Dr. Aparajita Dutta

Assistant Professor – Grade II
Email: aparajita.dutta[at]cse.nits.ac.in
Date of Joining: 18.12.2023
Academic Experience: 02+
Google Scholar: Click Here









Academic Qualifications

  • Ph.D. from IIT Guwahati
  • M.Tech  from Jadavpur University
  • B.Tech from NIT Silchar


Area of Interest

  • Machine Learning
  • Deep Learning
  • Computational Biology
  • Natural Language Processing
  • Deep Reinforcement Learning


Short Biographical Sketch

Dr. Aparajita Dutta is currently working as an Assistant Professor in the Department of Computer Science and Engineering at National Institute of Technology (NIT) Silchar Assam. Prior to this, she was an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Information Technology (IIIT) Guwahati. She completed her PhD at Indian Institute of Technology (IIT) Guwahati in the area of Computational Biology. Her PhD thesis is titled “Neural Network Models for Analyzing the Splicing Cell Variable from Genome Sequences”. She has collaborated with Oslo University Hospital, Norway in the analysis of differentially expressed mRNA in Glioblastoma cell lines. She has an industry experience of 1.5 years working as a Software Developer and Data Scientist. She has also worked at NIT Nagaland for one year, where she was the course instructor for C and Graph Theory courses.


 Teaching at NIT Silchar

  • Signals and Data Communication (Undergraduate course) [current]
  • Advanced Database Management System (Postgraduate course) [current]
  • Programming Lab (Undergraduate course) [current]


Previous Teaching Experience

  • Machine Learning (IIIT Guwahati)
  • Machine Learning Lab (IIIT Guwahati)
  • Artificial Intelligence (IIIT Guwahati)
  • Artificial Intelligence Lab (IIIT Guwahati)
  • Data Structures Lab (IIIT Guwahati)
  • Computer Organization (IIIT Guwahati)
  • Graph Theory (NIT Nagaland)
  • Introduction to Programming (NIT Nagaland)



  • Invited talk on Hands-on Training on Computational Intelligence for Health Informatics and Wearable Device Data Analysis for High-End Workshops organized under the Accelerated Vigyaan Karyashala scheme of “Science and Engineering Research Board (SERB) at NIT Silchar [24-30 Jul 2023].”
  • Session Chair for the technical session on Artificial Intelligence in IEEE GCON-2023 [23-25 Jun, 2023]
  • Reviewer in Scientific Reports (Nature), Computers in Biology and Medicine, Computational and Structural Biotechnology, Information Sciences, Heliyon (Elsevier), Current Bioinformatics.
  • Invited talk on Scope and demand of AI/ML organized under the Student Induction Program of AICTE at Regional Institute of Science and Technology (RIST), Meghalaya [19 Sep 2022].
  • Hands-on sessions on Deep Learning in NLP for Connected Devices for High-End Workshops organized under the Accelerated Vigyaan Karyashala scheme of the Science and Engineering Research Board (SERB) [20-26 Jul, 2022].
  • Invited talk on Deep Learning for NLP at Assam Engineering College, Guwahati [30 Jun,2022].
  • Online training on Basics of C and C++ Programming Language for Students organized under the Strengthening Component of DBT-STAR College Scheme by the Dept. of Biotechnology (DBT), Ministry of Science and Technology, Govt. of India [26 Jan 2021].
  • Hands-on-session in the Short-Term Course on Deep Learning for Natural Language Processing conducted under the Technical Education Quality Improvement Programme (TEQIP) sponsored by MHRD, Govt. of India [18-22 Nov 2019].

Research Grant

  • VRITIKA, SERB [AV/VRI/2022/0349]: Interpretable Machine Learning towards Precision Medicine [INR 1.5 Lacs], 2023
  • TIH, IIT Bhilai (under TSP scheme): Leveraging AI/ML for Customized Credit Assessment of the Bodo Tribe in the Bodoland Territorial Region [INR 16.5 Lacs], 2023-25


  • Rimpa Deka (M.Tech.), Thesis Title: Out-of-domain Detection Using Natural Language Processing (Completed at IIIT Guwahati in April 2023)
  • Parismita Pathak (M.Tech.), Thesis Title: Identification of Polyadenylation Signals in Genomic Sequences (Completed at IIIT Guwahati in April 2023)
  • Naman Singh Nayal (B.Tech.), Project Title: A Study on Synthetic Data Generation (Completed at IIIT Guwahati in April 2023)
  • Sai Tharun (B.Tech.), Project Title: Movies Recommendation System using Cosine Similarity (Completed at IIIT Guwahati in April 2023)
  • Uma Kadam (B.Tech.), Project Title: Prediction of Lysine Sumoylation Sites (Completed at IIIT Guwahati in December 2023)
  • Palash Pratim Dutta (Intern), Internship Title: Improved Out-of-domain Detection in Dialogue Systems using Distributed Representations (Completed at IIIT Guwahati in February 2023)



(J:Journal, C: Conference, P: Poster)

  • J4. S Lier, I Rein, S Lund, A L ̊ang, E L ̊ang, N Meyer, A Dutta, S Anand, G Nesse, R Johansen, A Klungland, J Rinholm, S Bøe, A Anand, S Pollard, M Lerdrup, D Pandey, P10.12.A CDK12/CDK13 inhibition disrupts a transcriptional program critical for glioblastoma survival, Neuro Oncology, Volume 24, Issue Supplement 2, September 2022, Page ii51.
  • J3. A Dutta, K Singh, and A Anand. Visualizing the splicing of non-canonical introns through recurrent neural networks. Journal of Bioinformatics and Computational Biology19(04), 2150014.
  • J2. A Dutta, A Dalmia, R. Athul, K Singh, and A Anand. (2020). Using the Chou’s 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks. Computers in Biology and Medicine116, 103558.
  • J1. A Dutta, T Dubey, K Singh, and A Anand.(2018). SpliceVec: distributed feature representations for splice junction prediction. Computational biology and chemistry74, 434-441.
  • C5. R Deka, P Dutta, and A Dutta. (2023, June). Distributed Feature Representations for Out-of-domain Detection in Dialogue Systems. In 2023 IEEE Guwahati Subsection Conference (GCON) (pp. 1-6). IEEE.
  • C4. A Mondal, A Dutta, and S Biswas. (2023, June). Dueling-DQN Based Spectrum Sharing Between MIMO Radar and Cellular Networks. In 2023 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit) (pp. 1-6). IEEE.
  • C3. A Dutta, K Singh, and A Anand. (2022, December). Identification of Splice Junctions Across Species Using BLSTM Model. In Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics (pp. 1-6).
  • C2. A Dutta and A Anand. Neural network models for analyzing the splicing cell variable from genome sequences. EMBO Symposium “Regulatory epigenomics: From large data to useful models”, 2019, Chennai, India.
  • C1. A Dutta, T Dubey, K Singh, and A Anand. “SpliceVec: distributed feature representations for splice junction prediction.” APBC Japan 2018.
  • P1. G Choudhary , N Thakur , O Sharma , S Sinha , A Dutta and R Sehgal. “Advancing Radioactive Source Detection with Machine Learning using Plastic Scintillator Detector.” DAE Symposium on Nuclear Physics December 2023.