Dr. Shreyank Narayana Gowda (Assistant Professor)

Research Interests: Data-efficient learning, Memory-efficient learning, Sustainable AI, Interpretable AI.

Dr. Shreyank Narayana Gowda is an Assistant Professor at the University of Nottingham where he works on deployable AI which broadly includes ethical, fair, efficient and sustainable AI. Previously, he was a postdoctoral researcher in AI for Healthcare at the University of Oxford, under Dr David Clifton at the Computational Health Informatics Lab. He completed his PhD at the University of Edinburgh where he was supervised by Dr Laura Sevilla-Lara and co-supervised by Dr Frank Keller. Shreyank was fortunate to be partially supported through Facebook AI where he collaborated with Dr Marcus Rohrbach. He broadly works on video-based computer vision applications. 

Dr. Valerio Giuffrida (Assistant Professor) 

Research Interests: Plant phenotyping, medical image analysis.

Dr. Valerio Giuffrida is an Assistant Professor in Computer Vision at the University of Nottingham. His research expertise is centered on applying computer vision, machine learning, and deep learning techniques to a variety of fields, with a focus on plant phenotyping. Dr. Giuffrida was also a Co-Investigator in the PhenomUK Scoping project, co-leading the Data Strand, scoping the data and analysis needs of the UK plant community and proposing proof-of-concept solutions for FAIR data and AI-driven analysis. Beyond his work in plant phenotyping, Dr. Giuffrida has worked in other AI-related areas, including medical image analysis. He actively contributes to the academic community by serving as a panel member for grant applications, including BBSRC, guest editor for journals such as Frontiers in Plant Science, and a reviewer for leading conferences and journals including BMVC, CVPR, NeurIPS, and ICCV.

Dr. Joy Egede (Assistant Professor)

Research Interests: Computer vision, biomedical signal processing, affective computing, multimodal AI.

Joy Egede is a Transitional Assistant Professor in the School of Computer Science at the  University of Nottingham. Her research interests span computer vision, machine learning, biomedical signal processing, and affective computing, particularly in healthcare applications. A core aspect of her research focuses on the development of multimodal artificial intelligence (AI) technologies that support the early diagnosis and treatment of medical conditions that change a person's behavioural and biomedical responses. Some of her work in this area includes automated mental health assessment using virtual human technologies, automated pain estimation in newborn babies, and automated detection of variations in the newborn life support (NSL) procedure. More broadly, she is involved in projects involving activity/ object recognition and tracking, automated synthesis of human behaviour and ethical affective computing.

 Projects - Virtual Human Technologies for Multimodal Mental Health Assessment

Dr. Michael Pound (Associate Professor) 

Research Interests: Plant Phenotyping, computer vision for engineering and physics, medical imaging.

Dr. Michael Pound is an Associate Professor of Computer Science at the University of Nottingham, UK. His research focuses on the development and application of computer vision approaches, often to biological images. He has been involved in interdisciplinary research across a variety of domains for over a decade, ranging from plant and medical imaging, through to engineering and physics. His current research projects are focusing on image segmentation and understanding, as well as 3D reconstruction. He is an active member of the plant phenotyping community, with many high-impact publications on the use of AI in plant science, as well as chairing the international workshop on Computer Vision Problems in Plant Phenotyping, which this year will run for the 10th time.

 Projects - Contrastive Learning of Plant Traits for Ecosystem Services, InLightenus: Seeing Deeper: AI-Enhanced Adaptive Optics for High-Resolution Biomedical Imaging, The 4D Plant, Data CAMMP, The Microphenotron, Capture, Lemur

Prof. Andrew French (Professor of Computer Science) 

Research Interests: Biological image analysis, plant phenotyping, synthetic data, medical image analysis.

Prof. Andrew French is the lead academic of the computer vision lab.  His expertise is in interdisciplinary computer vision, in particular working closely with the biosciences to develop new approaches to understanding biological images. Prof. French leads the national “AI in the Biosciences” community-building project. His contribution to the academic community includes serving on UKRI panels and working groups, and editorial work for journals.  He helped start several workshops and summer schools for computer vision in the biosciences, and has developed online training courses for AI and data science training for a biological audience. 

Projects - AI in the Biosciences, The 4D Plant, Data CAMMP, The Microphenotron,  Capture

Dr. Yancong Lin (Assistant Professor) 

Research Interests: Efficiency in AI, computer vision, robotics.

Data fuels AI, but collecting and annotating it is costly. My research focuses on creating data and compute-efficient AI models for robotic perception by pre-wiring deep learning with inductive knowledge priors, allowing perception systems to learn more from less. My work delivers leading performance while significantly reducing data demand, particularly in image geometries and autonomous vehicles.

Previously, I was a postdoc at TU Delft, working on cognitive robotics (advised by Dr. Holger Caesar) and a visiting researcher at ETH Zurich, working on photogrammetry (advised by Prof. Konrad Schindler). I earned my PhD from the Vision Lab TU Delft (supervised by Dr. Jan van Gemert and Dr. Silvia-Laura Pintea). 

My research has been supported by NWO (the Dutch Research Council) and featured in top-tier computer vision venues, including CVPR/ICCV/ECCV.  I have also collaborated closely with industry partners to advance AI-driven visual inspection technologies.

For the latest updates, please refer to my homepage: https://yanconglin.github.io/

Projects - Scene Flow, Image Geometries