Research Interests

Robust Statistics, Mathematical Modeling of ML Algorithms, Quantum Statistics

Bio

Anand Paul earned, from the National Cheng Kung University, a PhD in Electrical Engineering  (2010). He is now the Associate Professor of the Department of Biostatistics and Data Science, Louisiana State University Health Sciences Center. His work in Statistical Machine Learning with a particular focus on Robust intelligence has resulted in recognizing among top 2% scientists worldwide by Stanford University and Elsevier Publisher for the years 2022-2026. He has been an IEEE senior member since 2015 and member of ACM and ASA. He has more than  200 publications, in reputed journals and conferences. In addition to his research, Dr. Paul has served as an editor for several prestigious SCIE journals, including IEEE Access, Computer Animation and Virtual Worlds, ICT Express, PeerJ Computer Science, Cyber-Physical Systems (Taylor & Francis), AAAI, ICML, Neruips, ICLR, IJCAI-PKDD, EMCL. His research interests include Mathematical Modeling of Machine Learning Algorithms, Quantum Statistics, Data mining.

Publications/Presentations

Recent Publication

•              M Bratton, A Ulfers, G Laborde, V Dasa, P C K, L Leslie, D Jones, A Paul, "Sex and age-specific medication interaction in osteoporosis risk", GeroScience,  August 2026

•              Barathi S, Rathinaraja J, A Paul, "Contrast-Enhanced Gating in GRUs for Robust Low-Data Sequence Learning", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition June 2026.

•              Rathinaraja Jeyaraj, Barathi Subramanian, Kapilya Gangadharan, Anand Paul, "Gesture2Music: A Low-Latency Real-Time Framework for Continuous Gesture-Driven Music Generation", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 2026

•              F Saeed, A Paul, "ISO-DeTr: A novel detection transformer for industrial small object detection", Machine Learning with Applications, 100809, March 2026

•              OS Ajani, A Paul, R Mallipeddi, "A fitness-assignment method for evolutionary constrained multi-objective optimization",  Computers and Electrical Engineering 128, 110769, 2025

•              A Balasubramaniam, T Balasubramaniam, A Paul, DS Han, R Nayak, "Is There a Universal Dimensionality Reduction Technique for Feature Extraction?–A Comparative Analysis", IETE Technical Review, 1-20, 2025

•              A Ganesan, A Paul, "Robust and resilient hidden sequence decoding in noisy data with enhanced HMM and dynamic NN ensembles", International Journal of Data Science and Analytics, July 2025.

•              N Chellamani, SA Albelwi, M Shanmuganathan, P Amirthalingam, A Paul, "Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals",  Biosensors 15 (4), 255, April 2025

•              D Darlan, OS Ajani, A Paul, R Mallipeddi, "A multi-objective benchmark for UAV path planning with baseline results", Swarm and Evolutionary Computation 96, 101968, July 2025

•              N Chellamani, S A Albelwi, M Shanmuganathan, P Amirthalingam, E M Alharbi, H Q S Alatawi, K Prabahar, J B Aljabri, APaul, "A Deep Sparse Capsule Network for Non-Invasive Blood Glucose Level Estimation Using a PPG Sensor" MDPI Sensors, March 2025.

•              B Kuriachen, R Jeyaraj, D Raphael, P Ashok, PS Sundari, A Paul, "Defect detection in fused deposition modelling using lightweight convolutional neural networks",  Engineering Applications of Artificial Intelligence Vol. 141, February 2025.

•              M Lolaev, A Paul, J Kim, "Heuristic Weight Initialization for Transfer Learning in Classification Problems",  Computers, Materials & Continua 85 (2), 4155–4171, September 2025.