Dr. TRIPTI GOEL

March 16, 2022 by Tripti Goel
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Assistant Professor

National Institute of Technology (NIT) Silchar

Department of Electronics and Communications Engineering

Silchar, Assam, 788010, India

Email: triptigoel@ece.nits.ac.in

Phone: +91-9541345413

Date of Joining: 27/06/2018

Academic Experience: 7+ years

Personal Webpage: http://ec.nits.ac.in/triptigoel/

ACADEMIC QUALIFICATIONS

  • Ph.D.:     BPS Mahila Vishwavidyalaya, Haryana, India,2017
  • M.Tech.: Chottu Ram State College of Engg., Haryana, India, 2008
  • B.Tech.:  Maharishi Dayanand University, Haryana, India, 2004

EXPERIENCE

  • June 2018- Till Date: Assistant Professor, National Institute of Technology (NIT) Silchar, Assam, 788010, India.
  • Feb 2018-June 2018: Research Scientist, National Brain Research Center, Gurugram, India
  • July 2015-Feb, 2018: Assistant Professor, National Institute of Technology (NIT) Delhi, India
  • January 2009- November 2014: Senior Lecturer, Guru Premsukh Memorial College of Engineering, Delhi

RESEARCH INTERESTS AND SPECIALIZATION

  • Medical Image Processing
  • Neuroimaging
  • Neurodegeneration
  • Machine Learning/Deep Learning
  • Optimization Problems
  • Pattern Recognition
  • Digital Signal Processing

BIOGRAPHICAL SKETCH

Tripti Goel obtained her Bachelor of Engineering (Hons) from Maharishi Dayanand University in 2004. She obtained her M.Tech in 2008 from Chhotu Ram State College of Engg., Haryana, and her Ph.D. in 2017 from BPS Mahila Vishwavidyalaya, Haryana. She joined Bhagwan Mahaveer Institute of Engineering and Technology, Haryana as a Lecturer in August 2005. After completing her M. Tech., she joined Guru Premsukh Memorial College of Engg. as a lecturer in 2009 and became a Senior Lecturer in 2012. She joined NIT, Delhi, as an Assistant Professor in July 2015. During this period, she has been an active member of various committees like DUPC, DPPC, etc. After that, she joined National Brain Research Center, Gurugram, as Research Scientist in February 2018. She joined NIT Silchar as an Assistant Professor in June 2018. Her research area includes medical image processing, deep learning, machine learning, neuroimaging, soft computing, etc.

SPONSORED PROJECT

1. SERB sponsored research project titled “Development of a deep learning-based risk prediction and diagnostic model for Alzheimer’s disease using the integration of functional and structural MRI scans”, Funding Amount: 30,00,000 INR, Start Date: 6 February 2023

 

PATENT

1. T. Goel, R. Sharma, R. Khosla, R. Murugan, “System for the early detection of Alzheimer’s disease,” German Patent, IPC: G16 50/20, no. 202023100083.5, 2023.

2. R. Khosla, K. Guha, T. Goel, R. Khosla, A. J. Borah, R. P. Chowdhury, D. Patgiri, R. Borah, “A Smart Agriculture system for farm environment monitoring and crop selection using IoT and Machine Learning,” German Patent, IPC: G06Q50/02, no. 202023100001, 2023.

PUBLICATIONS (JOURNALS/CONFERENCES)

International Journals

  1. N Jagan Mohan, R Murugan, Tripti Goel, and Parthapratim Roy, “DRFL: Federated Learning in Diabetic Retinopathy Grading Using Fundus Images”,  IEEE Transactions on Parallel and Distributed Systems, 2023.
  2. M. Tanveer, M.A. Ganaie, Iman Beheshti, Tripti Goel, Nehal Ahmad, Kuan-Ting Lai, Kaizhu Huang, Yu-Dong Zhang, Javier Del Ser, Chin-Teng Lin, Deep learning for brain age estimation: A systematic review, Information Fusion, Volume 96, 2023, https://doi.org/10.1016/j.inffus.2023.03.007.
  3. Rahul Sharma, Tripti Goel*, M Tanveer,  C.T. Lin,  R Murugan, “Deep learning based diagnosis and prognosis of Alzheimer’s disease: A comprehensive review”,  IEEE Transactions on Cognitive and Developmental Systems. 
  4. Tripti Goel; Varaprasad, S.A.; Tanveer, M.; Pilli, R. Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry. Brain Sci. 2023, 13, 267. https://doi.org/10.3390/brainsci13020267
  5. Tripti Goel, R. Sharma, M. Tanveer, P. N. Suganthan, K. Maji and R. Pilli, “Multimodal Neuroimaging based Alzheimer’s Disease Diagnosis using Evolutionary RVFL Classifier,” in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3242354.
  7. D N Kiran Pandiri, R Murugan, Tripti Goel, Nishant Sharma, Aditya Kumar Singh, Soumya Sen, Tonmoy Baruah, “POT-Net: Solanum Tuberosum (Potato) Leaves Diseases Classification using an Optimized Deep Convolutional Neural Network”, Imaging Science Journal, 2023.
  8. Shradha Verma, Tripti Goel; M Tanveer, Weiping Ding, Rahul Sharma, R Murugan, “Machine learning techniques for the diagnosis of Schizophrenia: A comprehensive review and future research directions”, Journal of Ambient Intelligence and Humanized Computing, 2023.
  9. Ananya Bhattacharjee, R Murugan, Tripti Goel, Seyedali Mirjalili, “Pulmonary nodule segmentation framework based on fine-tuned and pre-trained deep neural network”,  IEEE Transactions on Radiation and Plasma Medical Sciences, 2023
  10. Dhananjay Reddy, R Murugan, Arnab Nandi, Tripti Goel, “Classification of arrhythmia disease through electrocardiogram signals using sampling vector random forest classifier,” Multimedia Tools and Applications, 2022. (Accepted for publication on 10/12/2022).
  11. P Supriya Patro, Tripti Goel, S A VaraPrasad, M Tanveer, R Murugan, Lightweight 3D Convolutional Neural Network for Schizophrenia diagnosis using MRI Images and Ensemble Bagging Classifier”, Cognitive Computation, 2022. (Accepted for publication on 05/12/2022).
  12. Shradha Verma, Tripti Goel, M Tanveer, “Quantitative Susceptibility Mapping in Cognitive Decline: A Review of Technical Aspects and Applications,” Cognitive Computation, 2022. (Accepted for publication on 05/12/2022).
  13. N Jagan Mohan, R Murugan, Tripti Goel, M TParthapratim Roy ” An Efficient Microaneurysms Detection Approach in Retinal Fundus Images,” International Journal of Machine Learning and Cybernetics,” 2022 (Accepted for publication on 14/10/2022).
  14. R. Sharma, T. Goel, M. Tanveer, P. N. Suganthan, I. Razzak and R. Murugan, “Conv-ERVFL: Convolutional Neural Network Based Ensemble RVFL Classifier for Alzheimer’s Disease Diagnosis,” in IEEE Journal of Biomedical and Health Informatics, 2022, doi: 10.1109/JBHI.2022.3215533.
  15. M Dhanalakshmi Bhavani, R Murugan, Tripti Goel, “An Efficient Dehazing Method of Single Image using Multi-Scale Fusion Technique’, Journal of Ambient Intelligence and Humanized Computing, 2022. https://doi.org/10.1007/s12652-022-04411-w
  16. Bhavani MD, Murugan R, Goel T. Robust U-Net: Development of robust image enhancement model using modified-Net architecture. Concurrency and Computation: Practice and Experience. 2022;e7347. https://doi.org/10.1002/cpe.7347
  17. Ananya Bhattacharjee, R Murugan, Badal Soni, Tripti Goel, “Ada-GridRF: A Fast and Automated Adaptive Boost Based Grid Search Optimized Random Forest Ensemble model for Lung Cancer Detection”, Physical and Engineering Sciences in Medicine, 2022. https://doi.org/10.1007/s13246-022-01150-2
  18. Ananya Bhattacharjee, R Murugan, Tripti Goel, “A Hybrid approach for lung cancer diagnosis using optimized Random Forest classification and K-means visualization algorithm”, Health and Technology, 2022. https://doi.org/10.1007/s12553-022-00679-2
  19. Sonal Yadav, Sanjoy Das, R Murugan, Sumantra Dutta Roy, Monika Agrawal, Tripti Goel, Anurag Dutta, “Performance analysis of deep neural networks through transfer learning in retinal detachment diagnosis using fundus images”, Sādhanā, Vol. 47, (49), pp.1-13, 2022.   https://doi.org/10.1007/s12046-022-01822-5
  20. Tripti Goel, R. Murugan, Seyedali Mirjalili, Deba Kumar Chakrabartty, Multi-COVID-Net: Multi-objective optimized network for COVID-19 diagnosis from chest X-ray images, Applied Soft Computing, Volume 115, 2022, 108250.https://doi.org/10.1016/j.asoc.2021.108250
  21. Shubham Dwivedi, Tripti Goel, M. Tanveer, R Murugan, Rahul Sharma, “Multi-modal fusion based deep learning network for effective diagnosis of Alzheimer’s disease,” IEEE MultiMedia          (Early Access) 2021. https://ieeexplore.ieee.org/document/9729422
  22. N Jagan Mohan, R Murugan, Tripti Goel, Parthapratim Roy, “Fast and Robust Exudate Detection in Retinal Fundus Images using Extreme Learning Machine Auto Encoders and Modified KAZE features”, Journal of Digital Imaging, 2021. (Accepted for publication on 03/11/2021).
  23. Rahul Sharma, Tripti Goel, M Tanveer; R Murugan, “FDN-ADNet: Fuzzy LTSVM based Deep learning Network for prognosis of the Alzheimer’s Disease using the sagittal plane of MRI scans”, Applied Soft Computing Journal. Accepted on 31/10/2021.
  24. N Jagan Mohan, R Murugan, Tripti Goel, Seyedali Mirjalili, Parthapratim Roy, “A Novel Four-Step Feature Selection Technique for Diabetic Retinopathy Grading”, Physical and Engineering Sciences in Medicine,2021. DOI:10.1007/s13246-021-01073-4
  25. R Murugan, Tripti Goel, Seyedali Mirjalili, Depa Kumar Chakrabartty, “WOANet: Whale Optimized Deep Neural Network for the Classification of COVID-19 from Radiography Images” Biocybernetics and Biomedical Engineering, 2021. https://doi.org/10.1016/j.bbe.2021.10.004
  26. Ananya Bhattacharjee, R Murugan, Swanirbhar Majumder, Tripti Goel, “Neural network-based computer-aided lung cancer detection”, Research on Biomedical Engineering, 2021. https://doi.org/10.1007/s42600-021-00173-0
  27. Rahul Sharma, Tripti Goel, M. Tanveer, Shubham Dwivedi, R Murugan, “FAF-DRVFL: Fuzzy Activation function based Deep Random Vector Functional Links Network for Early Diagnosis of Alzheimer Disease”, Applied Soft Computing Journal (Accepted on 29/03/2021)
  28. D N Kiran Pandiri, R Murugan, Tripti Goel, March 18, 2021, “Indian Regions Soil Image Database (IRSID): A dataset for classification of Indian soil types “, IEEE Dataport, doi: https://dx.doi.org/10.21227/2zz3-f173.
  29. R Murugan, Tripti Goel, “E-DiCoNet: Extreme Learning Machine based classifier for Diagnosis of COVID-19 using Deep Convolutional Network”, Journal of Ambient Intelligence and Humanized Computing. (Accepted on 08/11/2020)
  30. Tripti Goel, R Murugan, Seyedali Mirjalili, Depa Kumar Chakrabartty, “Automatic Screening of COVID-19 using an Optimized Generative Adversarial Network”, Springer Cognitive Computation (Accepted for publication on 21/10/2020)
  31. Tripti Goel, R Murugan, Seyedali Mirjalili, Deba Kumar Chakrabartty, “OptCoNet: An Optimized Convolutional Neural Network for an Automatic Diagnosis of COVID-19″, Applied Intelligence (Accepted for publication on 20/08/2020).
  32. Ankita Sharma, Deepika Shukla, Tripti Goel, Pravat Kumar Mandal, BHARAT: An Integrated Big Data Analytic Model for Early Diagnostic Biomarker of Alzheimer’s Disease, Frontiers in Neurology, vol. 10 9. 8 Feb. 2019, doi:10.3389/fneur.2019.00009
  33. N. Jagan Mohan, R. Murugan, Tripti Goel. (2020), “Investigations of Diabetic Retinopathy Algorithms in Retinal Fundus Images”, International Journal of Image Processing and Pattern Recognition, Vol.6(1): pp. 14–26.
  34. Goel, Tripti, and R. Murugan. (2020), “Deep Convolutional-Optimized Kernel Extreme Learning Machine Based Classifier for Face Recognition.” Computers & Electrical Engineering 85 106640.https://doi.org/10.1016/j.compeleceng.2020.106640
  35. Goel T, Nehra V, and Vishwakarma V P, An Adaptive Non-symmetric Fuzzy Activation Function based Extreme Learning Machines for Face Recognition. Arab J Sci Eng, vol. 42, no. 2, pp. 805-816, 2017.
  36. Goel T, Nehra V, and Vishwakarma V P, An Efficient Classification based on Genetically Optimized Hybrid PCA-Kernel ELM Learning. International Journal of Applied Pattern Recognition, vol. 3, no. 3, pp. 241-258, 2016.
  37. Goel T, Nehra V, and Vishwakarma V P, Pose Normalization based on Kernel ELM Regression for Face Recognition. International Journal of Image, Graphics and Signal Processing (IJIGSP), vol.9, no.5, pp. 68-75, 2017. DOI: 10.5815/ijigsp.2017.05.07.
  38. Goel T, Nehra V, and Vishwakarma V P, Comparative Analysis of various Illumination Normalization Techniques for Face Recognition. International Journal of Computer Applications, vol. 28, no. 9, pp. 1-7, 2011.
  39. Goel T, Nehra V, and Vishwakarma V P, An Efficient Hybrid DWT- Fuzzy DCT Based Illumination Normalization for Face Recognition. Multimedia Tools and Applications, Springer.

National Journals

  1. Dataset: D N Kiran Pandiri, R Murugan, Tripti Goel, March 18, 2021, “Indian Regions Soil Image Database (IRSID): A dataset for classification of Indian soil types “, IEEE Dataport, doi: https://dx.doi.org/10.21227/2zz3-f173.

International Conferences

  1. Maji, K., Sharma, R., Verma, S., Goel, T. (2023). RVFL Classifier Based Ensemble Deep Learning for Early Diagnosis of Alzheimer’s Disease. In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Lecture Notes in Computer Science, vol 13625. Springer, Cham. https://doi.org/10.1007/978-3-031-30111-7_52
  2. Shradha Verma, Tripti Goel, R Murugan“Discrete Cosine Transform based Laplacian Phase Unwrapping for Phase Image application”, 19th IEEE India Council International Conference-INDICON 2022 (Accepted on 09/09/2022).
  3. Krishanu Maji , Rahul Sharma, Shradha Verma and Tripti Goel, “RVFL Classifier based Ensemble Deep Learning for Early Diagnosis of Alzheimer’s Disease”, The 29th International Conference on Neural Information Processing (ICONIP 2022) (Accepted on 14/10/2022)
  4. Kiran Venneti, H Kashyap, R Murugan, Jagan Mohan, Tripti Goel, “AMDNet: Age-Related Macular Degeneration Diagnosis Through Retinal Fundus Images Using Lightweight Convolutional Neural Network”, IEEE Silchar Subsection Conference-SLCON-2022 (Accepted for Oral Presentation on 07/09/2022).
  5. A. Bhattacharjee, R. Murugan, T. Goel and Shankar K, “A powerful Transfer learning technique for multiclass classification of lung cancer CT images” 8th International Conference on Engineering and Emerging Technologies (ICEET 2022)” IEEE Malaysia ComsocVTS, has been accepted for an oral presentation on 24/08/2022.
  6. N Jagan Mohan, R Murugan, Trpti Goel, Parthapratim Roy, “ViT-DR: Vision Transformers in Diabetic Retinopathy Grading Using Fundus Images” for The IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 2022. (Accepted on 05/05/2022).
  7. Rahul Sharma, R Murugan, Trpti Goel , “An Optimized Deep Learning Network for Prognosis of Alzheimer’s Disease Using Structural Magnetic Resonance Imaging” for The IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 2022. (Accepted on 05/05/2022)
  8. N Jagan Mohan, R Murugan, Trpti Goel, “DR-FL: A Novel Diabetic Retinopathy Grading with Federated Learning Using Fundus Images” The North-Eastern Research Conclave  (NERC 2022).(Accepted on 27/04/2022).
  9. D N Kiran Pandiri, R Murugan, Tripti Goel, “ODNet: Optimized Deep Convolutional Neural Network for Classification of Solanum Tuberosum Leaves Diseases”, The IEEE Region 10 Symposium(TENSYMP) 2022 (Accepted on 12/04/2022).
  10. V. N. Medhi, K. M. Basumatary, R. Murugan and T. Goel, “An Early Detection of Parkinson’s Disease from Geometric Drawings,” 2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP), 2022, pp. 1-5. https://doi.org/10.1109/AISP53593.2022.9760641
  11. A. Bhattacharjee, R. Murugan, T. Goel and B. Soni, “Semantic segmentation of lungs using a modified U-Net architecture through limited Computed Tomography images,” 2021 Advanced Communication Technologies and Signal Processing (ACTS), 2021, pp. 1-6. https://doi.org/10.1109/ACTS53447.2021.9708190
  12. S. Dwivedi, T. Goel, R. Sharma and R. Murugan, “Structural MRI based Alzheimer’s Disease prognosis using 3D Convolutional Neural Network and Support Vector Machine,” 2021 Advanced Communication Technologies and Signal Processing (ACTS), 2021, pp. 1-4. https://doi.org/10.1109/ACTS53447.2021.9708107
  13. Vijaya Yaduvanshi, Murugan, Tripti Goel, “Oral cancer detection using modified local binary pattern”, 7th International Conference on Nanoelectronics, Circuits & Communication Systems, 2021 (Accepted for publication on 12/11/2021)
  14. S. Yadav, S. Das, R. Murugan and T. Goel, “RD-Light-Net: Light Weight Network for Retinal Detachment Classification through Fundus Images,” 2021 Sixth International Conference on Image Information Processing (ICIIP), 2021, pp. 369-374. https://doi.org/10.1109/ICIIP53038.2021.9702547
  15. Sayandeep Roy, Yash Singh, Utsab Biswas, Devendra Singh Gurjar and Tripti Goel, “Machine Learning in Smart Transportation Systems for Mode Detection” Accepted in INDICON-2021
  16. Rahul Sharma, Tripti Goel, R Murugan, “Prediction of Alzheimer’s Disease using Machine Learning Algorithm” International Conference on Computational Intelligence & Sustainable Technologies (ICoCIST-2021) Presented on 29 October, 2021
  17. Sonal Yadav, Sanjay Das, R Murugan, Tripti Goel, “RD-Light-Net: Light Weight Network for Retinal Detachment Classification Through Fundus Images” Sixth IEEE International Conference on Image Information Processing (ICIIP -2021). (Accepted on 26/10/2021).
  18. S. Dhanunjay Reddy, R Murugan, Arnab Nandi and Tripti Goel, “Arrhythmia detection and classification using two stage median filter through dynamic features of ECG signals”, International Conference on Communication, Devices and Computing (Accepted on 13/07/2021).
  19. Mohan, N. Jagan, R. Murugan, Tripti Goel, and Parthapratim Roy. “Exudate Localization in Retinal Fundus Images Using Modified Speeded Up Robust Features Algorithm.” In 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), pp. 367-371. IEEE, 2021.
  20. Jagan Mohan N., Murugan R., Goel T., Roy P. (2020) An Improved Accuracy Rate in Microaneurysms Detection in Retinal Fundus Images Using Non-local Mean Filter. In: Bhattacharjee A., Borgohain S., Soni B., Verma G., Gao XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1240. Springer, Singapore. https://doi.org/10.1007/978-981-15-6315-7_15
  21. Subham Chakraborty, R Murugan, TriptiGoel, “Classification of Tea Leaf Diseases using Convolutional Neural Network” 26th annual International Conference on Advanced Computing and Communications (Aceepted on 17/10/2020).
  22. Jagan Mohan, R Murugan, TriptiGoel, P P Roy “An Optic Disc Segmentation in Fundus Images Using Operator Splitting Approach” IEEE International Conference on Advanced Communication Technologies and Signal Processing (Aceepted on 21/10/2020).
  23. Rahul Sharma, Tripti Goel, R Murugan, “An Optimized Deep Learning Network for Prognosis of Alzheimer’s Disease Using Structural Magnetic Resonance Imaging”, IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES2020) LANGKAWI, MALAYSIA (Accepted on 18/11/2020).
  24. Jagan Mohan, R Murugan, Tripti Goel,”Exudate Localization in Retinal Fundus Images Using Modified Speeded Up Robust Features Algorithm”, IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES2020) LANGKAWI, MALAYSIA (Accepted on 20/11/2020).
  25. Jagan Mohan, R.Murugan, Tripti Goel, (2019), Investigations of diabetic retinopathy algorithms in retinal fundus images, proceedings of International Conference In Recent Trends on Electronics & Computer Science, NIT Silchar.
  26. Jagan Mohan N., Murugan R., Goel T., Roy P. (2020), “An Improved Accuracy Rate in Microaneurysms Detection in Retinal Fundus Images Using Non-local Mean Filter. In: Bhattacharjee A., Borgohain S., Soni B., Verma G., Gao XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1240. Springer, Singapore. https://doi.org/10.1007/978-981-15-6315-7_15
  27. Goel, Tripti, and R. Murugan. “A non-iterative fuzzy neural classifier for face recognition.” Eleventh International Conference on Graphics and Image Processing (ICGIP 2019). Vol. 11373. International Society for Optics and Photonics, 2020. https://doi.org/10.1117/12.2557232
  28. Tripti Goel, Vijay Nehra and Virendra P.Vishwakarma . : Illumination Normalization using Down-Scaling of Low-Frequency DCT Coefficients in DWT Domain for Face Recognition. Published in: 2013 Sixth International Conference on Contemporary Computing (IC3), vol. 3, 2013, pp. 295-300.
  29. Tripti Goel, Vijay Nehra and Virendra P.Vishwakarma .: Rescaling of Low-Frequency DCT Coefficients with Kernel PCA for Illumination Invariant Face Recognition” Published in: Advance Computing Conference (IACC), 2013 IEEE International Date of Conference: 22-23 Feb. 2013, pp. 1177-1182.
  30. Tripti Goel: Polarization Division multiplexing using Photonic Crystal Fiber. International Conference WECON on 18-19 October, 2008.

National Conferences

  1. Tripti Goel, Vijay Nehra and Virendra P.Vishwakarma . : Illumination Normalization Using Multiscale Approach and Nonlinear Classifier for Face Recognition. National Conference on Machine Intelligence and Research Advancement, Date of Conference: 19th – 20th March, 2015, at BPSMV, Khanpur Kalan, Haryana.
  2. Tripti Goel: Polarization Mode Dispersion in High-Speed Optical Communication System. in National Conference NCTET on 26-26 May, 2008.
  3. Tripti Goel: Polarization Mode dispersion in polarization Division Multiplexed Systems by Using Polarization Maintaining Photonic Crystal Fibers. in National Conference NCMI on 22-23 August 2008.

 BOOKS/CHAPTERS

  1. Jagan Mohan Nagula, R Murugan, Tripti Goel, “Role of Machine and Deep Learning Techniques in Diabetic Retinopathy Detection”, Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence, IGI Global, pp.32-46, 2022,
  2. Mohan, N. Jagan, R. Murugan, and Tripti Goel. “Machine Learning Algorithms for Hypertensive Retinopathy Detection through Retinal Fundus Images.” In Computer Vision and Recognition Systems, pp. 39-67. Apple Academic Press, 2022.
  3. N Jagan Mohan, R Murugan, Tripti Goel, “Deep Learning for Diabetic retinopathy Detection: Challenges and Opportunities”, Next Generation Healthcare Informatics, vol 1039, 2022, Springer, Singapore. https://doi.org/10.1007/978-981-19-2416-3_12
  4. Yaduvanshi V., Murugan R., Goel T. (2021) An Automatic Classification Methods in Oral Cancer Detection. In: Patgiri R., Biswas A., Roy P. (eds) Health Informatics: A Computational Perspective in Healthcare. Studies in Computational Intelligence, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-15-9735-0_8.
  5. N Jagan Mohan, R Murugan, Tripti Goel, 2020 “Machine learning algorithms for hypertensive retinopathy detection through retinal fundus images” in Research Innovations and Trends on Computer Vision and Recognition Systems, published by CRC press.
  6. Shubham Dwivedi, Devendra Singh Gurjar, Prabina Pattanayak, and Tripti Goel, “V2X Communications: Recent Advancements and Performance Analysis” 5G and Beyond Wireless Systems, Springer. 

PROFESSIONAL MEMBERSHIPS

  • Fellow, IEEE
  • Signal Processing Society, IEEE
  • Drishti CPS Foundation, IIT Indore

AWARDS & RECOGNITIONS

  1. Senior Member, IEEE.
  2. Received SERB-CRG funding for the project “Development of the deep learning-based risk prediction and diagnostic model for Alzheimer’s Disease using the integration of functional and structural MRI Scans”.
  3. Received best paper award at 2nd National Conference on Machine Intelligence and Research Advancement, Date of Conference: 19th – 20th March 2015, at BPSMV, Khanpur Kalan, Haryana.
  4. Received honors degree in M. Tech. from CRSCE, Haryana

ADMINISTRATIVE RESPONSIBILITIES

  • Associate Warden of Girls Hostel (GH-1)
  • Departmental Single Point of Contact-IIC-3.0
  •  Departmental B.Tech. Project Coordinator
  •  Lab in charge of Bio-Medical Imaging Lab
  •  Lab in Charge of Instrumentation and Measurement Lab
  •  Expert Member of DUPC Committee of CSE Department
  • Committee member of the DUPC Committee
  • Committee member of departmental outreach activities

Ph.D. Scholars Guided

    Guiding (Full-Time)

  1. Mr. N. Jagan Mohan (Co-Guide)
  2. Mr. Rahul Sharma
  3. Ms. Shradha Verma
  4. Mr. Raveendra Pilli

Guiding (Part-Time)

  1. Mr. Ragipati Karthik
  2. Mr. S.S. Vara Prasad
  3. Mr. Ujwal Ramekar
  4. M. Baciavathi
  5. Swetha Annangi

M.Tech. Scholars Guided

  1. Ms. Supriya Patro (2020-22 Department of Electronics and Communication, NIT Silchar) Association of abnormalities in MRI and fMRI in Schizophrenia patients
  2. Mr. Shubham Dwivedi: (2019-21 Department of Electronics and Communication, NIT Silchar) “Multi-modality image fusion”.
  3. Mr. Avinandam Das(2018-2020 Department of Electronics and Communication, NIT Silchar). “DF relaying using SWIPT”.

Guiding

  1. Mr. Kshitiz Ananad (2022-24 Department of Electronics and Communication, NIT Silchar)
  2. Mr. Krishanu Maji (2021-23 Department of Electronics and Communication, NIT Silchar)

B.Tech. Projects

  1. Debraj Purkayastha, Manzil Hoque, Golla Uday sai theja, Medikonda Aravind Ramoji, “Identification of the early stage of Alzheimer’s disease using clinical assessment, Structural MRI and Resting-State fMRI”
  2. Deep Learning Approach to Identify Covid-19 Using CT Image.
  3. Credit Card Fraud Detection

Conference Organized

1. IEEE sponsored International Conference on Signal Processing and Computer Vision (SIPCOV-2023) during 30-31 March 2023, technically sponsored by SERB.

 

Workshops Organized

  1. “Hands-on Training and Workshop on Computational Biology and Bio-Medical Informatics” during 25-31, July 2022 in Physical Mode at NIT Silchar, sponsored by SERB-Karyashala
  2. “Prototype/Process Design and Development” from 14th to 18th February 2022, organized by the IIC 4.0 in association with the Department of Electronics and Communication Engineering & Department of Management Studies, NIT Silchar, Coordinator
  3. Machine Intelligence in Biomedical and Health Informatics-2020, from 20 August 2020 to 24 August 2020, organized by the Department of Electronics and Communication Engineering, NIT Silchar
  4. Optimization and Intelligence in Engineering Applications (IEEE OIEA-2021) from 26/07/2021 to 30/07/2021 ” organized by the Department of Electronics and Communication Engineering, NIT Silchar
  5. Computer Vision and Pattern Recognition using Machine Learning from 29 July 2019 to 26 July 2019 organized by the Department of Electronics and Communication Engineering, NIT Silchar