Artificial Intelligence (AI) Laboratory

LEADERSHIP

Artificial Intelligence (AI) Laboratory

The AI Lab is a center for advanced research and innovation in Artificial Intelligence, focusing on the development of next-generation intelligent systems. The lab works on cutting-edge areas such as:

  •  Large Language Models (LLMs),
  • Diffusion language models, 
  • Hierarchical speculative decoding
  • AI-assisted 3D reconstruction,
  • Temporal memory architectures, and
  • Continuous sign language recognition.

Research in the AI Lab bridges theory and real-world application — from optimizing LLM serving efficiency to developing AI-driven healthcare, vision, and multimodal systems. With collaborations involving faculties from institutions such as University of Nebraska at Omaha, Imperial College London, University of the Littoral Opal Coast, and Microsoft, the lab provides a globally connected research environment.

The AI Lab is committed to building scalable, efficient, and socially impactful AI systems that address both global technological challenges and local societal needs.

LEADERSHIP

Laboratory In-charge

Dr. Suresh Manandhar

Dr. Suresh Manandhar

Honorary Chair, Visiting Professor

RESEARCH PIPELINE

Ongoing Research in GATC Laboratory

Multimodal Audio LLMs: State-of-the-art audio-driven language models integrating speech recognition and synthesis with contextual AI.

Researchers: Bishwojyuoti Chaudhary

Multimodal Audio LLMs: State-of-the-art audio-driven language models integrating speech recognition and synthesis with contextual AI.

Researchers: Bishwojyuoti Chaudhary

Structure-Based Virtual Screening and Activity Prediction of Millions of Molecules Using Machine Learning

Researchers: Image Acharya

Nepali Large Language Model: Customized NLP model fine-tuned on Nepali datasets for localized AI applications and digital inclusion.

Researchers: Rupesh Aryal

Healthcare Multimodal LLMs: Integrating clinical text, imaging, and speech data with deep learning for precision diagnostics and patient care.

Researchers: Suman Karki

Efficient LLM Serving through Hierarchical Speculative Decoding with Adaptive Routing

Researchers: Rishab Aryal

AI-Assisted Retopology for High-Fidelity 3D Face Reconstruction.

Researchers: Rupesh Maharjan

Diffusion Language Models (DLM)

Researchers: Ashok Pahadi

Importance-Driven Temporal Memory Architectures for Large Language Models: Prioritizing Important Past Events Over Recent Noise

Researchers: Bhim Prasad Rajbansi

Multi-Source Learning for Robust Brain Tumor Segmentation Across Heterogeneous MRI Datasets

Researchers: Usha Poudel Lamgade

Nepali Large Language Model: Enhancing Drug-Induced Liver Injury Prediction: Using Multi-Modal Graph Neural Networks with Explainable AI

Researchers: Manish Tiwari

Deep Learning Framework for Flood Prediction and Flood-Induced Food Security Risk Assessment in Koshi Province, Nepal

Researchers: Nikesh Aryal

Data Efficient Learning for Embodied Intelligence: Models, Analysis and Methods.

Researchers: Siman Giri

Physics-Aware Artificial Intelligence for Flood Prediction in the Bagmati River Basin, Nepal.

Researchers: Ashim Babu Shrestha