403 citations · 936 across the 29 of their papers we have counts for
30 papers
GraphSVR: A Graph Convolutional Support Vector Regression Framework for Robust Spatiotemporal Air Pollution Forecasting
Nourin Jahan, Muhammed Navas T, Tanujit Chakraborty +1
Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affected by anomalous observations…
Salt-Rock Creep Deformation Forecasting Using Deep Neural Networks and Analytical Models for Subsurface Energy Storage Applications
Pradeep Kumar Shukla, Tanujit Chakraborty, Mustafa Sari +2
This study provides an in-depth analysis of time series forecasting methods to predict the time-dependent deformation trend (also known as creep) of salt rock under varying confini…
Bayesian Machine Learning for Estimating Optimal Dynamic Treatment Regimes with Ordinal Outcomes
Xinru Wang, Tanujit Chakraborty, Bibhas Chakraborty
Dynamic treatment regimes (DTRs) are sequences of decision rules designed to tailor treatment based on patients' treatment history and evolving disease status. Ordinal outcomes fre…
Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak
Madhab Barman, Madhurima Panja, Nachiketa Mishra +1
Tuberculosis (TB) remains a formidable global health challenge, driven by complex spatiotemporal transmission dynamics and influenced by factors such as population mobility and beh…
E-STGCN: Extreme Spatiotemporal Graph Convolutional Networks for Air Quality Forecasting
Madhurima Panja, Tanujit Chakraborty, Anubhab Biswas +1
Modeling and forecasting air quality is crucial for effective air pollution management and protecting public health. Air quality data, characterized by nonlinearity, nonstationarit…
A Compounded Burr Probability Distribution for Fitting Heavy-Tailed Data with Applications to Biological Networks
Tanujit Chakraborty, Swarup Chattopadhyay, Suchismita Das +2
Complex biological networks, encompassing metabolic pathways, gene regulatory systems, and protein-protein interaction networks, often exhibit scale-free structures characterized b…
Spatiotemporal Forecasting of Traffic Flow using Wavelet-based Temporal Attention
Yash Jakhmola, Madhurima Panja, Nitish Kumar Mishra +3
Spatiotemporal forecasting of traffic flow data represents a typical problem in the field of machine learning, impacting urban traffic management systems. In general, spatiotempora…
Footprints of Data in a Classifier: Understanding the Privacy Risks and Solution Strategies
Payel Sadhukhan, Tanujit Chakraborty
The widespread deployment of Artificial Intelligence (AI) across government and private industries brings both advancements and heightened privacy and security concerns. Article 17…
WaveCatBoost for Probabilistic Forecasting of Regional Air Quality Data
Jintu Borah, Tanujit Chakraborty, Md. Shahrul Md. Nadzir +2
Accurate and reliable air quality forecasting is essential for protecting public health, sustainable development, pollution control, and enhanced urban planning. This letter presen…
Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission
Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty +5
Survival analysis is essential for studying time-to-event outcomes and providing a dynamic understanding of the probability of an event occurring over time. Various survival analys…
When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges
Abdenour Hadid, Tanujit Chakraborty, Daniel Busby
Generative Artificial Intelligence (GAI) represents an emerging field that promises the creation of synthetic data and outputs in different modalities. GAI has recently shown impre…
Forecasting CPI inflation under economic policy and geopolitical uncertainties
Shovon Sengupta, Tanujit Chakraborty, Sunny Kumar Singh
Forecasting consumer price index (CPI) inflation is of paramount importance for both academics and policymakers at the central banks. This study introduces a filtered ensemble wave…
Skew-Probabilistic Neural Networks for Learning from Imbalanced Data
Shraddha M. Naik, Tanujit Chakraborty, Madhurima Panja +2
Real-world datasets often exhibit imbalanced data distribution, where certain class levels are severely underrepresented. In such cases, traditional pattern classifiers have shown…
Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study
Xueqing Liu, Nina Deliu, Tanujit Chakraborty +2
Mobile health (mHealth) interventions often aim to improve distal outcomes, such as clinical conditions, by optimizing proximal outcomes through just-in-time adaptive interventions…
Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art
Tanujit Chakraborty, Ujjwal Reddy K S, Shraddha M. Naik +2
Since their inception in 2014, Generative Adversarial Networks (GANs) have rapidly emerged as powerful tools for generating realistic and diverse data across various domains, inclu…
Prediction of Transportation Index for Urban Patterns in Small and Medium-sized Indian Cities using Hybrid RidgeGAN Model
Rahisha Thottolil, Uttam Kumar, Tanujit Chakraborty
The rapid urbanization trend in most developing countries including India is creating a plethora of civic concerns such as loss of green space, degradation of environmental health,…
An ensemble neural network approach to forecast Dengue outbreak based on climatic condition
Madhurima Panja, Tanujit Chakraborty, Sk Shahid Nadim +3
Dengue fever is a virulent disease spreading over 100 tropical and subtropical countries in Africa, the Americas, and Asia. This arboviral disease affects around 400 million people…
Knowledge-based Deep Learning for Modeling Chaotic Systems
Zakaria Elabid, Tanujit Chakraborty, Abdenour Hadid
Deep Learning has received increased attention due to its unbeatable success in many fields, such as computer vision, natural language processing, recommendation systems, and most…
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting
Lena Sasal, Tanujit Chakraborty, Abdenour Hadid
Deep learning utilizing transformers has recently achieved a lot of success in many vital areas such as natural language processing, computer vision, anomaly detection, and recomme…
Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemics
Madhurima Panja, Tanujit Chakraborty, Uttam Kumar +1
Infectious diseases remain among the top contributors to human illness and death worldwide, among which many diseases produce epidemic waves of infection. The unavailability of spe…
Probabilistic AutoRegressive Neural Networks for Accurate Long-range Forecasting
Madhurima Panja, Tanujit Chakraborty, Uttam Kumar +1
Forecasting time series data is a critical area of research with applications spanning from stock prices to early epidemic prediction. While numerous statistical and machine learni…
Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events
Arnob Ray, Tanujit Chakraborty, Dibakar Ghosh
The remarkable flexibility and adaptability of both deep learning models and ensemble methods have led to the proliferation for their application in understanding many physical phe…
Nowcasting of COVID-19 confirmed cases: Foundations, trends, and challenges
Tanujit Chakraborty, Indrajit Ghosh, Tirna Mahajan +1
The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting more than 200 countries and territories worldwide. As of September 3…
Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis
Tanujit Chakraborty, Indrajit Ghosh
The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020,…