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Kusum Lata

Assistant Professor, Computer Science and Engineering (CSE)

Kusumlata.1@sharda.ac.in

About

Kusum Lata is currently working as an Assistant Professor in the Department of Computer Science & Engineering in School of Engineering & Technology, Sharda University. She has completed her Ph.D. in the Natural Language processing area in CSE department of NIT Hamirpur (H.P).  She is an IEEE member of IEEE, Delhi Section. Her research area is Natural language processing.

Experience
  • 9+ years
Qualification
  • Ph.D.  (NIT Hamirpur)
  • M.Tech (J.C. Bose University of Science and Technology, YMCA, formerly YMCA University of Science and Technology and YMCA Institute of Engineering)
  • B.E (Nagpur University)
     
Award & Recognition

  • Merit Certificate in Matriculation.
  • Invited as Mentor and Session Chair for workshops.
  • Reviewer of International Journal of Computational Intelligence Systems, Information Processing and Management, Springer
  • Many workshops has been attended 
     

Research

  • Kusum Lata, Pradeep Singh, Kamlesh Dutta, "A comprehensive review on feature set used for anaphora resolution”. Artificial Intelligence Review, vol 54, pp 2917–3006 (2021). SCI Indexed, Impact factor: 9.588
  • Kusum Lata, Pradeep Singh, Kamlesh Dutta, “Mention detection in coreference resolution: survey.” Applied Intelligence, DOI: 10.1007/s10489-021-02878-2. SCI Indexed, Impact factor: 5.019.
  • Kusum Lata, Soni Chaurasia and Dr. Ashutosh Dixit “Energy Efficient Routing Protocol For Dual Transmission In WHSNs” International Conference on Advanced Computing & Communication Technologies (ICACCT-2011), APIIT SD INDIA (1st International Engineering College), Panipat, 5th Nov, 2011
  • Soni Chaurasia, Kusum Lata, Rajeev Kumar,” QoS Supported Layered Communication Protocols in Wireless Sensor Network”, International Conference on Advances in Computing and Communication April 08-10, 2011 organized by NIT Hamirpur (H.P) ISBN: 978-81-920874-0-5, 8 -10 April, 2011, pp.170-173

Area of Interest

  • Natural Language processing, Deep Learning, Artificial Intelligence