I am an AI researcher with 5+ years of experience specializing in natural language processing, large language models (LLMs), multi-agent/multi-robot systems, and autonomous and intelligent systems optimizations.

I conduct high-impact AI research in decision-making, AI orchestration, and trustworthy AI, with a focus on safe, robust, and sustainable AI applications. My expertise includes training and optimizing transformer-based models (BERT, GPT, LLaMA, etc.), efficient inference deployment, and integrating LLMs into multi-agent coordination and sequential decision-making.

I have expertise in designing experiments, implementing novel algorithms, and developing evaluation frameworks for multi-agent reinforcement learning, evolutionary AI, and open-ended AI research. I'm proficient in ROS/ROS2, CUDA, PyTorch/Tensorflow, AWS, Python, C++, Matlab, and Linux, with experience in real-world AI deployments, simulation environments, and large-scale distributed training.

I'm passionate about AI for Good, actively contributing to research that enhances AI safety, robustness, and long-term sustainability while bridging fundamental research with real-world applications.