Dr. Alwin Poulose was born in Manjapra, Kerala, India, in 1992. He received a B.Sc. degree in computer maintenance and electronics from the Union Christian College, Aluva, Kerala, India, in 2012, an M.Sc. degree in electronics from the MES College Marampally, Kerala, India, in 2014, an M. Tech degree in communication systems from Christ University, Bangalore, India in 2017, and the Ph.D. degree in electronics and electrical engineering from Kyungpook National University, Daegu, South Korea in 2021. From 2021 to 2022, he was a researcher at the Center for ICT & Automobile Convergence (CITAC), Kyungpook National University, where he developed a localization and mapping system for autonomous vehicles. His research interests include localization, human activity recognition, facial emotion recognition, and human behavior prediction. He is a reviewer of prominent engineering and science international journals and has served as a technical program committee member/session chairing at several international conferences. He was a research fellow at the department of electrical and computer engineering, University of Michigan, Dearborn, United States, from 11/2022 to 12/2022. He is currently an Assistant Professor at the School of Data Science, Indian Institute of Science Education and Research (IISER), Thiruvananthapuram, Kerala, India, since January 2023.

Anjali Jain earned her master’s degree in Mathematics and Computing from Banaras Hindu University (BHU), where she specialized in Deep Learning, Machine Learning, Statistics, Data Visualization, and Optimization techniques for data analysis and computational tasks. Her master’s thesis, titled “Brain Tumor MRI Images: Segmentation and Classification,” delves into the segmentation and classification of brain tumor MRI images using advanced techniques such as Generative Adversarial Networks (GANs), transformers, CNN models, and transfer learning. During her academic journey, she participated in a government-funded internship (SRFP-CSTUP) at IIIT Allahabad under the supervision of Prof. Manish Kumar. Her research during this internship focused on a “Comparative Study on Machine Learning Classifiers,” where she analyzed two distinct datasets—one from healthcare and another from agriculture. In addition to her formal education, she completed an online internship with The Sparks Foundation, where she honed her data analysis and visualization skills by working on classification and regression projects. She is passionate about addressing complex challenges in medical image analysis and is committed to leveraging machine learning to drive significant advancements in healthcare.

Prerna Kumari holds a B.Sc. in Mathematics from Patna Women’s College and an M.Sc. in Mathematics and Computing from the DST-Centre for Interdisciplinary Mathematical Sciences (DST-CIMS), Banaras Hindu University. Demonstrating strong theoretical and computational proficiency, she has qualified for the UGC-NET examination three times in Computer Science and Applications and also cleared GATE (Data Science and Artificial Intelligence). Her research interests span Artificial Intelligence, Machine Learning, Deep Learning, and their applications across various domains. She is passionate about leveraging Data Science to solve real-world challenges through innovative and interdisciplinary approaches. She has completed a six-month advanced training in Data Science and Artificial Intelligence conducted by NASSCOM in collaboration with the Ministry of Electronics and Information Technology (MeitY), Government of India. Additionally, she gained hands-on experience during her internships at The Sparks Foundation and Bharat Intern, where she worked on practical data-driven projects. As part of her master’s thesis at BHU, Prerna developed a Deep Learning-based Chilli Thrips Detection System, effectively integrating mathematical modeling with real-world agricultural problem-solving.