineering Applications of Artificial Intelligence journal (Rejected)
Vision-Guided Predictive Action Imitation Learning with Discrete Latent Encoding for Multitasking Robots
March 2025
๐ŸŽฏ
Published a paper in NODYCON(2025)
DLDMP: Discrete Latent Diffusion Motion Planning for manipulators
2024
December 2024
๐Ÿ”ฌ
Developed Automated Tissue Processing using Transformers (Dexweaver Company)
October 2024
๐ŸŒพ
Developed Autonomous Harvesting Using Object Detection (YOLOv11) (Dexweaver Company)
August 2024
๐Ÿ“–
Published a paper in KNU-EERC2024 based on Leader Follower Robot Tracking Using Model Predictive Control