Debashis Das Chakladar

Debashis Das Chakladar

Research Scholar

Research Area

  • Brain-Computer Interface
  • Computational Neuroscience
  • Deep Learning
  • Machine Learning

Contact Information 9903131420


I am a research scholar at the PARIMAL lab under Dr. Partha Pratim Roy. My research areas are cognitive workload estimation using EEG, patten analysis of different diseases related to the human brain.

Internships/Research Experiences

  • 4 months internship program in IIT Kharagpur under the supervision of Dr. Debasis Samanta


  • Achieved Gold medal in MTech(CSE) from Maulana Abul Kalam Azad University of Technology, WestBengal
  • Achieved IEEE young professional award for the paper  "Study and analysis of a fast moving cursor control in a multithreaded way in brain computer interface" (CICBA -2017)


  • Chakladar, D. D., & Chakraborty, S. (2017). Study and analysis of a fast moving cursor control in a multithreaded way in brain computer interface. In International Conference on Computational Intelligence, Communications, and Business Analytics (pp. 44-56). Springer, Singapore.
  • Chakladar, D. D., & Chakraborty, S. (2018). EEG based emotion classification using “Correlation Based Subset Selection”. Biologically inspired cognitive architectures, 24, 98-106.
  • Chakladar, D. D., & Chakraborty, S. (2018). Multi-target way of cursor movement in brain computer interface using unsupervised learning. Biologically Inspired Cognitive Architectures, 25, 88-100.
  • Chakladar, D. D., & Chakraborty, S. (2019). Feature Extraction and Classification in Brain-Computer Interfacing: Future Research Issues and Challenges. In Natural Computing for Unsupervised Learning (pp. 101-131). Springer, Cham.
  • Saurav, S., Chakladar, D. D., Shaw, P., Chakraborty, S., & Kairi, A. (2019). Multi-target-Based Cursor Movement in Brain-Computer Interface Using CLIQUE Clustering. In Proceedings of International Ethical Hacking Conference 2018 (pp. 419-428). Springer, Singapore.
  • Khakon Das, Debashis Das Chakladar, Partha Pratim Roy, Atri Chatterjee, Shankar Prasad Saha, Epileptic seizure prediction by the detection of seizure waveform from the pre-ictal phase of EEG signal, Biomedical Signal Processing and Control, Elsevier, 2019 (Accepted)