Staff Profile

Dr Varun Ojha is a Senior Lecturer in Artificial Intelligence at the School of Computing at Newcastle University. He is Artificial Intelligence Theme Leader and Co-I on the EPSRC-funded National Edge AI Hub. In the past, Dr Ojha served as Lecturer (Assistant Professor) in Computer Science at the University of Reading, UK. He was a Postdoctoral Fellow at the Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland. Before this, Dr Ojha was a Marie-Curie Fellow (funded by the European Commission) at the Technical University of Ostrava, Czech Republic. He received a PhD in Computer Science from the Technical University of Ostrava, the Czech Republic. In his early career, Dr Ojha received a research fellowship position funded by the Govt of India’s Dept of Science and Technology at the Visva-Bharati University, India.

Trustworthiness Artificial Intelligence. I work on Deep Learning and Machine Learning. My primary research goals are to work on Deep Neural Networks towards the Security, Explainability, and Trustworthiness of AI.

Engineering and Science Applications of AI. I work on Artificial Intelligence Algorithms to solve complex Engineering and Science problems. For example, I have worked with researchers from Engineering, Climate Science, Hydrology, Environmental Science and Architecture, Physics, and Biology, innovating and applying AI to solve problems in these disciplines.

Data Science. I work on Images, Videos, Audio, Speech, and Text data. I have worked on research and industry projects funded by Innovate UK on Electric Vehicles and Natural Language Processing for energy monitoring. Visit my homepage for up-to-date information: ojhavk.github.io

• Articles

  • Duan H, Wang S, Ojha V, Wang S, Huang Y, Long Y, Ranjan R, Zheng Y. Wearable-based Behaviour Interpolation for Semi-supervised Human Activity Recognition. Information Sciences 2024, 665, 120393.
  • Snasel V, Stepnicka M, Ojha V, Suganthan PN, Gao R, Kong L. Large-scale Data Classification based on the Integrated Fusion of Fuzzy Learning and Graph Neural Network. Information Fusion 2024, 102067.
  • Vandaele R, Dance S, Ojha V. Deep Learning for Automated Trash Screen Blockage Detection Using Cameras: Actionable Information for Flood Risk Management. Journal of Hydroinformatics 2024, (ePub ahead of Print).
  • Ayers D, Lau J, Amezcua J, Carrassi A, Ojha V. Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents. Quarterly Journal of the Royal Meteorological Society 2023, 149(753), 1236-1262.
  • Konga L, Ojha V, Gao R, Suganthand PN, Snášel V. Low-rank and global-representation-key-based attention for graph transformer. Information Sciences 2023, 642, 119108.
  • Pravin C, Martino I, Nicosia G, Ojha V. Fragility, Robustness and Antifragility in Deep Learning. Artificial Intelligence 2023. In Press.
  • Vandaele R, Dance S, Ojha V. Calibrated river-level estimation from river cameras using convolutional neural networks. Environmental Data Science 2023, 2, e11.
  • Ojha V, Panto B, Nicosia G. Adaptive search space decomposition method for pre- and post-buckling analyses of space truss structures. Engineering Applications of Artificial Intelligence 2023, 117(Part B), 105593.
  • Amaradio MN, Ojha V, Jansen G, Gulisano M, Costanza J, Nicosia G. Pareto optimal metabolic engineering for the growth-coupled overproduction of sustainable chemicals. Biotechnology and Bioengineering 2022, 119(7), 1890-1902.
  • Ojha V, Jansen G, Patane A, La Magna A, Romano V, Nicosia G. Design and characterization of effective solar cells. Energy Systems 2022, 13(2), 355-382.
  • Ojha V, Nicosia G. Backpropagation neural tree. Neural Networks 2022, 149, 66-83.
  • Ojha V, Timmis J, Nicosia G. Assessing ranking and effectiveness of evolutionary algorithm hyperparameters using global sensitivity analysis methodologies. Swarm and Evolutionary Computation 2022, 74, 101130.
  • Vandaele R, Dance SL, Ojha V. Deep learning for automated river-level monitoring through river-camera images: An approach based on water segmentation and transfer learning. Hydrology and Earth System Sciences 2021, 25(8), 4435-4453.
  • Ojha VK, Griego D, Kuliga S, Bielik M, Bus P, Schaeben C, Treyer L, Standfest M, Schneider S, Konig R, Donath D, Schmitt G. Machine learning approaches to understand the influence of urban environments on human physiological response. Information Sciences 2019, 474, 154–169.
  • Ojha V, Abraham A, Snasel V. Heuristic design of fuzzy inference systems: A review of three decades of research. Engineering Applications in Artificial Intelligence 2019, 85, 845–864.
  • Bielik M, Kuliga S, Schneider S, Griego D, Ojha VK, Konig R, Donath D, Schmitt G. Examining trade-offs between social, psychological and energy potential of urban form. International Journal of Geo-Information 2019, 8, 1–52.
  • Ojha VK, Schiano S, Wu C, Abraham A, Snasel V. Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree. Neural Computing Application 2018, 29 (7), 467–481.
  • Ojha VK, Snasel V, Abraham A. Multiobjective programming for type-2 hierarchical fuzzy trees. IEEE Transaction on Fuzzy Systems 2018, 26(2), 915–936.
  • Ojha VK, Snasel V, Abraham A. Metaheuristic design of feedforward neural networks: a review of two decades of research. Engineering Applications in Artificial Intelligence 2017, 60, 97-116.
  • Ojha VK, Abraham A, Snasel V. Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming. Applied Soft Computing 2017, 52, 909-924.
  • Ojha VK, Dutta P, Chaudhuri A. Identifying the hazardousness of sewer-pipeline gas-mixture using classification methods. Neural Computing Application 2016, 28, 1343–1354.
  • Ojha VK, Jackowski K, Abraham A, Snasel V. Dimensionality reduction and function approximation of poly(lactic-co-glycolic acid) micro-and nano-particle dissolution rate. International Journal of Nanomedicine 2015, 10, 1119–1129.

• Conference Proceedings (inc. Abstracts)

  • Kong L, Kumar A, Snasel V, Das S, Kromer P, Ojha V. CSS–A Cheap-Surrogate-Based Selection Operator for Multi-objective Optimization. In: 10th International Conference on Bioinspired Optimization Methods and Their Applications (BIOMA 2022). 2022, Maribor, Slovenia: Springer.
  • Taylor R, Ojha V, Martino I, Nicosia G. Sensitivity Analysis for Deep Learning: Ranking Hyper-parameter Influence. In: 33rd International Conference on Tools with Artificial Intelligence (ICTAI 2021). 2021, Washington DC, USA: IEEE.
  • Vandaele R, Dance SL, Ojha V. Automated Water Segmentation and River Level Detection on Camera Images Using Transfer Learning. In: 42nd DAGM German Conference on Pattern Recognition (DAGM GCPR 2020). 2021, Tübingen, Germany: Springer.
  • Pravin C, Martino I, Nicosia G, Ojha V. Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons. In: Artificial Neural Networks and Machine Learning: 30th International Conference on Artificial Neural Networks (ICANN 2021). 2021, Bratislava, Slovakia: Springer.
  • Shergill JS, Pravin C, Ojha V. Accent and Gender Recognition from English Language Speech and Audio Using Signal Processing and Deep Learning. In: 20th International Conference on Hybrid Intelligent Systems (HIS 2020). 2021, Virtual event: Springer.

• Edited Books

  • Nicosia G, Ojha V, Malfa EL, Malfa GL, Jansen G, Pardalos P, Giuffrida G, Umeton R, ed. Machine Learning, Optimization, and Data Science: Part II. Cham: Springer, 2022.
  • Nicosia G, Ojha V, Malfa EL, Malfa GL, Jansen G, Pardalos P, Giuffrida G, Umeton R, ed. Machine Learning, Optimization, and Data Science: Part I. Cham: Springer, 2022.