R. Banerjee, S. Naskar and S. Sen Sarma, A closer look into the rectangular codes: Where the parity check predominates, Journal of Global Research in Computer Science 3(3) (2012) 17-23.
Title: Machine-mind Design for Natural Language Comprehension (Abstract)
S.K. Pal, R. Banerjee, S. Dutta and S. Sen Sarma, An insight into the Z-number approach to CWW, Fundamenta Informaticae 124(1-2) (2013) 197-229.
S.K. Pal and R. Banerjee, Context-granulation and subjective-information-quantification, Theoretical Computer Science 448 (2013) 2-14.
R. Banerjee and S.K. Pal, Text comprehension and the computational mind agencies, Natural Computing, Springer, 14(4), (2015) 603-635, DOI 10.1007/s11047-014-9478-x.
R. Banerjee and S.K. Pal, Z*-numbers: Augmented Z-numbers for machine-subjectivity representation, Information Sciences, 323 (2015), 143-178.
R. Banerjee and S.K. Pal, A computational model for the endogenous arousal of thoughts through Z*-numbers, Information Sciences, 405 (2017), 227-258.
R. Banerjee and S.K. Pal, Data-structures for multisensory information processing in an embodied machine-mind, IEEE Transactions on Cognitive and Developmental Systems, 10 (3) (2018) 726-737.
R. Banerjee and S.K. Pal, Z*-numbers, data-structures and thinking in machine-mind architecture, IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), (2020), 686-695.
R.Banerjee, S.K. Pal, J.K. Pal, A decade of Z-numbers, IEEE Transactions on Fuzzy Systems, 30 (8) (2022; Accepted 2021), 2800-2012.
S. Kaman, A. Sharma, R. Banerjee, Association between COVID-19 pandemic and serious mental illness: Systematic review within salutogenesis model for public health management, Current Psychiatry Research and Reviews, 19 (3), (2022) 241 - 261.
Km. Bhavna, A. Akhtar, R. Banerjee, D. Roy, Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage, Frontiers in Neuroinformatics, 18, 2024.
Km. Bhavna, N. Ghosh, R. Banerjee, D. Roy, Characterization of the temporal stability of ToM and pain functional brain networks carry distinct developmental signatures during naturalistic viewing. Scientific Reports, 14, (2024), 22479. https://doi.org/10.1038/s41598-024-72945-4
V. Chalka, M. Singh, N. Vadera, P. Shrivastava, G. Uppala , R. Banerjee, S. Dhanekar, K. Rangra, TiO2/PSi Heterostructure based multi-wavelength photodetector system for AIoT applications, IEEE Internet of Things Journal (2025). 10.1109/JIOT.2025.3571918.
Km. Bhavna, N. Ghosh, R. Banerjee, D. Roy, A Lightweight, End-to-End Explainable, and Generalized attention-based Graph Neural Network model trained on high-order spatiotemporal organization of dynamic functional connectivity to classify Autistics from Neurotypicals, Network Neuroscience (2025). (Accepted).
R. Banerjee, S.K. Pal, Machine-mind design for natural language comprehension, TWAS Regional Conference of Young Scientists on "Frontiers in Scientific Research", Bengaluru, 2015.
T. Gaikwad, R. Banerjee, Curiosity-driven intuitive physics learning, ICRA 2021 Workshop on "Learning to Learn: Robotics".
Km. Bhavna, R. Banerjee, D. Roy, End-to-end explainable artificial intelligence derived Theory-of-Mind fingerprints to distinguish between autistic and neuro-Typicals, 9th Annual Conference of Cognitive Science (ACCS9) 2022 & Conference on Next-gen AI: Inspiration from Brain Science (NAiBS) 2023 [Best Poster].
S. Kaman, A. Sharma, R. Banerjee, Can we measure neural correlates of natural wisdom to inform development of artificial wisdom, Next-gen AI: Inspiration from Brain Science (NAiBS) 2023.
Km. Bhavna, R. Banerjee, D. Roy, Theory-of-Mind fingerprints to distinguish autistic and neuro-typicals: An explainable-AI model, 2023 OHBM Annual Meeting.
S. Kaman, A. Sharma, R. Banerjee, Cortical circuits of context adaptability: Understanding neurobehavioral mechanisms Underlying Flexible Behavior, Cogsci 2023 [Abstract] & PReMI 2023 [Paper accepted].
Km. Bhavna, R. Banerjee, D. Roy, Developmental stability and segregation of Theory of Mind and Pain networks carry distinct temporal signatures during naturalistic viewing, ACCS10 2023.
S. Yokoyama, S. Ghosh, V. Dahiya, L. Dahiya, A. Chadha, R. Banerjee, Why do they say DH is the best of both worlds? Navigating DH futures at engineering schools in postcolonial Asia -- ADHO Digital Humanities Conference 2024: Reinvention & Responsibility (accepted)
A. Pal, R. Banerjee, A. Behera, H. Rajeshbhai, J. Suthar, An AI-Based E-Nose: a Novel Approach to Odour Sensing and Emotional Context Recognition, APSCON 2025.
R. Banerjee, S.K. Pal, The Z-number enigma: A study through an experiment, in R. R. Yager, A. M. Abbasov, M. R. Reformat and S. N. Shahbazova (Eds.), Soft Computing: State of the Art Theory and Novel Applications, ser. Studies in Fuzziness and Soft Computing, vol. 291, pp. 71 - 88, Springer, 2013. (Article preprint)
R. Banerjee, S.K. Pal, On Z-numbers and the machine-mind for natural language comprehension, in D.E. Tamir, N.D. Rishe and A. Kandel (Eds.), Fifty Years of Fuzzy Logic and its Applications, ser. Studies in Fuzziness and Soft Computing, vol. 326, pp. 415 - 457, Springer, 2015. (Article preprint)
R. Banerjee, S.K. Pal, A machine-mind architecture and Z*-numbers for real-world comprehension, in S.K. Pal and A. Pal (Eds.), Pattern Recognition and Big Data, pp. 807-844, World Scientific, Singapore, 2017. (Article preprint)
Km Bhavna, R. Banerjee, D. Roy, End-to-end explainable AI: Derived theory-of-mind fingerprints to distinguish between autistic and typically developing and social symptom severity, bioRxiv, 2023.01. 21.525016.
Km. Bhavna, R. Banerjee, D. Roy, Developmental stability and segregation of theory-of-Mind and pain networks carry distinct temporal signatures during naturalistic viewing, bioRxiv, 2023.08. 09.552564.
A. Sharma, S. Kaman, R. Banerjee, Artificial wisdom vs. human Wisdom: A potential quest, 10.31219/osf.io/rnqg7
N. Dadu, H, Singh, R. Banerjee, Grade Guard: A Smart System for Short Answer Automated Grading, https://arxiv.org/abs/2504.01253.
K. Agrawal, R. Banerjee. Synthetic Art Generation and DeepFake Detection A Study on Jamini Roy Inspired Dataset, https://arxiv.org/abs/2503.23226.