COMPUTER APPLICATION

Programmes Offered:

1. Doctor of Philosophy (Ph.D.)

Duration of the Programme  3 Years (Min) to 5 Years (Max)

Click here to download the syllabus for MSSVRAT

Admission Procedure: Merit Basis

2. M.Sc. in Information Technology (Machine Learning and Big Data Analytics)

Duration of the Programme:  2 Years (Multiple exit as per NEP 2020)

Admission Procedure: Merit Basis

3. B.Sc. in Information Technology (Digital Forensics and Cyber Security)/(Data Science and Aartificial Intelligence)

Duration of the Programme:  4 Years (Multiple exit as per NEP 2020)

Admission Procedure: Merit Basis

4. Bachelor of Computer Application (BCA)

Duration of the Programme:  4 Years (Multiple exit as per NEP 2020)

Admission Procedure: Merit Basis

Conference Presentations

1. Machine Learning based Extraction of Earthquake Precursors from GPS TEC data, September 30-October 3, 2024, International Conference on Mathematical Modeling in Physical Sciences, Kalamata, Greece.
2. Machine learning-based approach for detecting earthquake precursor from ionospheric time series data at anomaly crest station, MedGU-23 organized by Istanbul Technical University in Istanbul, Turkey during 27 to 30 November, 2023 ( Accepted for publication in Springer ASTI )
3. Prediction of Ionospheric TEC based on Ensemble Learning Method, August 28-31, 2023, International Conference on Mathematical Modeling in Physical Sciences, Belgrade, Serbia.
4. Prediction of Ionospheric Total Electron Content (TEC) based on Empirical Mode Decomposition (EMD) and Long Short-Term Memory (LSTM) Neural Network, 11-12 January 2022, First Indian Space Weather Conference (ISWC-2022), Physical Research Laboratory, Ahmedabad, India.
5. Ionospheric response to solar and interplanetary disturbances,11-12 January 2022, First Indian Space Weather Conference (ISWC-2022), Physical Research Laboratory, Ahmedabad, India.
6. Short Term Prediction of Ionospheric Total Electron Content (TEC) based on Solar and Geomagnetic Data, 30-31 Aug 2021, National Conference on Recent Trends in Academic Research, Council of Industrial Innovation and Research (CIIR), Noida, Uttar Pradesh, India
7. Effect of solar phenomena to the earth's atmosphere, National Conference on Emerging Trends in Physics, 16 June 2021, Tezpur University, Assam
8. Prediction of ionospheric total election content using deep learning approach, International Conference on Emerging Areas in Science and Technology, 01-02 June 2021, RGU, Assam
9. Use of high performance computing for prediction of cyclonic tracks over bay of bengal and resultant precipitation over northeastern India, IECEIC, 30-31 Jan 2019, SCSVM, Tamil Nadu.
10. The use of NARX Neural Networks to predict the Vertical Total Electron Content over Guwahati, National Seminar on Advances in Electronics and Allied Science & Technology, 4-5 Nov 2016, Gauhati University, Assam, India
11. Implementation of Scaly Neural Network for Extraction of Earthquake Precursor Using DTW and Fuzzy C-Mean Algorithm, International Conference on Emerging trends in Electronics, Electrical and Computing Technologies, 18-19 Oct 2014, India International Centre, New Delhi, India

Journals

1. Nath S, Chetia B, Kalita S. (2022) Ionospheric TEC Prediction using Hybrid Method based on Ensemble Empirical Mode Decomposition (EEMD) and Long Short-Term Memory (LSTM) Deep Learning Model over India, Advances in Space Research, Elsevier, ISSN 0273-1177, https://doi.org/10.1016/j.asr.2022.10.067.
2. Kalita S, Chetia B. (2020) A Novel Approach for Ionospheric Total Electron Content Earthquake Precursor and Epicenter Detection for Low-Latitude, International Journal of Engineering and Geosciences, ISSN:2548-0960, https://doi.org/10.26833/ijeg.614856
3. Kalita S, Chetia B. (2019) Use of High Performance Computing for Prediction of Cyclonic Tracks over Bay of Bengal and Resultant Precipitation over the Northeastern India, IEEE – ICECEIC, 978-1-7281-0174-3
4. Kalita S, Chetia B, Devi M, Barbara A. K (2017) Prediction of Total Electron Content using Nonlinear Autoregressive Models with eXogenous input Recurrent Neural Network, Global Journal of Computer Science and Technology, Vol 17, No 4-H (2017): ISSN 0975-4172
5. Chetia Bornali, Devi Minakshi, Kalita Santanu, Barbara Ananda K.(2017) Magnetic Storm Time effect on upper and lower atmosphere: An analysis through GPS and remote sensing observation over Guwahati,  Indian Journal of Radio & Space Physics, ISSN:0367-8393, Vol 46,  pp 120-130
6. Kalita S, Chetia B. (2015) Design of artificial neural network for extraction of earthquake precursor from GPS total electron content(TEC) data, Asian Journal of Spatial Science, Dibrugarh University, ISSN 2347-7636  pp. 38-42
7. Kalita S, Chetia B, Devi M, Barbara A. K. (2016) Prediction of Geomagnetic Storm using Multi-layer feed-forward Neural Networks, International Journal of Electronics and Applied Research, ISSN:2395- 0064, 2016, vol. 3, Issue 1, PP 84-91
8. Chetia Bornali, Kalita Santanu, Devi Minakshi, Ray Kamla Prsan, Barbara Ananda Kumar. (2016) Measured and Computed Total Electron Content over Guwahati: Observed Through Satellite and Model Computation. Int. J. of Adv. Res. 4 (Sep). 1724-1735,ISSN 2320-5407
9. Kalita S. (2015) Monitoring the TEC variation using pattern matching method during earthquakes as determined from ground based TEC measurement and satellite data, International Journal of Scientific and Research Publications, ISSN: 2250-3153 Volume 5, Issue 6
10. Kalita S, Chetia B. (2014) Implementation of Scaly Neural Network for Extraction of Earthquake Precursor Using DTW and Fuzzy C-Mean Algorithm, Proc. DIGNATE: ETEECT,,ISBN 978-93-5196-068-3, pp 66-70

1. Surajit Nath (Awarded)
2. Sidhartha Kumar Saikia
3. Deep Jyoti Borah
4. Mridupaban Bora
5. Kularanjan Hazarika
6. Dipanita Phukan
7. Monika Medhi

1.One Week Hands-on Workshop on Full Stack Web Development, 29th May to 04 June 2023

2. Hands-on Workshop on Networking and Communication.

3. Seminar on “Confusion Matrix in Classification Problems” was organized on 07th December, 2022.

4. Academic talk on “Sampling Methods- Its Key Role in Scientific Research” was organized on 28th November, 2022.

5. Seminar on “An Insight into Deepfake Technology” was organized on 17th November, 2022.

6. Patent No: 1

Patent Application ID and Date of Grant: 202231009348 A dated: 11.03.2022

Publication Number 10/2022

Title of Invention: An IOT based smart gas monitoring and controlling system

Inventor: Mr. Surajit Nath

7. Patent No: 2

Patent Application ID and Date: Application No: 202321053974 dtd 10/08/2023

Title of Invention: Intelligent Decision Support System for Business Management Using AI and Machine Learning

Inventor: Dr. Santanu Kalita

3. Patent No: 3

Patent Design number (UK): 6382736        Grant date: 08 October 2024

Title of Invention: A device for providing Cybersecurity for Secure Data Transmission using AI and ML Integration

Inventor: Dr. Santanu Kalita

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