Publications
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Biju Dharmapalan Why Women Drift Away from Science https://www.dailyexcelsior.com/why-women-drift-away-from-science/#google_vignette Daily Excelsior In school classrooms, girls often do well in science-sometimes exceptionally well. They score high, answer confidently, and speak about careers in medicine, research, or environmental science with genuine enthusiasm. Yet as the academic funnel narrows, something shifts. By the time science reaches its more demanding spaces-research laboratories, doctoral programmes, institutional leadership-many of these young women are no longer there.Women are often excluded from high-visibility assignments or leadership roles on the assumption that they may not be “available.” |
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Sanjay Kumar Srivastava Building community resilience from the ground up https://www.preventionweb.net/drr-community-voices/building-community-resilience-ground Prevention Web Jeevika is a community-driven initiative on resilience at the intersection of multidimensional poverty and cross-border risk in North Bihar. Effective disaster risk reduction relies on community-led initiatives that leverage local knowledge and social capital to build lasting resilience. This blog post highlights that fostering grassroots action is essential for proactive adaptation and long-term safety. |
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Sanjay Kumar Srivastava Safer Seismic Future with AI https://cms.nias.res.in/sites/default/filesefs/2026-03/Safer%C2%A0Seismic%C2%A0Future%20with%20AI.pdf Surakshit Sansar, Jan-Feb 2026. PP.25-27. Twenty-five years after the Bhuj earthquake, India has strengthened its disaster systems—but seismic risk remains high. Artificial intelligence offers a decisive shift from reactive response to anticipatory risk management through real-time seismic analytics, predictive damage modelling, and smarter emergency logistics. With the India AI Mission providing national infrastructure and coordination, India can embed AI into disaster governance at scale—building cities, systems, and institutions resilient to the earthquakes of the future. |
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Dhananjay A. Sant Understanding NIAS Sculpture https://cms.nias.res.in/sites/default/filesefs/2026-02/Understanding%20NIAS%20sculpture.pdf NIAS |
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Rudrodip Majumdar Evaluation of Energy Transition Readiness in the Residential Cooking Sector Among the Low and Medium-Income Households in Bengaluru https://link.springer.com/chapter/10.1007/978-981-95-3389-3_31 Kumar, R., Majumdar, R. (2026). Renewable Power for Sustainable Growth: Proceedings of ICRP 2024 (Volume 2); Lecture Notes in Electrical Engineering (LNEE) Series, Springer (pp. 349–370). This study examines the readiness of the inhabitants of Bengaluru, a metropolitan city located in the State of Karnataka in India, to shift to electricity-based residential cooking. The study also touches upon the critical knowledge gaps regarding the energy transition from an established LPG-based ecosystem to the new electric cooking ecosystem. Based on a household survey conducted in Bengaluru focusing on low-income and medium-income households, the study briefly discusses the complex interplay between culinary habits and sustainable practices that would dictate the transition readiness in the residential cooking sector on a mass scale. |
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R Srikanth A Methodological Framework for Strategic Electricity Generation Planning in India: Assessing Resource Adequacy Through Probability Risk Metrics https://link.springer.com/chapter/10.1007/978-981-95-3389-3_32 Das, S.S., Majumdar, R., Krishnan, A.V., Srikanth, R. (2026). In: Renewable Power for Sustainable Growth: Proceedings of ICRP 2024 (Volume 2); Lecture Notes in Electrical Engineering (LNEE) Series, Springer (pp. 371–392). This study discusses a methodological framework in conjunction with the existing probability-based risk metrics for assessing the resource adequacy of the electricity generation mix, considering the generation capacities of different sources, their average availability levels, and the possible outages that these sources may suffer from. The simulations show that the available capacity decreases with an increasing number of discrete risk events, which limits the capability of the power system to meet the demand. For a 2-day test simulation (considering a loss of load expectation value of 2 event-days), the loss of load event is found to be 4 events, and the expected unreserved energy is estimated to be 1400 MWh over the predefined, representative 2-day period. |
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A V Krishnan A Methodological Framework for Strategic Electricity Generation Planning in India: Assessing Resource Adequacy Through Probability Risk Metrics https://link.springer.com/chapter/10.1007/978-981-95-3389-3_32 Das, S.S., Majumdar, R., Krishnan, A.V., Srikanth, R. (2026). In: Renewable Power for Sustainable Growth: Proceedings of ICRP 2024 (Volume 2); Lecture Notes in Electrical Engineering (LNEE) Series, Springer (pp. 371–392). This study discusses a methodological framework in conjunction with the existing probability-based risk metrics for assessing the resource adequacy of the electricity generation mix, considering the generation capacities of different sources, their average availability levels, and the possible outages that these sources may suffer from. The simulations show that the available capacity decreases with an increasing number of discrete risk events, which limits the capability of the power system to meet the demand. For a 2-day test simulation (considering a loss of load expectation value of 2 event-days), the loss of load event is found to be 4 events, and the expected unreserved energy is estimated to be 1400 MWh over the predefined, representative 2-day period. |
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Rudrodip Majumdar A Methodological Framework for Strategic Electricity Generation Planning in India: Assessing Resource Adequacy Through Probability Risk Metrics https://link.springer.com/chapter/10.1007/978-981-95-3389-3_32 Das, S.S., Majumdar, R., Krishnan, A.V., Srikanth, R. (2026). In: Renewable Power for Sustainable Growth: Proceedings of ICRP 2024 (Volume 2); Lecture Notes in Electrical Engineering (LNEE) Series, Springer (pp. 371–392). This study discusses a methodological framework in conjunction with the existing probability-based risk metrics for assessing the resource adequacy of the electricity generation mix, considering the generation capacities of different sources, their average availability levels, and the possible outages that these sources may suffer from. The simulations show that the available capacity decreases with an increasing number of discrete risk events, which limits the capability of the power system to meet the demand. For a 2-day test simulation (considering a loss of load expectation value of 2 event-days), the loss of load event is found to be 4 events, and the expected unreserved energy is estimated to be 1400 MWh over the predefined, representative 2-day period. |