A statistical model for stroke outcome prediction and treatment planning. - Abhishek Sengupta; Vaibhav Rajan; Sakyajit Bhattacharya; G. R. K. Sarma (EMBC, 2016)

Prediction and imputation in irregularly sampled clinical time series data using hierarchical linear dynamical models. - Abhishek Sengupta; A. P. Prathosh; Satya Narayan Shukla; Vaibhav Rajan; Chandan K. Reddy (EMBC, 2017)

Towards optogenetic vision restoration with high resolution. - Ulisse Ferrari; Stéphane Deny; Abhishek Sengupta; Romain Caplette; Francesco Trapani; José-Alain Sahel; Deniz Dalkara; Serge Picaud; Jens Duebel; Olivier Marre (PLoS Comput. Biol., 2020)

An efficient High-Volume Production Performance Screening using On-Chip Ring Oscillators. - Tobias Kilian; Abhishek Sengupta; Daniel Tille; Martin Huch; Ulf Schlichtmann (DFT, 2023)

Predictive Modeling of Recurrent Implantation Failure and Pre-eclampsia Using Machine Learning and Gene Expression Profiling. - Priyanka Sharma; Shruti Pandey; Sonalika Ray; Mohit Mazumder; Payal Gupta; Abhishek Sengupta; Ankur Chaurasia; Abhishek Sengupta (ICCCNT, 2023)

Predictive Modeling of Recurrent Implantation Failure and Pre-eclampsia Using Machine Learning and Gene Expression Profiling. - Priyanka Sharma; Shruti Pandey; Sonalika Ray; Mohit Mazumder; Payal Gupta; Abhishek Sengupta; Ankur Chaurasia; Abhishek Sengupta (ICCCNT, 2023)

Precision at its Core: Machine Learning-Infused Metabolomics Model for Preterm Birth Prediction in Human. - Ansh Tandon; Tushar Gupta; Aysha Verma; Sudeepti Kulshrestha; Riya Dua; Sharvin Varghese; Romasha Gupta; Nagma Abbasi; Priyanka Narad; Ankur Chaurasia; Abhishek Sengupta (ICCCNT, 2023)