Shreyank N Gowda
Scholar

Shreyank N Gowda

Google Scholar ID: H95HfgIAAAAJ
Assistant Professor at the University of Nottingham
Computer VisionZero-shot LearningGreen AI
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Citations & Impact
All-time
Citations
919
 
H-index
12
 
i10-index
14
 
Publications
20
 
Co-authors
25
list available
Contact
Emailshreyank.narayanagowda@nottingham.ac.uk
Publications
21 items
Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models
2026
Cited
0
QC-SMOTE: Quality-Controlled SMOTE for Imbalanced Classification
2026
Cited
0
Uncertainty-Aware Longitudinal Forecasting of Alzheimer's Disease Progression Using Deep Learning
2026
Cited
0
Can News Predict the Market? Limits of Zero-Shot Financial NLP and the Role of Explainable AI
2026
Cited
0
Using Explainability as a Training-Time Reliability Signal for Efficient ECG Classification
2026
Cited
0
Prompt Injection Detection is Regime-Dependent: A Deployment-Aware Evaluation with Interpretable Structural Signals
2026
Cited
0
Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
2026
Cited
0
SECOS: Semantic Capture for Rigorous Classification in Open-World Semi-Supervised Learning
2026
Cited
0
Resume
Academic Achievements
  • 2025: 1 paper accepted at NeurIPS 2025
  • 2025: 2 papers accepted at MICCAI-W 2025
  • 2025: 1 paper accepted at ACM Multimedia 2025
  • 2025: 1 paper accepted at ICCV 2025 and 1 at ICCV-W 2025
  • 2025: 1 paper accepted at CVPR-W 2025
  • 2025: 1 paper accepted at ICLR 2025
  • 2024: 3 papers accepted at ACCV 2024
  • 2024: 2 papers accepted at ECCV 2024 and 1 at ECCV-W 2024
  • 2024: 1 paper accepted at MICCAI 2024
Background
  • Assistant Professor at the University of Nottingham
  • Specializes in deployable computer vision research
  • Focuses on data-efficient and memory-efficient learning methodologies
  • Works with diverse datasets including images, videos, and medical data
  • Research is strongly motivated by human visual perception and learning
  • Expertise in zero-shot, few-shot, and semi-supervised learning
  • Passionate about promoting Green AI initiatives
Co-authors
17 total
Laura Sevilla-Lara
Laura Sevilla-Lara
Reader at University of Edinburgh
Marcus Rohrbach
Marcus Rohrbach
Professor for Multimodal Reliable AI, TU Darmstadt, Germany
Xiao-Bo Jin
Xiao-Bo Jin
Xi'an Jiaotong-Liverpool University
Frank Keller
Frank Keller
University of Edinburgh
Chun Yuan
Chun Yuan
Graduate School at Shenzhen, Tsinghua University
David A. Clifton
David A. Clifton
Chair of Clinical Machine Learning, University of Oxford
Xinyue Hao
Xinyue Hao
University of Edinburgh
Anurag Arnab
Anurag Arnab
Google DeepMind