I am Rakesh Choudhary, a dedicated and accomplished PhD holder specializing in Artificial Intelligence applications in anaerobic codigestion from the National Institute of Technology Delhi. With a solid foundation in Civil and Environmental Engineering, I have demonstrated excellence throughout my academic journey, including being a Gold Medalist in my M.Tech program from Jagannath University.
My expertise spans across statistical learning, deep learning, supervised learning, and machine learning, with proficiency in advanced tools such as Python, R, MATLAB, and Microsoft Excel. I have applied these skills to tackle complex environmental challenges, particularly in optimizing biogas production processes.
I am passionate about leveraging AI and advanced analytics to drive innovation in sustainable technologies. My research has focused on enhancing the efficiency of anaerobic digestion processes, contributing to the development of sustainable solutions for waste management and energy pro
EDUCATION
🎓 Doctor of Philosophy ( in Civil Environmental Engineering
Research Focus: Artificial Intelligence Applications in Anaerobic Co-Digestion
Institution: National Institute of Technology (NIT) Delhi, New Delhi, India
🎓 Master of Technology (M.Tech.) – Gold Medalist
Discipline: Civil Environmental Engineering
Institution: Jagannath University, Haryana, India
🎓 Bachelor of Technology (B.Tech.)
Discipline: Civil Environmental Engineering
Institution: Netaji Subhas University of Technology (NSUT), West Campus, New Delhi, India
RESEARCH, TEACHING, or OTHER INTERESTS
Environmental Engineering, Artificial Intelligence, Renewable Energy, Sustainability and the Environment, Waste Management and Disposal
Nanobiotechnology-enabled enhancement of process stability and methane production in anaerobic digestion Eman Elbealy, Rahmah N. Al-Qthanin, Rakesh Choudhary, Moharana Choudhury, Sushobhan Majumdar, Kailash Rajaram Harne, Ajay Kumar Frontiers in Environmental Science, 2026 Anaerobic digestion (AD) is widely recognised as a sustainable technology for managing organic waste and generating renewable energy. Despite its potential, slow kinetics, instability under varying operational conditions, and inhibition from toxic intermediates often hinder AD processes. Nanobiotechnology has emerged as a mechanistically promising approach to enhance process stability and methane production by strengthening microbial performance, accelerating hydrolysis kinetics, and reinforcing syntrophic electron transfer pathways. The addition of zero-valent iron, carbon nanotubes, and metal oxides enhances hydrolysis rates, stimulates methanogenic pathways, and facilitates direct interspecies electron transfer (DIET). These mechanisms collectively improve methane yield while maintaining redox balance, buffering capacity, and long-term operational stability. Evidence from laboratory- and pilot-scale studies indicates that nanomaterial amendments can enhance methane production, typically by 10%–60% under optimised dosing conditions in most systems, with higher enhancements reported for selected conductive transition metal carbides under controlled experimental regimes. Reductions in lag phase duration of 15%–40% and improved tolerance to ammonia concentrations exceeding 1.5–3.0 g L −1 NH 4 + –N have also been documented, depending on reactor configuration and substrate type. These enhancement ranges are derived from condition-resolved extraction of experimental studies meeting predefined inclusion criteria and were normalised against non-amended controls under identical operational settings rather than selectively cited maximum values. Additionally, integrating nanomaterials with pretreatment techniques, bioaugmentation, and bio-electrochemical systems offers synergistic pathways for optimising biogas production. However, the application of nanomaterials also raises important environmental and biosafety concerns, including their transformation during digestion, partitioning into digestates, potential impacts on soil and aquatic systems following land application, and challenges related to dose optimisation, recovery, and lifecycle risk assessment. This review applies a condition-resolved quantitative synthesis by extracting methane yield and production rate and stability indicators (e.g., lag phase, VFA, alkalinity, TAN/FAN tolerance) and normalising enhancements against non-amended controls within operational clusters (temperature regime, reactor configuration, ISR/SIR, substrate class, and nanomaterial dose).
Insights into Hazardous and Special Wastes: A Case Study of Latin America Prangya Rath, Farhana Rahman, Harshita Jain, Laxmi Kant Bhardwaj, Pankaj Kanti Jodder, Bhawana Sharma, Moharana Choudhury, CÃntia Soares, Natan Padoin Data Analytics and Smart Technologies in Solid Waste Management Advancing Sustainability, 2026 In recent decades, waste has emerged as a pressing global environmental concern, spurred by urbanization and population growth. In developing nations like Latin America, waste poses significant human health risks. Waste composition has evolved notably since the 20th-century technological revolution, including pollutants such as pesticides, pharmaceuticals, plastics, and nonmaterials, complicating waste management efforts worldwide. This chapter deals with the escalating health and environmental challenges stemming from toxic and special waste in Latin America. It examines the rapid emergence of electronic waste (e-waste), pesticides, medical, mining, and industrial waste due to technological advancements and population growth. Particular attention is paid to the sometimes-disregarded predicament of garbage pickers, constantly exposed to dangerous products, highlighting the necessity of protective regulations. The research illustrates the potential and difficulties in trash management by examining the complex link between garbage creation and technological advancement. To guarantee a sustainable future for waste management in the area, emphasis is focused on the significance of international collaboration and the creation of creative policies. This chapter aims to offer a thorough and innovative viewpoint on handling hazardous and unusual trash in Latin America.
Predicting water quality index using stacked ensemble regression and SHAP based explainable artificial intelligence Rakesh Choudhary, Ajay Kumar, Priyadharsini C., Mude Murali Naik, Moharana Choudhury, Nadeem A. Khan Scientific Reports, 2025 Effective forecasting of the Water Quality Index (WQI) considerably impacts water resource management as well as public health safety. This study proposes a new approach for WQI forecasting using stacked regression ensemble modeling integrated with SHAP (Shapley Additive explanations), a form of Explainable Artificial Intelligence (XAI). The model was developed using a dataset of 1,987 water quality samples from Indian rivers (2005-2014), processed through six optimized machine learning algorithms: XGBoost, CatBoost, Random Forest, Gradient Boosting, Extra Trees, and AdaBoost, combined using Linear Regression as the meta-learner. The model was trained using seven normalized physicochemical parameters as predictors, and the computed WQI (via the weighted arithmetic method) served as the response variable. The stacked ensemble model outperformed all individual models, achieving the highest performance across all evaluation metrics, with R² reaching 0.9952, Adjusted R² at 0.9947, MAE recorded at 0.7637, and RMSE reduced to 1.0704. Among the individual models, CatBoost and Gradient Boosting demonstrated the strongest standalone performance. CatBoost achieved an R² of 0.9894, Adjusted R² at 0.9883 MAE of 0.8399, and RMSE of 1.5905, while Gradient Boosting attained an R² of 0.9907, Adjusted R² at 0.9898 MAE of 1.0759, and RMSE of 1.4898, respectively. SHAP analysis revealed that DO, BOD, conductivity, and pH were the most influential parameters contributing to the prediction of WQI. This integrated framework improves existing approaches by providing high predictive accuracy and model interpretability along with real-time environmental monitoring capabilities. It fosters anticipatory environmental surveillance, automated policy frameworks, and confidence among stakeholders regarding the sustainability of water resources.
Preface Emerging and Re Emerging Viral Diseases Integrating Conventional and Complementary Treatment Strategies, 2025
Electronic Wastes The Manmade Crisis Navamallika Gogoi, Dharitri Borah, Moharana Choudhury Electronic Waste Impact on Health Animals and the Environment, 2025
Preface Electronic Waste Impact on Health Animals and the Environment, 2025
Preface Advances in Hydrology Spatial Intelligence Climate Change and Sustainable Water Resource Management, 2025
Food and Agro-Industrial Wastes Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Preface Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Advances in Hydrology Advances in Hydrology Spatial Intelligence Climate Change and Sustainable Water Resource Management, 2025
Introduction to food and agro industrial wastes Srijan Goswami, Moharana Choudhury, Mika Sillanpää Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Electronic Wastes and Contamination of Water Laxmi Kant Bhardwaj, Prangya Rath, Moharana Choudhury, America Metzdorff, Pankaj Kanti Jodder Electronic Waste Impact on Health Animals and the Environment, 2025
Biorefinery products from food and agro-industrial wastes Satyendra Tripathi, Touseef Hussain, Moharana Choudhury, Eric D. van Hullebusch, Natan Padoin Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Valorization of food and agroindustrial wastes—synthesis and purification Parimal Chandra Ray, Syed Hadi Abdul Rouf, Niraj Singh, Sanjenbam Joel Singh, Moharana Choudhury, Kaleeswari Kalimuthu, CÃntia Soares, Murad Muhammad, Rodgers Nyamosi Rogito, Jay Kumar Verma Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Valorization of food and agroindustrial wastes—biological transformation Pritha Kumar, Sanee Chauhan, Godfred Addai, Rakesh Choudhary, Prapti Sudan, Moharana Choudhury, Ajay Kumar, Angel G. Polanco RodrÃguez, Satyam Kumar Chaudhari, Viola Vambol, Pramod Kumar Food and Agro Industrial Wastes Sustainable Impacts Transformation and Added Value of by Products, 2025
Routes of synthesis and characterizations of nanoparticles Gulzar Ahmed Rather, Arghya Chakravorty, Basharat Ahmad Bhat, Ishfaq Majeed Malik, Fayaz Hussain Mir, Siva Sankar Sana, Vimala Raghavan, Anima Nanda, Moharana Choudhury Applications of Nanomaterials in Agriculture Food Science and Medicine, 2020
Predicting water quality index using stacked ensemble regression and SHAP based explainable artificial intelligence R Choudhary, A Kumar, P C, MM Naik, M Choudhury, NA Khan Scientific Reports 15 (1), 31139 , 2025 2025 Citations: 46
Spatial intelligence integration in smart wastewater systems: advancing efficiency and sustainability in urban sewer networks R Choudhary, LK Bharadwaj, TN Tan, M Choudhury, D Sharma, P Rath, ... 2025 Citations: 5
AI-enhanced air quality assessment and prediction in industrial cities: A case study of Kryvyi Rih, Ukraine M Halaktionov, V Bredun, R Choudhary, M Goroneskul, A Kumar, F Ouiya, ... Ecological Engineering & Environmental Technology 26 (6), 45–56 , 2025 2025 Citations: 8
Electronic wastes, its impact on wildlife and biodiversity PR Chowdhury, S Goswami, R Choudhary, M Choudhury Electronic waste, 65-71 , 2025 2025 Citations: 15
Regional specifics of using community bins in waste management: A case study of rural communities in Poltava Region (Ukraine) V Bredun, R Choudhary, A Kumar Trends in Ecological and Indoor Environmental Engineering 2 (4), 10-17 , 2024 2024 Citations: 8
STUDY AND FINANCIAL ANALYSIS OF PROPOSED MODEL FOR E-WASTE MANAGEMENT R Choudhary, H Laura Universal Research Reports 4 (2), 45-48 , 2017 2017
Study of Main components of E-waste and suggestions of Responsibilities for E-Waste management in India R Choudhary, H Laura Universal Research Reports 4 (2), 38-37 , 2017 2017
MOST CITED SCHOLAR PUBLICATIONS
Predicting water quality index using stacked ensemble regression and SHAP based explainable artificial intelligence R Choudhary, A Kumar, P C, MM Naik, M Choudhury, NA Khan Scientific Reports 15 (1), 31139 , 2025 2025 Citations: 46
Electronic wastes, its impact on wildlife and biodiversity PR Chowdhury, S Goswami, R Choudhary, M Choudhury Electronic waste, 65-71 , 2025 2025 Citations: 15
AI-enhanced air quality assessment and prediction in industrial cities: A case study of Kryvyi Rih, Ukraine M Halaktionov, V Bredun, R Choudhary, M Goroneskul, A Kumar, F Ouiya, ... Ecological Engineering & Environmental Technology 26 (6), 45–56 , 2025 2025 Citations: 8
Regional specifics of using community bins in waste management: A case study of rural communities in Poltava Region (Ukraine) V Bredun, R Choudhary, A Kumar Trends in Ecological and Indoor Environmental Engineering 2 (4), 10-17 , 2024 2024 Citations: 8
Spatial intelligence integration in smart wastewater systems: advancing efficiency and sustainability in urban sewer networks R Choudhary, LK Bharadwaj, TN Tan, M Choudhury, D Sharma, P Rath, ... 2025 Citations: 5
STUDY AND FINANCIAL ANALYSIS OF PROPOSED MODEL FOR E-WASTE MANAGEMENT R Choudhary, H Laura Universal Research Reports 4 (2), 45-48 , 2017 2017
Study of Main components of E-waste and suggestions of Responsibilities for E-Waste management in India R Choudhary, H Laura Universal Research Reports 4 (2), 38-37 , 2017 2017