Tanistha Nayak

Room No. - ,
Department of IST-ETC

+91-7978738696

tanisthanist213@gmail.com

She holds the position of Assistant Professor at the Department of IST. He has 5 years of teaching and research experience in the area of Computer Science and Information Technology. She Completed her M Tech in Computer Science Engineering ( Specialization Information Communication Technology)in 2015 from VSSUT BURLA. she also qualified the National Eligibility Test (NET) for Lectureship conducted by UGC in 2018. Her M Tech thesis work was On Detection of Breast Cancer using Evolutionary Neural Network.  She is currently pursuing her PhD in Sambalpur University. Her current research interests are Artificial Neural Network, Machine Learning.

Selected Publications

  • Group
  • Research
  • Publications
  • Teachings

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  1. Dash T, Nayak T, Swain RR (2015b) Controlling wall following robot navigation based on gravitational search and feed forward neural network. In: Proceedings of the 2nd international conference on perception and machine intelligence, ACM, pp 196–200.
  2. Dash and T. Nayak, “A java based tool for basic image processing and edge detection,” Journal of Global Research in Computer Science, vol. 3 no. 5, pp.57-60, 2012.
  3. Dash, T. Nayak, and S. Chattopadhyay, “Handwritten signature verification (offline) using neural network approaches: A comparative study,” International Journal of Computer Applications, vol. 57 no. 7, pp. 33-41, 2012.
  4. Dash, T .Nayak, and S. Chattopadhyay, “Offline handwritten signature verification using associative memory net,” International Journal Advanced Research in Computer Engineering & Technology, vol.1 no. 4, pp. 370-374, 2012.
  5. Dash, S. Chattopadhyay, and T. Nayak, “Handwritten signature verification using adaptive resonance theory type-2 (ART-2) Net”. Journal of Global Research in Computer Science, vol. 3 no. 8, pp. 21-25, 2012.
  6. Dash, T., Mishra, G., and Nayak, T. 2012. A Novel Approach for Intelligent Robot Path Planning. In: proc. of National Conference on Artificial Intelligence, Robotics and Embedded Systems (AIRES) – 2012, Visakhapatnam (June, 2012), pp. 388–391.
  7. Dash, T., Sahu, S.R., Nayak, T., and Mishra, G. 2014. Neural Network Approach to Control Wall-Following Robot Navigation. in proc: IEEE International Conference on Advanced Communication, Control and Computing Technologies (ICACCCT-2014), Tamilnadu, India; pp. 1072—1076.
  8. Nayak, T.Dash, D.C Rao, P.K Sahu, “Evolutionary Neural Networks versus Adaptive Resonance Theory Net for Breast Cancer Diagnosis,” ICIA-16: Proceedings of the International Conference on Informatics and AnalyticsAugust 2016 Article No.: 97Pages 1–6https://doi.org/10.1145/2980258.2980458
  9. Nayak, T. Dash, A Comparative Study on Quantum Pushdown Automata, Turing Machine and Quantum Turing Machine, International Journal of Computer Science and Information Technologies, Vol. 3(1), 2012, 2932-2935.
  10. Tanistha Nayak et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (1) , 2012, 2932 – 2935, ISSN- 0975-9646
  11. Nayak, D.C Rao, M.R Kabat, “Neighbor Selection in Peer-to-Peer Computing using Multi-Layer Perceptron” in 1st International Conference on Next Generation Computing Technologies (NGCT), Pages-244-250.
  12. Nayak, G. Mishra, “A Novel Approach for Intelligence Robot Planning” in  proc. of National Conference on Artificial Intelligence, Robotics and Embedded Systems (AIRES) – 2012, Visakhapatnam (June, 2012), pp. 388-391

Teaching :

UG Level

  1. Discrete Mathematics
  2. Numerical Method
  3. Computer Network
  4. Database System
  5. Data Structure.

PG Level

  1. Engineering Mathematics
  2. Wireless Sensor Network
  3. Mobile Communication