Dr Mamatha Thota

Dr. Mamatha Thota is a Senior Lecturer in Computer Science with a research focus on Machine Learning and Deep Learning. Their expertise spans both theoretical and applied AI, including domain adaptation, lifelong learning, self-supervised learning, foundation models, multi-modal learning, and medical imaging. Their research is particularly focused on improving representation learning in deep neural networks by developing novel self-supervised learning approaches and architectural innovations. Additionally, they explore how these techniques can be applied to real-world domains such as food packaging and agri-food systems, including yield forecasting, environment-aware agricultural systems, and vertical farming.

An active contributor to the research community, Dr. Mamatha Thota serves as a reviewer for top-tier conferences, including NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, ACCV, BMVC, and TMLR and has received the Outstanding Reviewer Award at BMVC. They have also taken on leadership roles as the Chair for the ECCV 2023 and ICCV 2024 workshop review process and as the Principal Organizer and Chair for the WiML ICCV-2023 and ECCV-2024 workshops.

Dr. Mamatha Thota has also shared their insights as a TEDx speaker and holds an ILM Level 5 qualification, demonstrating their commitment to leadership and professional development.

Machine Learning/Deep Learning; Domain Adaptation; Lifelong Learning; Self-Supervised Learning; Foundation Models; Multi-Modal Learning; AI for Food Packaging; Yield Forecasting & Optimization; Vertical Farming.