A Review of Converter Topologies for Battery Charging Applications in Plug-in Hybrid Electric Vehicles. - Siddhant Kumar; Adil Usman (IAS, 2018)

Association Learning based Hybrid Model for Cloud Workload Prediction. - Siddhant Kumar; Neha Muthiyan; Shaifu Gupta; Dileep Aroor Dinesh; Aditya Nigam (IJCNN, 2018)

Body Weight Support Assisted Virtual Reality based Treadmill Walk with Gait Characterization. - Dhaval Solanki; Siddhant Kumar; Pradeep Raj; Uttama Lahiri (ICCCNT, 2019)

gCrop: Internet-of-Leaf-Things (IoLT) for Monitoring of the Growth of Crops in Smart Agriculture. - Siddhant Kumar; Gourav Chowdhary; Venkanna Udutalapally; Debanjan Das; Saraju P. Mohanty (iSES, 2019)

Sentiment Analysis Using Cuckoo Search for Optimized Feature Selection on Kaggle Tweets. - Akshi Kumar 001; Arunima Jaiswal; Shikhar Garg; Shobhit Verma; Siddhant Kumar (Int. J. Inf. Retr. Res., 2019)

Unsupervised discovery of interpretable hyperelastic constitutive laws. - Moritz Flaschel; Siddhant Kumar; Laura De Lorenzis (CoRR, 2020)

Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy. - Li Zheng; Siddhant Kumar; Dennis M. Kochmann (CoRR, 2020)

A Simple Short-Circuit Protection Scheme for Grid Connected Boost Converter using Output Voltage Characteristic. - Siddhant Kumar; Bharat Singh Rajpurohit (IAS, 2021)

What machine learning can do for computational solid mechanics. - Siddhant Kumar; Dennis M. Kochmann (CoRR, 2021)

Floating Isogeometric Analysis. - Helge C. Hille; Siddhant Kumar; Laura De Lorenzis (CoRR, 2021)

Discovering plasticity models without stress data. - Moritz Flaschel; Siddhant Kumar; Laura De Lorenzis (CoRR, 2022)

Bayesian-EUCLID: discovering hyperelastic material laws with uncertainties. - Akshay Joshi; Prakash Thakolkaran; Yiwen Zheng; Maxime Escande; Moritz Flaschel; Laura De Lorenzis; Siddhant Kumar (CoRR, 2022)

NN-EUCLID: deep-learning hyperelasticity without stress data. - Prakash Thakolkaran; Akshay Joshi; Yiwen Zheng; Moritz Flaschel; Laura De Lorenzis; Siddhant Kumar (CoRR, 2022)

Automated discovery of generalized standard material models with EUCLID. - Moritz Flaschel; Siddhant Kumar; Laura De Lorenzis (CoRR, 2022)

Numerical Approaches for Investigating Quasiconvexity in the Context of Morrey's Conjecture. - Jendrik Voss; Robert J. Martin; Oliver Sander; Siddhant Kumar; Dennis M. Kochmann; Patrizio Neff (J. Nonlinear Sci., 2022)

Malware Classification Using Machine Learning Models. - Sudesh Kumar; Shersingh; Siddhant Kumar; Karan Verma (ICMLDE, 2023)

Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID. - Moritz Flaschel; Huitian Yu; Nina Reiter; Jan Hinrichsen; Silvia Budday; Paul Steinmann; Siddhant Kumar; Laura De Lorenzis (CoRR, 2023)

Enhanced Floating Isogeometric Analysis. - Helge C. Hille; Siddhant Kumar; Laura De Lorenzis (CoRR, 2023)

Unifying the design space of truss metamaterials by generative modeling. - Li Zheng; Siddhant Kumar; Dennis M. Kochmann (CoRR, 2023)

Inverse Design of Vitrimeric Polymers by Molecular Dynamics and Generative Modeling. - Yiwen Zheng; Prakash Thakolkaran; Jake A. Smith; Ziheng Lu; Shuxin Zheng; Bichlien H. Nguyen; Siddhant Kumar; Aniruddh Vashisth (CoRR, 2023)

A discontinuous Galerkin / cohesive zone model approach for the computational modeling of fracture in geometrically exact slender beams. - Sai Kubair Kota; Siddhant Kumar; Bianca Giovanardi (CoRR, 2023)

Experiment-informed finite-strain inverse design of spinodal metamaterials. - Prakash Thakolkaran; Michael A. Espinal; Somayajulu Dhulipala; Siddhant Kumar; Carlos M. Portela (CoRR, 2023)

HyperCAN: Hypernetwork-Driven Deep Parameterized Constitutive Models for Metamaterials. - Li Zheng; Dennis M. Kochmann; Siddhant Kumar (CoRR, 2024)

Deep learning reveals key predictors of thermal conductivity in covalent organic frameworks. - Prakash Thakolkaran; Yiwen Zheng; Yaqi Guo; Aniruddh Vashisth; Siddhant Kumar (CoRR, 2024)

Inverse Designing Surface Curvatures by Deep Learning. - Yaqi Guo; Saurav Sharma; Siddhant Kumar (Adv. Intell. Syst., 2024)

A topology optimisation framework to design test specimens for one-shot identification or discovery of material models. - Saeid Ghouli; Moritz Flaschel; Siddhant Kumar; Laura De Lorenzis (CoRR, 2025)

Can KAN CANs? Input-convex Kolmogorov-Arnold Networks (KANs) as hyperelastic constitutive artificial neural networks (CANs). - Prakash Thakolkaran; Yaqi Guo; Shivam Saini; Mathias Peirlinck; Benjamin Alheit; Siddhant Kumar (CoRR, 2025)

DiffuMeta: Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers. - Li Zheng; Siddhant Kumar; Dennis M. Kochmann (CoRR, 2025)