Journal Publications
Please refer to Google Scholar Profile & RGate Profile for the complete list (including conferences & book chapters).
Please check GitHub repository for codes and datasets. 
* Indicates Joint First Authors


Published/Under Revision/Submitted:

  1. Panja, M.*, Chakraborty, T.*, Biswas, A., Deb, S. (2025+) E-STGCN: Extreme Spatiotemporal Graph Convolutional Networks for Air Quality Forecasting. Submitted. [Preprint | Code]
  2. Wang, X., Chakraborty, T., Chakraborty, B. (2025+) Bayesian Machine Learning for Estimating Optimal Dynamic Treatment Regimes with Ordinal Outcomes. Submitted. [Preprint | Code]​​
  3. Wang, Z., Lee, J. W., Chakraborty, T., Ning, Y., Liu, M., Feng, X., Ong, M. E. H., Liu, N. (2025+) Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission. ​Submitted. [Preprint | Code]
  4. Sadhukhan, P., Chakraborty, T. (2025+) Footprints of Data in a Classifier Model: The Privacy Issues and Their Mitigation through Data Obfuscation.  Submitted. [Preprint]​ ​
  5. Shukla, PK., Chakraborty, T., Sari, M., Sarout, J., Mandal, PP. (2025+) Forecasting creep deformation behaviour of salt rock for energy storage applications: A deep learning and analytical approach. Submitted. ​
  6. Nareti, U.K., Gupta, D., Adak, C., Chattopadhyay, S., Riese, E., Agarwal, M., Kumar, S., Chakraborty, T. (2025+) Engineering Student Perceptions of Introductory CS Course Assessment in an Indian Setting​. Submitted.
  7. Rakshit, A., Bandyopadhyay, G., Chakraborty, T., Biswas, S. (2025+) A Discrete Asymptotic Approximation Approach for Quantitative Analysis of Hedge Error. Submitted. 
  8. Mukhiya, K., Luwang, SR., Nurujjaman, M., Chakraborty, T., Saha, S., Hens, C. (2025+) Universal Patterns in the Blockchain: Analysis of EOAs and Smart Contracts in ERC20 Token Networks. Submitted. 
  9. Das, D., Panja, M., Ray, A., Radhakrishnan, A., Hens, C., Dana, S. K., Murukesh, N., Ghosh, D., Chakraborty, T.,(2025+) Forecasting Precipitation in Bear Island using Probabilistic Machine Learning Informed by Causal Climate Drivers. Submitted. 
  10. Besher, D., Sengupta, A., Chakraborty, T. (2025+) Forecasting the US Climate Policy Uncertainty using Bayesian Machine Learning. Submitted. 
  11. Barman, M., Panja, M., Mishra, N., Chakraborty, T. (2025) Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak. Machine Learning. [Paper | Code]
  12. Liu, X., Deliu, N., Chakraborty, T., Bell, L., Chakraborty, B. (2025) Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study. Annals of Applied Statistics, Vol. 19, pg. 1403-1425. [Paper | Code] ​
  13. Naik, S.M.*, Chakraborty, T.*, Panja, M., Hadid, A., Chakraborty, B. (2025) Skew Probabilistic Neural Networks for Learning from mbalanced Data. Pattern Recognition, Vol. 165 [Paper | Code]​
  14. Banerjee, A., Gupta, S., Priyanshu, P., Kar, A., Saha, R., Chakraborty, T., Ghosh, D., Kurths, J., Hens, C. (2025) ​Recent Changes in Spatiotemporal Patterns of Heat Extremes in South Asia. npj Climate and Atmospheric Science. [Paper]
  15. Chakraborty, T., Chattopadhyay, S., Das, S., Naik, S.M., Hens, C. (2025) A Compounded Burr Probability Distribution for Fitting Heavy-Tailed Data with Applications to Biological Networks. Chaos, Vol. 35 [Paper | Code]
  16. Ghosh, A., Das, P., Chakraborty, T., Das, P., Ghosh, D. (2025) Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study. Journal of Theoretical Biology, Vol. 605 [Paper | Code]
  17. Goswami, R., Garai, A., Sadhukhan, P., Ghosh, P., Chakraborty, T. (2025) Shape Penalized Decision Forests for Imbalanced Data Classification. IEEE Access, Vol. 13, pg. 86380-86395. [Paper | Python Package] 
  18. Das, D., Radhakrishnan, A., Chakraborty, T., Ray, A., Hens, C., Dana, S. K., Ghosh, D., Murukesh, N. (2025) Pattern change of precipitation extremes in Svalbard. Scientific Reports, Vol. 15, pg. 1-13. [Paper] ​​
  19. Sengupta, S.*, Chakraborty, T.*, Singh, S.K. (2024). Forecasting CPI inflation under economic policy and geo-political uncertainty. International Journal of Forecasting, Vol. 41, pg. 953-981. [Paper | Code]
  20. Borah, J.*, Chakraborty, T.*, Nadzir, M., Cayetano, M., Benedetto, F., Majumdar, S. (2024). A Novel Hybrid Approach For Efficiently Forecasting Air Quality Data. IEEE Sensor Letters, Vol. 9, pg. 1-4.  [Paper | Code]​​
  21. Chakraborty, T., Reddy U., Naik, S.M., Panja, M., Manvitha, B. (2024). Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art. Machine Learning: Science and Technology, Vol. 5, pg. 1-35. [Paper] 
  22. Jakhmola, Y., Panja, M. Mishra, N.K., Ghosh, K., Kumar, U., Chakraborty, T. (2024). Spatiotemporal Forecasting of Traffic Flow using Wavelet-based Temporal Attention. IEEE Access, Vol. 12, pg. 188797-188812. [Paper | Code]
  23. Hadid, A.*, Chakraborty, T.*, Busby, D. (2024). When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges. Expert Systems, Vol. 41, pg. 1-16. [Paper]
  24. ​Panja, M*., Chakraborty, T.*, Kumar, U., Liu, N. (2023). Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemic. Neural Networks, Vol. 165, pg. 185-212.  ​[Paper | Code | Medium Post | R Package]
  25. Chakraborty, T., Kamat, G., Chakraborty, A. K. (2023). Bayesian Neural Tree Models for Nonparametric Regression. Australian & New Zealand Journal of Statistics, Vol. 65, pg. 1-26. [Paper | Code] ​
  26. Panja, M*., Chakraborty, T.*, Nadim. Sk., Ghosh, I., Kumar, U., Liu, N. (2023). An ensemble neural network approach to forecast Dengue outbreak based on climatic condition. Chaos, Solitons & Fractals, Vol. 167, pg. 1-14. [Paper | Code]
  27. Thottolil, R., Kumar, U., Chakraborty, T. (2023). Prediction of Transportation Index for Urban Patterns in Small and Medium-sized Indian Cities using Hybrid RidgeGAN Model. Scientific Reports, Vol. 13, pg. 1-18. [Paper | Code] 
  28. Bhattacharyya, A*., Chakraborty, T.*, Rai, S. N. (2022). Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model. Nonlinear Dynamics, Vol. 107, pg. 3025-3040. ​[Paper | Code]
  29. Chakraborty, T., Chattopadhyay, S., Das, S., Kumar, U., Jayavelu, S. (2022). Searching for heavy-tailed probability distributions for modeling real-world complex networks. IEEE Access, Vol. 10, 115092-115107. ​[Paper | Code]  
  30. Chakraborty, T., Das, S., Chattopadhyay, S. (2022). A New Method for Generalizing Burr and Related Distributions. Mathematica Slovaca, Vol. 72, pg. 241-264. [Paper]
  31. Ray, A.*, Chakraborty, T.*, Ghosh, D. (2021). Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events​. Chaos, Vol. 31, pg. 1-15.​ [Paper | Code]
  32. Chattopadhyay, S., Chakraborty, T., Ghosh, K., Das, A. K. (2021). Modified Lomax Model: A heavy-tailed distribution for fitting large-scale real-world complex networks.  Social Network Analysis and Mining, Vol. 11, pg. 11-43. [Paper]
  33. Chakraborty, T., Chakraborty, A. K., Biswas, M., Banerjee, S., Bhattacharya, S. (2021). Unemployment Rate Forecasting: A Hybrid Approach. Computational Economics, Vol. 57, pg. 183-201. [Paper] 
  34. Chakraborty, T., Ghosh, I. (2020). Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis. Chaos, Solitons & Fractals, Vol. 135, pg. 1-10. [Paper | Code]
  35. Chakraborty, T., Chakraborty, A. K. (2020). Hellinger Net : A Hybrid Imbalance Learning Model to Improve Software Defect Prediction. IEEE Transactions on Reliability, Vol. 70, pg. 481-494. [Paper]
  36. Chakraborty, T., & Chattopadhyay, S., Chakraborty, A. K. (2020). Radial basis neural tree model for improving waste recovery process in a paper industry. Applied Stochastic Models in Business and Industry, Vol. 36, pg. 49-61. [Paper | Code]
  37. Chakraborty, T., Chakraborty, A. K. (2020). Superensemble classifier for improving predictions in imbalanced data sets. Communications in Statistics - Case Studies and Data Analysis, Vol. 6, pg. 123-141. [Paper]
  38. Chakraborty, T., Chattopadhyay, S., Ghosh, I. (2019). Forecasting dengue epidemics using a hybrid methodology. Physica A, Vol. 527, pg. 1-8. [Paper]
  39. Chakraborty, T., Chakraborty, A. K., Chattopadhyay, S. (2019). A novel distribution-free hybrid regression model for manufacturing process efficiency improvement. Journal of Computational and Applied Mathematics​, Vol. 362, pg. 130-142. [Paper] ​
  40. Chakraborty, T., Chakraborty, A. K., Murthy, C. A. (2019). A nonparametric ensemble binary classifier and its statistical properties. Statistics & Probability Letters, Vol. 149, pg. 16-23. ​[Paper | Code]​