Ramesh VENKADACHALAM PALANI
Asst. Professor of Mathematics
Department of Mathematics
Central University of Tamil Nadu

Main Office: CLC 1b, Central University of Tamil Nadu, Thiruvarur, Neelakudy, Tamil Nadu 610005
Phone: +91-8300251729 / +91-9962551729
Email: vpramesh@gmail.com, rameshmat@cutn.ac.in


Our Pedagogical Initiative



Ph.D. Thesis Guidance:

  • Thatchaayini R, A Note on Gauss's Theorem on primitive Roots (2018)
  • Priyanga B, Design and analysis of an a priori mesh for singularly perturbed problems (2018)
  • Prithvi M, Error estimates of numerical algorithms for singularly perturbed problems with discontinuous data (2019)

M.Phil. Thesis Guidance:

  • Saswati Sinha, Primitive roots in contrast to Semi-Primitive roots modulo n (2019)

Integrated M.Sc. Thesis Guidance: (1 year duration)

  • Aarthi T, A few computations in the multiplicative group modulo n (2019)
  • Ashish Sahoo, Benchmarking Machine Learning Algorithms for Optical Characters Recognition: Which one does it better? (2019)
  • Anagha N V, Computing the Upper Bound of Phi Function of RSA Cryptosystem (2019)
  • Anjali Sushil V, Relation Between Orbits and Strongly unequal permutations in S n and its Application in Solving sudoku (2019)
  • Bharathi K, A Note on S. Sivasankaranarayana Pillai’s Theorem (2019)
  • Mathew Alex, Pneumonia Detection on Chest X-Rays with Machine Learning (2019)
  • Rupika T, Hand written digit Recoginition: An Empirical Comparison of Machine Learning Algorithms (2019)
  • Sivaranjani N, Credit rating of consumers with little financial history - Risk Analysis (2019)
  • Anjali P V, Stirling Numbers and Transpositions (2018)
  • Athira S, Sales forecast using the method of Random forest (2018)
  • Eyamuna N, Machine learning algorithm for image classification to distinguish dogs from cats (2018)
  • Geethanjali K, Deep learning and image categorization using supervised learning algorithms for Human- Computer interaction (2018)
  • Kalaivani M, Machine learning algorithm to understand the deforestation of the amazon from space (2018)
  • Kanimozhi C, Monitoring invasive species by convolutional neural network (2018)
  • Mageshpriya D, A note on retractable module (2018)
  • Manna Elza Joseph, Some techniques in image segmentation (2018)
  • Rajeswari E, Market basket analysis using F1 score maximization (2018)
  • Aswathi KV, Big data analytics on customer behavior using light GBM model (2018)
  • Aishwarya R, Big Data Retail Analytics for Demand Planning (Using Artificial Neural Network) (2017)
  • Favas L, Supervised Machine Learning Using Convolutional Neural Networks for Image Classification (2017)
  • Jobin Idiculla, A Naive Bayes model for aspect-level sentiment analysis of text data (2017)
  • Makeshwari M, Zero-sum problems in finite groups (2017)
  • Preethi S, Talking Data Mobile User Demographics - Big Data Analytics (2017)
  • Vijitha S, The Multinomial Logistic Regression for Big Data Analytics (2017)
  • Aarthika, Computational number theory and visualization using open source software R (2016)
  • Anitha L, Some Identities based on Cantors idea of height of the polynomial - A new concept (2016)
  • Divya D, Pedagogy of machine learning using artificial neural network (simulating the human brain) (2016)
  • Gowtham R , Computability and Complexity Analysis of Decision Problems (Charles Babbage - David Hilbert - Alan Turing) (2016)
  • Preethi S, Artificial Neural Network based big data analytics for Winton Stock Market Challenge (Supervised learning system) (2016)
  • Vengadesan N, Computational Number Theory and Visualization using Python (2016)
  • Aarthi D, Computation of American option by Crank-Nicholson Method (2015)
  • Manjula R, Computation of American Option (2015)
  • Prithvi M, Sudoku and Directional Change of Lexicographic Permutations: A new theory (2015)
  • Thatchaayini R, Combinations & Point wise Unequal Permutations with Applications to Sudoku (2015)
  • Priyadharshini M, Open Source Software for Big Data Analytics : R (2015)
  • Priyanga B, Regression for Big Data Analytics using R and Python (2015)
  • Shiva Prakash YV, Health care Big Data Analytics - Predicting Diabetes: A Case Study (2015)
  • Sowmitha R, Open Source Software for Big Data Analytics : Python (2015)

INSA Summer Intership Guidance

  • Aayushi Kundalia, Big data analytics using Deep Learning Algorithms (2019)
  • Sooraj Gupta, A few Predictive Machine Learning Algorithms (2019)
  • Sahil Unagar, Deep Learning for Large Scale Image Classification Problem (2019)
  • Hitha P R, Davenport Constant and Wieferich Primes (2018)
  • Maria Jose K, Normal Order of ω(n) and Ω(n) (2018)
  • Rohit Upadhya, Image Classification Using Convolutional Neural Networks (2018)
  • Kutty Kumar, Intellectual Asset Valuation - Big Data Analytics (2018)
  • Abrar Ahmad, Image classification Using Convolutional Neural Network (2017)
  • Anjana Rajagopal, Comparison of different M estimators of Robust regression and Interactive visualization of data using R (2017)
  • Febin John Sam, Deep Network Learning using (SnLU) Smooth non-linear unit and Medical Machine Learning with Tensorflow (2017)