- Office Address: 507 Min H. Kao Building
- Phone: 865-974-1125
- Fax: 865-974-5483
- E-mail: firstname.lastname@example.org
- Ph.D. in Computer Application Technology, Jilin University, China, 2019
- M.Sc. in Embedded Microelectronics and Wireless Network Systems, Coventry University, U.K., 2012
- B.Eng. in Electronics Engineering, University of Mumbai, India, 2011
- Diploma in Digital Electronics, Shri Bhagubhai Mafatlal Polytechnic, India, 2008
Milan Parmar is an academician, learner, teacher, developer, consultant, and researcher with a demonstrated history of working in higher education and industry, as well as an excellent research publication record with 9+ years of extensive teaching experience and credentials in data science. He specializes in solving complex problems using machine learning and data analytics, especially in the industrial and healthcare domains. He is currently a lecturer in the Min H. Kao Department of Electrical Engineering and Computer Science. Passionate about cultivating a dynamic and engaging learning experience, he specializes in teaching a range of subjects, including data structures, AI, machine/deep learning, network security, and programming languages. His teaching philosophy revolves around leveraging computer-aided technology to enhance classroom learning environments. By incorporating cutting-edge tools and platforms, he aims to create an immersive and interactive educational setting that resonates with students. His teaching is not just about imparting knowledge but also about nurturing a passion for learning and problem-solving. He is dedicated to empowering students to think critically, collaborate effectively, and excel in the ever-evolving landscape of computer science and software development.
Before arriving at the University of Tennessee, Knoxville, Parmar was a postdoctoral associate researcher in the Computer Science Engineering department at Mississippi State University. He assisted the head of the department (Dr. Shahram Rahimi) in maintaining a PATENT LAB, where his major responsibilities included conducting advanced research experiments in the Natural Language Processing (NLP) project, teaching courses related to data science, helping PhD students and master’s students with their theses, assisting in grant writing, and identifying new analysis topics for the group that could lead to publications. Similarly, from 2016 to 2019, he assisted his Head of Department (Dr. Limin Wang) in maintaining a data science group at Jilin University of Finance and Economics in China. He is the first Indian to receive the Chinese Education Board's Outstanding Foreign Lecturer Award in Jilin Province, China. He has prior experience with outreach programs, workshops, collaboration meetings, and conferences. Motivated to continue contributing to the field of machine learning and AI. He earned his PhD in Computer Science from Jilin University in China (2019), his Master's in Embedded Microelectronics and Wireless Systems from Coventry University in the United Kingdom (2012), his Bachelor of Engineering from Mumbai University in India (2011), and his diploma degree in Digital Electronics from Shri Bhagubhai Mafatlal Polytechnic in India (2008).
He has also advised numerous public and private organizations on the implementation of information systems. Parmar has published more than 15 research articles and conference papers, many of which have appeared in high-impact Q1 and Q2 journals, such as ISA Transactions, IEEE ACCESS, Neurocomputing, and Physica A. His published works have been cited more than 200+ times worldwide, according to his Google Scholar profile. In addition, Dr. Parmar has served as lead editor in special issues for several SCI journals, including "IEEE Transactions on Computers," "IEEE Transactions on Systems, Man, & Cybernetics," and "Computational Intelligence & Neuroscience." Furthermore, he has also peer-reviewed more than 50+ journal articles, according to his Web of Science profile.
Algorithms: Design & Implementation
Machine learning Techniques in Data Analysis
Image Processing & Analysis
Pattern Recognition in medical datasets
Data preprocessing techniques for data mining
Anomaly Detection with clustering algorithms