• Sudarsan Sadasivuni et.al In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring

• Sudarsan Sadasivuni et.al Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention

• Sudarsan. Sadasivuni, et. al, "A 43.6 TOPS/W AI Classifier with Sensor Fusion for Sepsis Onset Prediction," 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022, pp. 569-572, doi: 10.1109/BioCAS54905.2022.9948610
• Sudarsan Sadasivuni et.al In‑sensor neural network for high energy efficiency analog‑to‑information conversion, Nature/Scientific Reports (2022) 12:18253 https://doi.org/10.1038/s41598-022-23100-4
• Sudarsan Sadasivuni et al. Fusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset. Sci Rep 12, 5711 (2022). https://doi.org/10.1038/s41598-022-09712-w 
• Sudarsan Sadasivuni, et al. Real time prediction of cardiovascular diseases using reservoir-computing and fusion with electronic medical record. AICAS 2022 Korea, June 13-15, 2022
• Sudarsan Sadasivuni, et al. Real time prediction of cardiovascular disease using fusion of electronic medical record and electrocardiogram AMIA Clinical Informatics Conference Houston, May 24-26, 2022 [#CIC-2022]
• Sudarsan Sadasivuni, et al. Real time Sepsis Prediction Using Function of on-Chip Analog classifier and Electronic Medical Record, 2022 IEEE International Symposium on Circuits & Systems, Austin, Texas May 28- June 1, 2022 [ISCAS-2022]

• Sudarsan Sadasivuni, et al Multi-Task Learning Mixed-Signal Classifier for In-situ Detection of Atrial Fibrillation and Sepsis, Biomedical Circuits and Systems Conference (BIO-CAS-2021) Berlin, Oct 6-9, 2021
• Sudarsan Sadasivuni et al. . Fusion of Fully Integrated Analog Machine Learning Classifier with Electronic Medical Records for Real-Time Prediction of Sepsis Onset. Research Square; 2021. DOI: 10.21203/rs.3.rs-564329/v1. 
• Sudarsan Sadasivuni et al. "Recurrent Neural Network Circuit for Automated Detection of Atrial Fibrillation from Raw ECG" In International Symposium on Circuits and Systems [ISCAS-2021], Korea, 2021, pp. 1-5, doi: 10.1109/ISCAS51556.2021.9401666.  May 24-27

• S. Prashant Bhanushali, S. Sadasivuni, I. Banerjee and A. Sanyal, "Digital Machine Learning Circuit for Real-Time Stress Detection from Wearable ECG Sensor," 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), Springfield, MA, USA, 2020, pp. 978-981, doi: 10.1109/MWSCAS48704.2020.9184466. 
• Sudarsan Sadasivuni et al. "Neural Networks for Authenticating Integrated Circuits Based on Intrinsic Nonlinearity," 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), Springfield, MA, USA, 2020, pp. 253-256, doi: 10.1109/MWSCAS48704.2020.9184655.
• M. Danesh, Aishwarya Bahudhanam Venkatasubramaniyan, Gaurav Kapoor, Naveen Ramesh, Sudarsan Sadasivuni, Sanjeev Tannirkulam Chandrasekaran and Arindam Sanyal   "Unified Analog PUF and TRNG Based on Current-Steering DAC and VCO," in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 28, no. 11, pp. 2280-2289, Nov. 2020, doi: 10.1109/TVLSI.2020.3011648.

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