About me
Hi! I’m Prayag, working as an Associate Professor in Machine Learning at Halmstad University, Sweden.
Research Interest
- Quantum Machine Learning, Deep Learning, Graph Neural Networks, Federated Learning, Reinforcement Learning, Unsupervised Feature Selection
- Natural Language Processing, Large Language Models, Computer Vision, Multimodal and Multisource Fusion
- Applications in Healthcare, Bioinformatics, and Intelligent Systems
- Explainable, Interpretable, and Causal Models
- Internet of Things
News
- [Oct 2024] 1 paper accepted by TMLR
- [Sept 2024] 1 paper accepted by Nature Biomedical Innovations.
- [Sept 2024] Hiring PhD Candidate in Multimodal Large Language Models (LLM) for Healthcare at Halmstad University, Sweden.
- [Sept 2024] Promoted to Associate Professor (Docent) at Halmstad University, Sweden
- [Jul 2024] 1 paper accepted by CIKM 2024
- [Jul 2024] 2 papers accepted by TMLR (paper 1, paper 2)
- [May 2024] 2 papers accepted by IEEE TNNLS & IEEE TFS
- [Feb 2024] Promoted to Senior Lecturer at Halmstad University, Sweden
- [Jan 2024] Editorial Board: Associate Editor of Neural Networks, Elsevier
- [Nov 2023] Editorial Board: Associate Editor of Alexandria Engineering Journal, Elsevier
- [May 2023] 1 paper accepted by ACL 2023
Selected Articles
Topic-wise publication can be found in the Publication section, and full publication at Google Scholar.
Quantum ML
- Tiwari, P., Dehdashti, S., Safty, KH., Bruza, P., & Notzel, J. (2024). Enhancing Quantum Machine Learning: The Power of Non-Linear Optical Reproducing Kernels.
- Tiwari, P., Dehdashti, S., Obeid, A. K., Marttinen, P., & Bruza, P. (2022). Kernel Method based on Non-Linear Coherent States in Quantum Feature Space. Journal of Physics A: Mathematical and Theoretical.
- Tiwari, P., Zhang, L., Qu, Z., & Muhammad, G. (2024). Quantum Fuzzy Neural Network for Multimodal Sentiment and Sarcasm Detection. Information Fusion.
- Qu, Z., Zhang, L., & Tiwari, P. (2024). Quantum Fuzzy Federated Learning for Privacy Protection in Intelligent Information Processing. IEEE Transactions on Fuzzy Systems.
- Moreira, C., Tiwari, P., Pandey, H. M., Bruza, P., & Wichert, A. (2020). Quantum-like Influence Diagrams for Decision-Making. Neural Networks.
Multimodal/Information Fusion
- Qian, Y., Zheng, Z., Tiwari, P., Ding, Y., & Zou, Q. (2024). Multiple Kronecker RLS Fusion-Based Link Propagation for Drug-Side Effect Prediction. Transactions on Machine Learning Research (TMLR).
- Wu, H., Liu, J., Jiang, T., Zou, Q., Qi, S., Cui, Z., Tiwari, P., & Ding, Y. (2024). AttentionMGT-DTA: A Multi-Modal Drug-Target Affinity Prediction Using Graph Transformer and Attention Mechanism. Neural Networks.
Graph Neural Networks
- Liang, G., Tiwari, P., Nowaczyk, S., & Byttner, S. (2024). Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation. CIKM 2024.
- Liang, G., Tiwari, P., Nowaczyk, S., Byttner, S., & Fernandez, F. A. (2024). Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-Temporal Forecasting. IEEE Transactions on Neural Networks and Learning Systems.
(Bio-)NLP
- Zhan, S., Mo, F., Tiwari, P., Wang, B., Li, Q., Nie, JY,. Simonsen, JG. (2024). Mixture of Latent Experts Using Tensor Products. Transactions on Machine Learning Research (TMLR).
- Yu, F., Zhang, H., Tiwari, P., & Wang, B. (2024). Natural Language Reasoning: A Survey. ACM Computing Survey.
- Wang, B., Xie, Q., Pei, J., Tiwari, P., Li, Z., & Fu, J. (2023). Pre-trained Language Models in Biomedical Domain: A Systematic Survey. ACM Computing Survey.
- Gao, Y., Ji, S., Zhang, T., Tiwari, P., & Marttinen, P. (2022). Contextualized Graph Embeddings for Adverse Drug Event Detection. In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD).
- Ji, S., Zhang, T., Ansari, L., Fu, J., Tiwari, P., & Cambria, E. (2021). MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare. LREC 2022.
Healthcare
- Li, X., Zhang, Y., Tiwari, P., Song, D., Hu, B., Yang, M., Zhao, Z., Kumar, N., & Marttinen, P. (2022). EEG Based Emotion Recognition: A Tutorial and Review. ACM Computing Surveys.
- He, L., Niu, M., Tiwari, P., Marttinen, P., Su, R., Jiang, J., Guo, C., Wang, H., Ding, S., Wang, Pan, X., & Dang, W. (2022). Deep Learning for Depression Recognition with Audiovisual Cues: A Review. Information Fusion.
- Saberi-Movahed, F., Rostami, M., Berahmand, K., Karami, S., Tiwari, P., Oussalah, M., & Band, S. S. (2022). Dual Regularized Unsupervised Feature Selection Based on Matrix Factorization and Minimum Redundancy with Application in Gene Selection. Knowledge-Based Systems.
Useful Links
- Google Scholar (Citations: ∼9000, h-index: 45)