1st Edition
Machine Learning in 2D Materials Science
Chapter 1 Introduction to Machine Learning for Analyzing Material–Microbe Interactions
Venkataramana Gadhamshetty, Parvathi Chundi, and Bharat K. Jasthi
Chapter 2 Introduction to 2D Materials
Roberta Amendola and Amit Acharjee
Chapter 3 An Overview of Machine Learning
Dilanga Abeyrathna, Mahadevan Subramaniam, and Parvathi Chundi
Chapter 4 Discovery of 2D Materials with Machine Learning
Md Mahmudul Hasan, Rabbi Sikder, Bharat K. Jasthi, Etienne Z. Gnimpieba, and Venkataramana Gadhamshetty
Chapter 5 Bacterial Image Segmentation through Deep Learning Approach
Ejan Shakya and Pei-Chi Huang
Chapter 6 Self-Supervised Learning-Based Classification of Scanning Electron Microscope Images of Biofilms
Md Ashaduzzaman and Mahadevan Subramaniam
Chapter 7 Quorum Sensing Mechanisms, Biofilm Growth, and Microbial Corrosion Effects of Bacterial Species
Vaibhav Handa, Saurabh Dhiman, Kalimuthu Jawaharraj, Vincent Peta, Alain Bomgni, Etienne Z. Gnimpieba, and Venkataramana Gadhamshetty
Chapter 8 Data-Driven 2D Material Discovery Using Biofilm Data and Information Discovery System (Biofilm-DIDS)
Tuyen Do, Alain Bomgni, Shiva Aryal, Venkataramana Gadhamshetty, Diing D. M. Agany, Tim Hartman, Bichar D. Shrestha Gurung, Carol M. Lushbough, and Etienne Z. Gnimpieba
Biography
Parvathi Chundi, PhD is Professor of Computer Science, University of Nebraska-Omaha. Prior to Omaha, Dr. Chundi was with Agilent Technologies and HP Labs, both in Palo Alto, CA.
Venkataramana Gadhamshetty, PhD, PE is Professor of Environmental Engineering in Department of Civil and Environmental Engineering, South Dakota School of Mines and Technology. He is a cofounder of 2D materials for Biofilm Science Engineering and Technology (2DBEST) center and 2D materials laboratory (2DML) at SDSM&T.
Bharat K. Jasthi, PhD is Associate Professor, Department of Materials and Metallurgical Engineering, South Dakota School of Mines and Technology. Dr. Jasthi has research expertise in the areas of microstructural modification, structure property correlation, new alloy development, powder metallurgy, additive manufacturing, and development of engineered surface thin films and coatings for a wide range of applications.
Carol Lushbough, MA is an Emeritus Professor of Computer Science, University of South Dakota.
