Current Position

I’m an AI researcher and full-stack software developer with a strong foundation in machine learning, generative AI, scientific computing, and signal processing. Currently, I serve as a Research Scientist at Texas A&M AgriLife Research, where I lead interdisciplinary projects at the intersection of AI, remote sensing, and life sciences.

I have a proven track record of developing end-to-end machine learning pipelines—from data preprocessing and model design to distributed GPU training and deployment in both production and research environments. My expertise spans tools and frameworks such as TensorFlow, PyTorch, Kubeflow, Ray, OpenCV, Open3D, Docker, and Kubernetes.

My recent research focuses on leveraging the emerging capabilities of large language models (LLMs)—including reasoning, planning, and multi-agent collaboration—to streamline analytical workflows for multimodal remote sensing data. This includes integrating and processing ground-based field observations, UAV imagery, satellite data, LiDAR, and Ground Penetrating Radar (GPR) to support applications in scientific research automation and agricultural digital phenotyping. As part of this work, I’ve gained hands-on experience fine-tuning and aligning LLMs using advanced prompting techniques such as Chain-of-Thought (CoT) and ReAct, along with Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA and Direct Preference Optimization (DPO). I’ve also implemented multimodal RAG systems and designed multi-agent workflows for complex reasoning tasks using tools such as ADK, CrewAI, Hugging Face, LangChain, AutoGen, LangGraph, and other generative AI frameworks.

My background in computer vision has also enabled me to contribute to multidisciplinary research efforts, developing tools for feature extraction, object detection, and image segmentation using CNNs, Vision Transformers (ViT), transfer learning, and semantic segmentation. I have applied these methods across multidimensional image datasets, from microscopy to hyperspectral imagery, enabling high-throughput, automated disease detection and lab optimization.

Community Role

Beyond my research, I am an open-source advocate deeply committed to community engagement and knowledge sharing. Leveraging on Google's recognition as a "Google Developer Expert" in Machine Learning and a "Google Cloud Champion," I do my best to actively contribute to the community by creating and publishing content around Machine Learning, TensorFlow, and related Google Cloud Platform(GCP) services, such as Vertex AI, speaking at developer conferences and meetups, and mentoring students and startups seeking guidance in the space of Machine Learning.

Background and academia

My academic journey is rooted in computer science and data science, culminating in a Ph.D. in Engineering focused on ML and a graduate certificate in Remote Sensing from Texas A&M University. Additionally, along with my academic accomplishments, I have over ten years of experience working in the industry as a data science and full-stack software developer and teaching experience. This background and my experience working with interdisciplinary teams of scientists and experts from different fields have given me unique skills and the ability to work on breaking complex problems into manageable pieces and uncovering efficient solutions within tight timelines.

Technical skills

I am passionate about programming and enjoy leveraging my skills to bring innovative ideas to life. As a certified member of the TensorFlow and Intel Edge AI networks, I am a full-stack developer proficient in Python, JavaScript, .Net, MATLAB, and C++. My expertise extends to mobile application development for Android and creating robust cloud solutions on GCP. As a data scientist, I have dedicated extensive hours to analyzing multidimensional data using a wide range of Machine Learning and Deep Learning libraries, including TensorFlow, PyTorch, Scikit-Learn, Scipy, Dask, Pandas, OpenVINO, and OpenCV.

I am open to collaborating and engaging in discussions about creating tools that could positively impact people's lives. Please feel free to reach out.