publications

2026

1. Slithering Through Gaps: Capturing Discrete Isolated Modes via Logistic Bridging

   Pinaki Mohanty and Ruqi Zhang

   In Proceedings of 29th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2026

   Also available on arXiv: 2604.10821

2025

1. Entropy-Guided Sampling of Flat Modes in Discrete Spaces

   Pinaki Mohanty, Riddhiman Bhattacharya, and Ruqi Zhang

   In NeurIPS Workshop on Structured Probabilistic Inference & Generative Modeling (SPIGM), Dec 2025

   Also available on arXiv: 2505.02296

2023

1. Beyond Disagreement-based Learning for Contextual Bandits

   Pinaki Ranjan Mohanty

   Jul 2023

   DOI
2. SDN and application layer DDoS attacks detection in IoT devices by attention-based Bi-LSTM-CNN

   Ishaani Priyadarshini, Pinaki Mohanty, Ahmed Alkhayyat, and 2 more authors

   Transactions on Emerging Telecommunications Technologies, Jul 2023

   Abs DOI

   Abstract The Internet of Things (IoT) is connecting more devices every day. Security is critical to ensure that the devices operate in a trusted environment. The lack of proper IoT security encourages cybercriminals to target many smart devices across the network and gain sensitive information. Distributed Denial of Service (DDoS) attacks are common in the IoT infrastructure and involve hijacking IoT devices to consume resources and interrupt services. This may specifically vandalize the application running the service that the end users are trying to access (application layer DDoS attacks) or flood the network bandwidth leading to network failure (software defined network DDoS attacks). This article proposes a hybrid attention-based bidirectional long short term memory (LSTM) with convolutional neural networks (CNN) to identify DDoS attacks in the application layer and SDN. We deploy several other machine learning models like logistic regression, decision trees, random forests, support vector machines, K-nearest neighbors, extreme gradient boosting, artificial neural networks, CNN, LSTM, CNN-LSTM to evaluate the performance of our proposed model. The evaluation metrics considered for the study are accuracy, precision, recall, and F-1 score. The experimental analysis on multiple datasets exhibits that the proposed model performs the classification efficiently with an accuracy of 99.74% and 99.98%.

2022

1. A study on the sentiments and psychology of twitter users during COVID-19 lockdown period

   Ishaani Priyadarshini, Pinaki Mohanty, Raghvendra Kumar, and 3 more authors

   Multimedia Tools and Applications, Jul 2022

   Abs DOI

   The outbreak of the novel Coronavirus in late 2019 brought severe devastation to the world. The pandemic spread across the globe, infecting more than ten million people and disrupting several businesses. Although social distancing and the use of protective masks were suggested all over the world, the cases seem to rise, which led to worldwide lockdown in different phases. The rampant escalation in the number of cases, the global effects, and the lockdown may have a severe effect on the psychology of people. The emergency protocols implemented by the authorities also lead to increased use in the number of multimedia devices. Excessive use of such devices may also contribute to psychological disorders. Hence, hence it is necessary to analyze the state of mind of people during the lockdown. In this paper, we perform a sentiment analysis of Twitter data during the pandemic lockdown, i.e., two weeks and four weeks after the lockdown was imposed. Investigating the sentiments of people in the form of positive, negative, and neutral tweets would assist us in determining how people are dealing with the pandemic and its effects on a psychological level. Our study shows that the lockdown witnessed more number positive tweets globally on multiple datasets. This is indicative of the positivity and optimism based on the sentiments and psychology of Twitter users worldwide. The study will be effective in determining people’s mental well-being and will also be useful in devising appropriate lockdown strategies and crisis management in the future.

2. A new three-point sixth-order THAGE iteration method for mildly nonlinear two-point boundary value problems with engineering applications

   Pinaki Ranjan Mohanty

   Engineering with Computers, Jul 2022

   Abs DOI

   We study a new sixth-order compact discretization using uniform three-grid point for the mildly nonlinear differential equation }}\backslashphi ”=g(t,\backslashphi )}}, subject to the values of ϕgiven at two end points of the regular solution interval. We also discuss three-step AGE (THAGE) iteration method as an application to the resulting difference equation as a powerful numerical computation device. In this algorithm, the common term is evaluated first to save the CPU time in comparison with the corresponding two-step algorithm. In addition, the error analysis is studied. Numerical performance is compared with the exact solution, and with the two-step AGE and SOR iteration methods.

2021

1. Analyzing Some Elements of Technological Singularity Using Regression Methods

   Ishaani Priyadarshini, Pinaki Ranjan Mohanty, and Chase Cotton

   Computers, Materials and Continua, Jul 2021

   Abs DOI

   Technological advancement has contributed immensely to human life and society. Technologies like industrial robots, artificial intelligence, and machine learning are advancing at a rapid pace. While the evolution of Artificial Intelligence has contributed significantly to the development of personal assistants, automated drones, smart home devices, etc., it has also raised questions about the much-anticipated point in the future where machines may develop intelligence that may be equal to or greater than humans, a term that is popularly known as Technological Singularity. Although technological singularity promises great benefits, past research works on Artificial Intelligence (AI) systems going rogue highlight the downside of Technological Singularity and assert that it may lead to catastrophic effects. Thus, there is a need to identify factors that contribute to technological advancement and may ultimately lead to Technological Singularity in the future. In this paper, we identify factors such as Number of scientific publications in Artificial Intelligence, Number of scientific publications in Machine Learning, Dynamic RAM (Random Access Memory) Price, Number of Transistors, and Speed of Computers’ Processors, and analyze their effects on Technological Singularity using Regression methods (Multiple Linear Regression and Simple Linear Regression). The predictive ability of the models has been validated using PRESS and k-fold cross-validation. Our study shows that academic advancement in AI and ML and Dynamic RAM prices contribute significantly to Technological Singularity. Investigating the factors would help researchers and industry experts comprehend what leads to Technological Singularity and, if needed, how to prevent undesirable outcomes.

2. A new sixth-order approximation for nonlinear two-point boundary value problems: application of single-step alternating group explicit iteration method to engineering problems

   Pinaki Ranjan Mohanty

   Engineering with Computers, Jul 2021

   Abs DOI

   We report a new three-point compact sixth-order approximation for the solution of nonlinear two-point boundary value problems }} {-}w\^{\backslashprime\backslashprime} + f\backslashleft( {t,w} \backslashright) = 0 }}, subject to natural boundary conditions prescribed at two end points. We also discuss the application of single-step alternating group explicit (SAGE) iteration method to the nonlinear difference equation as a computational tool. The error analysis of the SAGE iteration method is discussed briefly. We have compared the results obtained by using the proposed SAGE iteration method with the results obtained by corresponding two-step alternating group explicit iteration method to demonstrate experimentally the superiority of the proposed method.