About Dr Sneha Verma
I'm a lecturer in the School of Computer Science and Engineering at the University of Sunderland. My research focuses on artificial intelligence, multimodal machine learning, and data-driven systems, with applications in areas such as healthcare analytics, digital twins, and intelligent infrastructure. I've extensive experience in developing AI models for complex real-world problems, including computer vision, sensor data analytics, and predictive systems.
Prior to joining the University of Sunderland, I was a Lecturer in Computer and Data Science at York St John University. I've also held research positions at Newcastle University and Teesside University, contributing to interdisciplinary projects in artificial intelligence, robotics, and digital health.
My work spans both fundamental and applied AI research, particularly in multimodal data integration, trustworthy machine learning, and intelligent systems for societal impact. I've authored several peer-reviewed publications and has been involved in collaborative research projects with academic and industry partners. Alongside my research, I'm actively engaged in teaching and mentoring undergraduate and postgraduate students in artificial intelligence, machine learning, and data science.
Teaching and supervision
- ENG2001-Industrial Automation and Control
- ENGM128 - Smart Factories
- ENX313 - Project Supervisor
Research
- Artificial Intelligence and Machine Learning: Development of intelligent models for complex real-world applications using deep learning, multimodal learning, and data-driven techniques.
- Multimodal Data Analysis: Integration and analysis of heterogeneous data sources such as images, sensor data, and structured datasets for improved predictive modelling and decision-making.
- Computer Vision: Research on image and video analytics, including object detection, activity recognition, and scene understanding for real-world environments.
- Healthcare AI: Application of machine learning and multimodal AI techniques for medical data analysis, particularly in areas such as cancer diagnosis and medical image interpretation.
- Digital Twins and Smart Infrastructure: Development of AI-driven digital twin systems for monitoring, simulation, and optimization in complex environments such as construction and urban infrastructure.
- Human–AI Collaboration: Designing AI systems that support human decision-making and enhance productivity in real-world operational settings.
- Sensor Data Analytics: Processing and analysing IoT and sensor-based datasets to detect patterns, monitor systems, and support predictive maintenance.
- Responsible and Trustworthy AI: Exploring methods to improve transparency, reliability, and ethical deployment of AI systems in societal applications.
Areas of expertise
- Artificial Intelligence and Machine Learning
- Deep Learning and Multimodal Data Fusion
- Computer Vision and Image Analysis
- Medical Image Analysis and Healthcare AI
- Digital Twins and Intelligent Infrastructure
- Sensor Data Analytics and IoT Systems
- Activity Recognition and Human–Machine Interaction
- Data-Driven Decision Support Systems
- Responsible and Trustworthy AI
Further information
Research Grants
- Principal Investigator / Research Lead, Multimodal AI for Early Diagnosis of Breast and Prostate Cancer using Histopathological and Infrared Spectral Data with Explainability Analysis – Funded by the British Council under the UK–Saudi research collaboration programme. The project is conducted in collaboration with researchers from University of Manchester and partner institutions in Saudi Arabia.
Duration: 2026–2028.
Focus: Development of explainable multimodal artificial intelligence models integrating histopathological imaging and infrared spectral data to enable earlier and more reliable diagnosis of breast and prostate cancers.
Awards and Achievements
- Nominee, AI & Robotics Research Awards – Recognising innovation in trustworthy autonomous systems, London, UK (2024)
- Nominee, European Scientific Prize for outstanding contributions to AI and Robotics, Italy (2023)
- Associate Fellow of the Higher Education Academy (AFHEA) – Awarded under the UK Professional Standards Framework, London, UK (2022)
- Travel Grant Award, Worshipful Company of Tin Plate Workers – Recognising excellence in research, London, UK (2023)
- WCSIM Postgraduate Research Award – For outstanding research contribution, City of London, UK (2021)
- City University Scholarship – Awarded for MPhil and Doctoral studies, London, UK (2019–2023)
- CSIR Senior Research Fellowship, Council of Scientific and Industrial Research (CSIR), India (2018–2019)
- International Conference Travel Grant, India (2018)
- National-Level Scholarship for Bachelor’s Degree, Higher Education Commission (HEC), India (2011–2015)
- University Research Funding for Master’s Project, Central Glass and Ceramic Research Institute (CGCRI), India (2016–2017)
Professional Memberships
- Member, MLCommons – International machine learning community focused on benchmarking, standards, and collaborative AI research (since 2023)
- Member, International Group of Artificial Intelligence – Global professional network promoting research and collaboration in artificial intelligence (since 2023)
- Member, Worshipful Company of Scientific Instrument Makers – Professional livery company supporting innovation and excellence in science and engineering instrumentation (since 2021)
- Member, City AI Society – AI research and professional community at City, University of London (since 2023)
- Member, Newcastle AI Society – Artificial intelligence research and networking community at Newcastle University (since 2022)