Dr. Anitha Jandhyala
Dr. Anitha Jandhyala has a Master’s degree in Mathematics from Jawaharlal Nehru Technological University, Hyderabad, M.B.A in HR from Madurai Kamaraj University, Bachelor of Education from Bangalore University, Master of Philosophy in Mathematics from Madurai Kamaraj University and Doctor of Philosophy from Vellore Institute of Technology, Vellore . She has 18.5 years of experience in teaching under-graduate and Post-graduate students in India and abroad. Earlier, she was working as an adjunct Professor at New Jersey City University, New Jersey, U.S.A . Presently she is working as an Associate Professor in the Department of Management Studies.
|Qualification||Institution||Year||Ph.D||Vellore Institute of Technology||2020||M.Phil||Madurai Kamaraj University||2008||M.B.A||Madurai Kamaraj University||2011||B.Ed||Bangalore University||2007||M.Sc||Jawahar Lal Nehru Technological University||2000|
|Designation||Institution||From||To||Adjunct Professor||New Jersey City University, New Jersey, U.S.A||2018||2020||Assistant Professosr||PES University, Banlore||2008||2017||Sr. Lecturer||T.John College, Bangalore||2005||2008||Lecturer||Nalanda College, Hyderabad||2000||2004|
- Time Table coordinator
- Curriculum committee coordinator
Expertise / list of subjects handled
- Business Mathematics
- Business Statistics
- Numerical methods
- Engineering Mathematics
- Operations Research
- Business Research methods
- Quantitative Techniques for Business
- Data Analysis & Decision Making
- Pre-calculus for Business
- Calculus for Business
- Multi-objective optimization using Statistical and Soft Computing Techniques in Electro Discharge Machine
- Expert Judgement Method to Determine Attribute Weights for Effectively teaching Mathematics in High Schools, International Journal of Mathematics Trends and Technology, 71-76, Volume 66, Issue 3- March 2020.
- A Comparative Analysis of Multi-Criteria Decision-Making Techniques to Optimize the Process Parameters in Electro Discharge Machine, 3rd International Conference on Innovations in Mechanical Engineering (ICIME-2020). Accepted for publication as a book chapter in Lecture Notes in Mechanical Engineering (Springer).
- Optimization of Process Parameters in Electro Discharge Machine using Standard Deviation and TOPSIS method, International Conference on Applications of fluid-Dynamics, ICAFD-2019 AIP Conference Proceedings, Volume 2177, Issue 1, 10.1063/1.5135182
- Optimization of EDM Process Parameters using Standard Deviation and Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA), book chapter in International Conference on Intelligent Manufacturing and Energy Sustainability pp 655-662 (Springer).
- Optimization of Process Parameters in Electro Discharge Machine using Standard Deviation, MULTIMOORA and MOOSRA methods, book chapter in Innovative Product Design and Intelligent Manufacturing Systems, pp 619-629. (Springer)
- Optimization of Process Parameters in Electro Discharge Machine using Standard deviation and MOORA method, in the 4th international conference on Materials and manufacturing engineering-2019. Accepted for publication as a book chapter in Lecture Notes in Mechanical Engineering (Springer) ISSN: 2195-4356, which is indexed by SCOPUS.
- Multi-attribute decision making of Electric Discharge Machining on AISI-D2 steel using TOPSIS method in International Journal of Pharmacy and Technology. March,2018, volume .10/Issue no. 1/ 31188-31201.
- Optimization of Surface Roughness in EDM for D2 Steel by RSM-GA Approach Universal Journal of Mechanical Engineering 2 (6), 205-210, 2014.
- Multi-objective optimization of Surface Roughness and Material removal rate in EDM steel by RSM-GA approach, In International Journal of Pharmacy and Technology. June,2016, volume .8/Issue no. 2/ 12197-12206.
- Comparison of Neural Network Learning Algorithms for prediction of Surface roughness in EDM, Journal of Mechatronics and Intelligent Manufacturing, Volume 3, No.12,2012.
- Multi-Objective optimization of Electrical Discharge Machining Processes using Artificial Neural Network in Jordon Journal of Mechanical & Industrial Engineering Volume10, Number 1, March 2016, Pg 11-18.