Welcome!

Hi! I’m Prayag, an Associate Professor in Machine Learning at Halmstad University, Sweden. Visit Google Scholar (Citations: ∼12000, H-index: 50) for my research publications.

Research Interests

• Quantum Machine Learning, Deep Learning, Graph Neural Networks, Federated Learning, Reinforcement Learning, Unsupervised Feature Selection  
• Large Language Models, Computer Vision, and Multimodal Learning  
• Applications: Healthcare, Bioinformatics, and Intelligent Systems
• Model Design: Explainable, Interpretable, and Causal Models
• Internet of Things

News

• [May 2025] 2 papers accepted by ICML 2025 (paper 1, paper 2)
• [April 2025] IEEE Quantum Week Workshop Organizer: Quantum Computing and Reinforcement Learning, 2025
• [Feb 2025] 1 paper accepted by CVPR 2025
• [Jan 2025] 1 paper accepted by NAACL 2025
• [Jan 2025] 3 papers accepted by WWW 2025 (paper 1, paper 2, paper 3)
• [Jan 2025] Workshop Organizer: Quantum Machine Learning for Communication Networks, ICCCN 2025
• [Jan 2025] Joined the Editorial Board as Associate Editor of IEEE Transactions on Fuzzy Systems
• [Dec 2024] Tutorial accepted on Quantum Machine Intelligence and Fuzzy Learning, FUZZ-IEEE 2025
• [Dec 2024] 1 paper accepted by ICASSP 2025
• [Dec 2024] 1 paper accepted by AAAI 2025
• [Dec 2024] Special Session: Quantum Machine Learning Algorithms and Applications, IJCNN 2025
• [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] Joined the Editorial Board as Associate Editor of Neural Networks, Elsevier
• [Nov 2023] Joined the Editorial Board as Associate Editor of Alexandria Engineering Journal, Elsevier
• [May 2023] 1 paper accepted by ACL 2023

Selected Articles

For a full publications list, visit Google Scholar

🔹 Large Language Models, Computer Vision & Multimodal Learning

• Wang C, Fang X, Tiwari P. DyPolySeg: Taylor Series-Inspired Dynamic Polynomial Fitting Network for Few-shot Point Cloud Semantic Segmentation. ICML 2025.
• Wang C, He S, Fang X, Han J, Liu Z, Ning X, Li W, Tiwari P. Point Clouds Meets Physics: Dynamic Acoustic Field Fitting Network for Point Cloud Understanding. CVPR 2025.
• Wang C, He S, Fang X, Wu M, Lam SK, Tiwari P. Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation. AAAI 2025.
• Zhu C, Chen N, Gao Y, Zhang Y, Tiwari P, Wang B. Is Your LLM Outdated? A Deep Look at Temporal Generalization. NAACL 2025.
• Zhan S, Mo F, Tiwari P, Wang B, Li Q, Nie JY, Simonsen JG. Mixture of Latent Experts Using Tensor Products. TMLR 2024.
• Yu F, Zhang H, Tiwari P, & Wang B. Natural Language Reasoning: A Survey. ACM Computing Survey 2024.

🔹 Graph Neural Networks

• Wang Y, Tan S, Shen J, Xu Y, Song H, Xu Q, Tiwari P, Xu M. Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance. ICML 2025.
• Liang G, Abiri N, Hashemi AS, Lundström J, Byttner S, Tiwari P. Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation. ICASSP 2025.
• Liang G, Tiwari P, Nowaczyk S, Byttner S. 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 FA. Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-Temporal Forecasting. IEEE TNNLS.
• Gao Y, Ji S, Zhang T, Tiwari P, Marttinen P. Contextualized Graph Embeddings for Adverse Drug Event Detection. ECML 2022.

🔹 Quantum ML

• Tiwari P, Dehdashti S, Safty KH, Bruza P, Notzel J (2025). Enhancing Quantum Machine Learning: The Power of Non-Linear Optical Reproducing Kernels.
• Yao B, Tiwari P, Li Q (2025). Self-supervised pre-trained neural network for quantum natural language processing. Neural Networks.
• 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 HM, Bruza P, & Wichert A (2020). Quantum-like Influence Diagrams for Decision-Making. Neural Networks

🔹 Healthcare & Bioinformatics

• Liao Q, Zhang Y, Chu Y, Ding Y, Liu Z, Zhao X, Wang Y, Wan J, Ding Y, Tiwari P, Zou Q (2025). Application of Artificial Intelligence In Drug-target Interactions Prediction: A Review. Nature Biomedical Innovations.
• 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.
• 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.
• 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.
• Ji S, Zhang T, Ansari L, Fu J, Tiwari P, Cambria E. MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare. LREC 2022.