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Machine Learning for Semiconductor Materials book cover

1st Edition

Machine Learning for Semiconductor Materials

Edited By Neeraj Gupta, Rashmi Gupta, Rekha Yadav, Sandeep Dhariwal, Rajkumar Sarma Copyright 2026
226 Pages 80 B/W Illustrations
by CRC Press

226 Pages 80 B/W Illustrations
by CRC Press
Also available as eBook on:
Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of technology computer-aided design (TCAD). It provides various algorithms of machine learning, such as regression, decision tree, support vector machine, K -means clustering and so forth. This book also highlights semiconductor materials and their uses in multi-gate... Read more

1. Semiconductor Materials: Current Applications and Limitations of Advanced Semiconductor Devices

C. Shekhar

2. Machine Learning: Introduction and Features

Deborah T. Joy, Raygun Jose, Charu Jain, Divia T. Joy and Rashmi Gupta

3. Fault Detection in Semiconductor Manufacturing: A Classification Analysis of the SECOM Dataset

Vanshika Jain, Rashmi Gupta, Neeraj Gupta and Prashant Kumar

4. Predictive Modelling for Yield Enhancement

Arpita Pattnaik, Neeraj Gupta, Rashmi Gupta, Arun Kumar Singh and Rajkumar Sarma

5. Deep Learning for Image Classification in Semiconductor Inspection

Vanshika Jain, Rashmi Gupta, Neeraj Gupta, Prashant Kumar and Rajat Butola

6. Machine Learning for Semiconductor Devices

Nivedita Manohar Mathkunti and Manjulata Badi

7. Numerical Simulation-Based Biosensing Performance Exploration of a Cylindrical BioFET Using Machine Learning

Amit Das, Sonam Rewari, Binod Kumar Kanaujia, S.S. Deswal and R.S. Gupta

8. Semiconductor Materials for EV and Renewable Energy

Manjulata Badi and Ila Rai

9. Performance Comparison of Vertical TFET Using Triple Metal Gate Structures and Insights of Machine Learning Approach: A Comprehensive Study

Neharika Sharma, Neeraj Gupta, Karamjit Kaur Sikkon and Seema Narwal

10. Design and Performance Exploration of Macaroni Channel-Based Ge/Si Interfaced Nanowire FET for Analog and High-Frequency Applications Using Machine Learning

Apoorva Kaul, Amit Das, Shivani Yadav, Sonam Rewari and Deva Nand

Biography

Neeraj Gupta is an Associate Professor at Amity University Haryana with over 16 years of teaching experience. His expertise includes VLSI design, low-power and analog design, AI and embedded systems. He has published 40+ papers, two book chapters, one book and 12 patents and has received the Best Researcher and Best Teacher Award (2024).

Rashmi Gupta is an Assistant Professor at Amity University Haryana with 13+ years of experience. Her research interests include AI, software engineering and IoT. She has authored 20+ papers, two book chapters, one book and five patents.

Rekha Yadav is an Assistant Professor at DCRUST, Murthal. She specializes in semiconductor device modeling and VLSI design, with 15 years of experience, over 30 publications and four book chapters.

Sandeep Dhariwal is an Associate Professor at Alliance University, Bengaluru. With 14+ years of experience, he focuses on low-power CMOS and semiconductor modeling. He has published 40+ articles, three books and holds three patents.

Rajkumar Sarma is a Postdoctoral Researcher at the University of Limerick, Ireland. With 11+ years of experience, his research spans digital VLSI, FPGA prototyping and quantum architectures. He has 25+ publications, 15+ patents and two books.

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