H. Kodamana

发表

Approaches to robust process identification: A review and tutorial of probabilistic methods

Nima Sammaknejad, Ruomu Tan, Hariprasad Kodamana, 2018, Journal of Process Control.

Deep learning aided rational design of oxide glasses

Jayadeva, Mathieu Bauchy, N. M. Anoop Krishnan, 2019, Materials Horizons.

TASAC: a twin-actor reinforcement learning framework with stochastic policy for batch process control

H. Kodamana, Tanuja Joshi, H. Kandath, 2022, ArXiv.

Glass Fracture Upon Ballistic Impact: New Insights From Peridynamics Simulations

H. Kodamana, M. Bauchy, N. Krishnan, 2019, Front. Mater..

Insights from principal component analysis applied to Py-GCMS study of Indian coals and their solvent extracted clean coal products

H. Kodamana, Ajishnu Roy, H. Dhawan, 2021, International Journal of Coal Science & Technology.

Hierarchically Distributed Monitoring for the Early Prediction of Gas Flare Events

Biao Huang, H. Kodamana, M. Nixon, 2019, Industrial & Engineering Chemistry Research.

A text mining framework for screening catalysts and critical process parameters from scientific literature - a study on Hydrogen production from alcohol

H. Kodamana, Avan Kumar, S. Ganesh, 2022, Chemical Engineering Research and Design.

Predicting Young’s Modulus of Glasses with Sparse Datasets using Machine Learning

H. Kodamana, M. Bauchy, N. Krishnan, 2019 .

Prediction of Synoptic-Scale Sea Level Pressure Over the Indian Monsoon Region Using Deep Learning

K. S. Srujan, H. Kodamana, S. Sandeep, 2021, IEEE Geoscience and Remote Sensing Letters.

A Dynamical Linkage Between Western North Pacific Tropical Cyclones and Indian Monsoon Low‐Pressure Systems

H. Kodamana, S. Sandeep, E. Suhas, 2022, Geophysical Research Letters.

Batch-to-Batch Adaptive Iterative Learning Control—Explicit Model Predictive Control Two-Tier Framework for the Control of Batch Transesterification Process

H. Kodamana, S. Bhartiya, Riju De, 2022, ACS omega.

Semi‐supervised dynamic latent variable modeling: I/O probabilistic slow feature analysis approach

Biao Huang, Hariprasad Kodamana, Lei Fan, 2018, AIChE Journal.

Gaussian process modelling with Gaussian mixture likelihood

Biao Huang, Atefeh Daemi, Hariprasad Kodamana, 2019, Journal of Process Control.

Application of machine learning in understanding plant virus pathogenesis: trends and perspectives on emergence, diagnosis, host-virus interplay and management pdf

Hariprasad Kodamana, Dibyendu Ghosh, Srija Chakraborty, 2021, Virology Journal.

An Efficient and Stabilizing Model Predictive Control of Switched Systems

Sharad Bhartiya, Hariprasad Kodamana, H. Kodamana, 2017, IEEE Transactions on Automatic Control.

An adaptive, interacting, cluster-based model for predicting the transmission dynamics of COVID-19

Hariprasad Kodamana, Sourabh Singh, R. Ravinder, 2020, Heliyon.

Deep learning aided automatic and reliable detection of tomato begomovirus infections in plants

H. Kodamana, S. Chakraborty, S. Chakraborty, 2021, Journal of Plant Biochemistry and Biotechnology.

Multi-objective dynamic optimization of hybrid renewable energy systems

H. Kodamana, Manojkumar Ramteke, Reena Sharma, 2021, Chemical Engineering and Processing - Process Intensification.

Predicting Young's modulus of oxide glasses with sparse datasets using machine learning

Mathieu Bauchy, Nitya Nand Gosvami, N. M. Anoop Krishnan, 2019, Journal of Non-Crystalline Solids.

Successive Linearization based Stochastic Model Predictive Control for batch processes described by DAEs

Hariprasad Kodamana, Laxman Leema Atmaram, H. Kodamana, 2020 .

Switching Conditional Random Field Approach to Process Operating Mode Diagnosis for Multi-Modal Processes

Biao Huang, Hariprasad Kodamana, Mengqi Fang, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Prediction of ENSO Beyond Spring Predictability Barrier Using Deep Convolutional LSTM Networks

Hariprasad Kodamana, Mayuna Gupta, S. Sandeep, 2022, IEEE Geoscience and Remote Sensing Letters.

Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses with large datasets

H. Kodamana, N. Krishnan, R. Ravinder, 2021, Materials Advances.

Process control of mAb production using multi-actor proximal policy optimization

H. Kodamana, Tanuja Joshi, Nikita Gupta, 2023, Digital Chemical Engineering.

TASAC: A twin-actor reinforcement learning framework with a stochastic policy with an application to batch process control

H. Kodamana, Tanuja Joshi, N. Kaisare, 2023, Control Engineering Practice.

Twin actor twin delayed deep deterministic policy gradient (TATD3) learning for batch process control

Harikumar Kandath, Hariprasad Kodamana, Tanuja Joshi, 2021, Comput. Chem. Eng..

Reinforcement learning based optimization of process chromatography for continuous processing of biopharmaceuticals

Anurag S. Rathore, Hariprasad Kodamana, Saxena Nikita, 2021, Chemical Engineering Science.

Reinforcement learning based control of batch polymerisation processes

Vikas Vikram Singh, Hariprasad Kodamana, H. Kodamana, 2020 .

A novel approach to process operating mode diagnosis using conditional random fields in the presence of missing data

Biao Huang, Nima Sammaknejad, Hariprasad Kodamana, 2018, Comput. Chem. Eng..

Mixtures of Probabilistic PCA With Common Structure Latent Bases for Process Monitoring

Biao Huang, Hariprasad Kodamana, Rahul Raveendran, 2019, IEEE Transactions on Control Systems Technology.

Process monitoring using a generalized probabilistic linear latent variable model

Biao Huang, Hariprasad Kodamana, Rahul Raveendran, 2018, Autom..

Fault detection and isolation using probabilistic wavelet neural operator auto-encoder with application to dynamic processes

H. Kodamana, S. Chakraborty, Jyoti Rani, 2023, Process Safety and Environmental Protection.

A Novel Dynamic Just-in-Time Learning Framework for Modeling of Batch Processes

Tanuja Joshi, Hariprasad Kodamana, Vishesh Goyal, 2020 .

An Adaptive, Interacting, Cluster-Based Model Accurately Predicts the Transmission Dynamics of COVID-19

A. Sharma, R. Ravinder, S. Singh, 2020, medRxiv.

FRIGATE: Frugal Spatio-temporal Forecasting on Road Networks

H. Kodamana, Mridul Gupta, Sayan Ranu, 2023, ArXiv.

A Deep Learning Framework for the Detection of Tropical Cyclones From Satellite Images

K. S. Srujan, V. John, H. Kodamana, 2021, IEEE Geoscience and Remote Sensing Letters.

Fault detection and isolation of multi-variate time series data using spectral weighted graph auto-encoders

H. Kodamana, Sandeep Kumar, Jyoti Rani, 2023, Journal of the Franklin Institute.

Variance-Capturing Forward-Forward Autoencoder (VFFAE): A Forward Learning Neural Network for Fault Detection and Isolation of Process Data

H. Kodamana, Manojkumar Ramteke, Umang Goswami, 2023, Process Safety and Environmental Protection.

Fault detection of pressurized heavy water nuclear reactors with steady state and dynamic characteristics using data-driven techniques

H. Kodamana, Ajishnu Roy, P. Tamboli, 2023, Progress in Nuclear Energy.

Multiobjective Bayesian Optimization Framework for the Synthesis of Methanol from Syngas Using Interpretable Gaussian Process Models

H. Kodamana, K. Pant, S. Upadhyayula, 2022, ACS omega.

Multi-objective Optimization Based Recursive Feature Elimination for Process Monitoring

Manojkumar Ramteke, Hariprasad Kodamana, Anubha Agrawal, 2021, Neural Processing Letters.

Real-Time Mode Diagnosis for Processes With Multiple Operating Conditions Using Switching Conditional Random Fields

Biao Huang, Hariprasad Kodamana, Mengqi Fang, 2020, IEEE Transactions on Industrial Electronics.

Identification of robust probabilistic slow feature regression model for process data contaminated with outliers

Biao Huang, Hariprasad Kodamana, Lei Fan, 2018 .

Robust Identification of Nonlinear Errors-in-Variables Systems With Parameter Uncertainties Using Variational Bayesian Approach

Yongsheng Ding, Fan Guo, Biao Huang, 2017, IEEE Transactions on Industrial Informatics.

A Stabilizing Sub-Optimal Model Predictive Control for Quasi-Linear Parameter Varying Systems

P. S. V. Nataraj, Sharad Bhartiya, Hariprasad Kodamana, 2020, IEEE Control Systems Letters.

An Augmented Model Approach for Identification of Nonlinear Errors-in-Variables Systems Using the EM Algorithm

Yongsheng Ding, Fan Guo, Biao Huang, 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

A Convolutional Neural Network-based gradient boosting framework for prediction of the band gap of photo-active catalysts

H. Kodamana, S. Upadhyayula, Avan Kumar, 2023, Digital Chemical Engineering.

Dynamic prediction of interface level using spatial temporal markov random field

Biao Huang, Artin Afacan, Hariprasad Kodamana, 2019, Comput. Chem. Eng..

Mirage: Model-Agnostic Graph Distillation for Graph Classification

H. Kodamana, S. Manchanda, Mridul Gupta, 2023, ArXiv.

Application of twin delayed deep deterministic policy gradient learning for the control of transesterification process pdf

Harikumar Kandath, Hariprasad Kodamana, Tanuja Joshi, 2021, ArXiv.

A Dynamical Linkage Between Western North Pacific Tropical Cyclones and Indian Monsoon Low‐Pressure Systems

K. S. Srujan, H. Kodamana, S. Sandeep, 2021, Geophysical Research Letters.

A deep learning-aided multi-objective optimization of a downstream process for production of monoclonal antibody products

H. Kodamana, Md Nasre Alam, Anupa Anupa, 2024, Biochemical Engineering Journal.

Forecasting sustainable power generation profiles to achieve net zero emissions using multi-objective techno-ecological framework: A study in the context of India

B. Bakshi, H. Kodamana, Manojkumar Ramteke, 2023, Comput. Chem. Eng..

Recycle-BERT: Extracting Knowledge about Plastic Waste Recycling by Natural Language Processing

B. Bakshi, H. Kodamana, Manojkumar Ramteke, 2023, ACS Sustainable Chemistry & Engineering.

Renewables-Integrated Energy Systems Can Provide Electricity at Lower Cost with Less Environmental and Social Damage

B. Bakshi, H. Kodamana, Manojkumar Ramteke, 2022, ACS Sustainable Chemistry & Engineering.

Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data

H. Kodamana, Tapas Tripura, Souvik Chakraborty, 2024, ArXiv.

Quantifying ecosystem services from trees by using i-tree with low-resolution satellite images

B. Bakshi, H. Kodamana, Manojkumar Ramteke, 2024, Ecosystem Services.

Identification of nonlinear errors-in-variables systems in state-space form: A linear parameter varying approach

Juan Li, Biao Huang, J. Fraser Forbes, 2017, 2017 11th Asian Control Conference (ASCC).

Weakly supervised large-scale pancreatic cancer detection using multi-instance learning

H. Kodamana, Keerthiveena Balraj, Shyamapada Mandal, 2024, Frontiers in oncology.

Hierarchical Distributed Monitoring for Early Prediction of Gas Flare Events

Biao Huang, H. Kodamana, M. Nixon, 2019 .