Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks. - Sneha Saha; Thiago Rios; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck; Xin Yao 001; Zhao Xu 001; Patricia Wollstadt (ICDM Workshops, 2019)

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior. - Sneha Saha; Thiago Rios; Leandro L. Minku; Xin Yao 001; Zhao Xu 001; Bernhard Sendhoff; Stefan Menzel (SSCI, 2019)

Quantifying The Generative Capabilities Of Variational Autoencoders For 3D Car Point Clouds. - Sneha Saha; Stefan Menzel; Leandro L. Minku; Xin Yao 001; Bernhard Sendhoff; Patricia Wollstadt (SSCI, 2020)

Exploiting Linear Interpolation of Variational Autoencoders for Satisfying Preferences in Evolutionary Design Optimization. - Sneha Saha; Leandro L. Minku; Xin Yao 001; Bernhard Sendhoff; Stefan Menzel (CEC, 2021)

Exploiting Generative Models for Performance Predictions of 3D Car Designs. - Sneha Saha; Thiago Rios; Leandro L. Minku; Bas van Stein; Patricia Wollstadt; Xin Yao 001; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (SSCI, 2021)

Split-AE: An Autoencoder-based Disentanglement Framework for 3D Shape-to-shape Feature Transfer. - Sneha Saha; Leandro L. Minku; Xin Yao 001; Bernhard Sendhoff; Stefan Menzel (IJCNN, 2022)

Learning-based generative representations for automotive design optimization. - Sneha Saha (2023)

Predictive Healthcare Analytics: A Multidisease Approach using Logistic Regression. - Shibaa Naik; Pushpak Kumar; Sneha Saha; Samriddha Das Bairagya; Darshan Rawat; Santos Kumar Baliarsingh (ICCCNT, 2024)