Thanusri Aenugula is currently pursuing a Master’s degree in Data Science. She earned her Bachelor of Engineering in Electrical and Electronics Engineering. Her research interests include artificial intelligence, machine learning, and computer vision, and she is enthusiastic about learning and contributing to ongoing research projects at the AVLL Lab. Outside of her professional interests, she enjoys singing and traveling.
Personal website: https://thanusri1601.github.io/portfolio/
Nazar Oladepo
Nazar Oladepo is a Masters student in Computer Science at Texas A&M University. His research is currently focused on Artificial Intelligence and Human-Computer Interaction, exploring ways to develop interfaces that allow people to seamlessly interact with highly complicated systems. He will be assisting on the automated plant phenotyping project by developing the system GUI. Nazar has a background in software and website development and is passionate about functional and appealing design. Nazar’s hobbies include drawing, reading, and travel.
Aditya Rajiv
Aditya Rajiv is a data science professional with a strong enthusiasm for full-stack AI engineering. He has a keen interest in problem-solving and in developing multimodal AI systems using cutting-edge technologies to create meaningful impact. He specializes in bridging the gap between data research and production-grade engineering. His approach goes beyond training models, focusing on building complete AI ecosystems that span data orchestration, model architecture, deployment, and monitoring.
Dhanush Shekar
Dhanush Dhana Shekar is a Master’s student in Data Science (Electrical and Computer Engineering track) at Texas A&M University. His primary interests are in machine learning and deep learning, with a particular focus on convolutional neural networks. He often approaches problems from a computer vision perspective, modeling them as visual tasks whenever possible. He is especially interested in using artificial intelligence to bridge interdisciplinary gaps by applying machine learning techniques to real-world challenges beyond traditional technology domains, including healthcare and other data-driven scientific and engineering applications. Outside of academics, he enjoys playing table tennis and closely follows Formula 1 and soccer.