Dr.M.Monica Subashini is a motivated researcher with teaching experience of more than twelve years. She received the B.E degree in Electronics and Instrumentation (EIE) from Karunya Institute of Technology, Bharathiyar University in 2001 and the M.E degree in Applied Electronics from St.Peter’s Engineerng College, Anna University in 2007. Her doctoral degree was towards Medical Image Analysis, (Identification of Astrocytoma Grades based on Image Segmentation using Intelligent Systems) and received PHD in 2014 from VIT University.
In 2008, she joined the Department of Electronics Engineering, Saveetha Engineering College, as a Lecturer, and was a part of the research and development team lead by Prof. Bala Subrahmanyam Piratla (Scientist, ISRO), Professor at Saveetha Engineering College and completed innovative projects. She also collaborated with CISCO systems in establishing Communication & Networking Lab. Since February 2009, she has been with the Department of Electrical Engineering, VIT University, where she was an Assistant Professor, became an Assistant Professor (Sr) in 2012, and an Associate Professor in 2014. Her current research interests include Medical Image Analysis and Modeling, Medical diagnostics and Bio-sensing, Bio-Engineering Artificial Intelligence, Machine learning, Industrial & Human Systems, Tissue health monitoring and Human vital signs measurement.
Dr.Monica Subashini is a member of the Institution of Engineers (India); she has received Gandhian Young Technological Innovation Award (GYTI), 2014 for a project titled "Voice Activated Safety App" by Mithila Harish under her supervision. Also she is leading a team of motivated students in research who regularly participates and fetch laurels in various competitions (OLX Machine Learning Challenge, Techgig Data Science Edition 2 Challenge and ZS Young Data Scientist Challenge 2017), hackathons, symposiums and international conferences.
Based on her specialization and research interests, Dr.Monica Subashini has authored more than 45 International/National Journal papers, International/National conference papers and book chapters. Most of them are published in leading peer-reviewed, referred impact factor journals. She is also a potential reviewer in various journals and conference committees.
A Deep Neural Network-Based Model for Screening Autism Spectrum Disorder Using the Quantitative Checklist for Autism in Toddlers (QCHAT)