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Faculty

Dr. Indrajeet Kumar

Designation: Associate Professor
Extn:
Email: indrajeet.kumar@bgu.ac.in
Area: Computer Science & Engineering

Brief Profile

Dr. Indrajeet Kumar is currently serving as an Associate Professor in the School of Applied Science at Birla Global University. He has earned his Ph.D. degree from Uttarakhand Technical University, Dehradun in March 2019, obtained his M.Tech. (Computer Engineering) degree from YMCA University of Science & Technology, Faridabad in 2013 and B. E Degree in Computer Science and Engineering from Sant Longowal Institute of Engineering & Technology, Longowal in 2009. His research interests include Biomedical Image Processing, computer vision, pattern recognition, Machine Learning and Deep Learning. Under his esteemed supervision, 2 Ph.D degree is awarded and 2 is ongoing. He has authored and co-authored several publications in refereed SCI/SCIE/Scopus indexed journals and has many international IEEE, Springer Nature peer reviewed conferences. His papers got many citations with h-index of 14 and i-10 index of 19. He is a reviewer for many national and international peer reviewed journals and member of technical program committee for many national and international conferences. He is having a healthy experience of teaching and research and an active member of professional societies like IEEE, ISTE and ACM. Dr. Kumar is a self-motivated and self-driven personality and has taken several initiatives for the advancement of research and academic development.

  • Educational Qualifications

    Ph. D.

    Uttarakhand Technical University, Dehradun, India

    M.Tech

    YMCA University of Science & Technology, Faridabad, India

    B.Tech

    Sant Longowal Institute of Engineering & Technology, Longowal, India

  • Academic Experience
    • Working as an Associate Professor from 15th March 2024 to 12 Aug, 2024 at Graphic Era Hill University, Dehradun, Uttarakhand. India.
    • Working as an Assistant Professor from 22nd June 2019 to 14th March 2024 at Graphic Era Hill University, Dehradun, Uttarakhand. India.
    • Working as an Assistant Professor from 24th July 2017 to 20th June 2019 at Galgotias College of Engineering & Technology, Greater Noida, India.
    • Worked as a Teaching assistant from Aug 2013 to June 2017 at Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, Uttarakhand. India.
    • Worked as a Teaching assistant from Aug 2011 to June 2013 at YMCA University of Science & Technology, Faridabad, Haryana, India.
    • Worked as a Software Engineer from Aug 2009 to July 2011 at MSS infosystem, Noida, Sec 22
  • Research Experience
    • Working as a Research Coordinator for CSE department from January 2023 to December 2023 at Graphic Era Hill University, Dehradun, Uttarakhand. India.
    • Worked as a Full time PhD Research Scholar from Aug 2013 to June 2017 at Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, Uttarakhand. India.
    • Worked as a Full time M.Tech Research Scholar from Aug, 2011 to June 2013 at YMCA University of Science & Technology, Faridabad, Haryana, India.
  • Research Profile
  • Publication
    • Singh, D. K., Jha, S. K., Kumar, I., & Mohd, N. (2024). Swarm Intelligence-Based Optimisation and Its Application in Computational Convergence in Electronic Health Records. In Computational Convergence and Interoperability in Electronic Health Records (EHR) (pp. 175-194).
    • Kumar, I., & Mohd, N. (2024). Ways of Using Computational Thinking to Improve Students’ Ability to Think Critically. In Infrastructure Possibilities and Human-Centered Approaches With Industry 5.0 (pp. 253-266).
    • Gudur, R., Tamboli, A. I., Kumar, I., & Joshi, K. (2024). Integration of Genetic Algorithm and Convolutional Neural Networks for Histopathological Image Analysis in Breast Cancer Diagnosis. International Journal of Intelligent Systems and Applications in Engineering, 12(3s), 542-552.
    • Kumar, L., Singh, K. U., Kumar, I., Kumar, A., & Singh, T. (2023). Robust Medical Image Watermarking Scheme Using PSO, LWT, and Hessenberg Decomposition. Applied Sciences, 13(13), 7673.
    • Kumar, L., Kumar, A., Kumar, S., & Kumar, I. (2023). Applications of Watermarking in Different Emerging Areas: A Survey. In Advancements in Bio-Medical Image Processing and Authentication in Telemedicine (pp. 161-184).
    • Kumar, I., Bisht, A., & Rawat, J. (2023). Identification of Tomato Plant Disease Using Faster R-CNN and RetinaNet. In Convergence of Cloud Computing, AI, and Agricultural Science (pp. 306-327). IGI Global.
    • Kumar, I., & Gudur, R., (2023). Machine Learning Approaches for Automatic Lesion Detection in Mammography Images. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 91–96.
    • Panwar, A., Kumar, I., Bhoite, A., & Prasad, V. (2023). Machine Learning-Based Classification of Medical Images for Disease Diagnosis in Healthcare. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 01–07.
    • Kumar, I, Bhatt C, and Singh KU. 2022. Entropy based automatic unsupervised brain intracranial hemorrhage segmentation using CT images. Journal of King Saud University-Computer and Information Sciences. Vol. 34(6), Pages 2589-2600.
      DOI: https://doi.org/10.1016/j.jksuci.2020.01.003.
    • Kumar, I., Kumar, A., Kumar, VD., Kannan, R. Vimal, V., Singh, KU, Mahmud, M. 2022. Dense Tissue Pattern Characterization using Deep Neural Network, Cognitive Computation.
      DOI: https://doi.org/10.1007/s12559-021-09970-2
    • Khan, MA., Khan, R., Algarni, F., Kumar, I., Choudhary, A., Srivastava., A. 2022. Performance Evaluation of Regression Models for COVID-19: A Statistical and Predictive Approach. Ain Shams Engineering Journal, Vol. 13(2), 101574.
      DOI: https://doi.org/10.1016/j.asej.2021.08.016.
    • Kumar, I., Singh, S.P., Shivam., 2022. Machine learning in bioinformatics. In Bioinformatics (pp. 443-456). Academic Press.
      DOI: https://doi.org/10.1016/B978-0-323-89775-4.00020-1
    • Singh S.P., Rawat J., Mittal M., Kumar I., Bhatt C., 2022. Application of AI in SCM or Supply Chain 4.0. In: Fernandes S.L., Sharma T.K. Artificial Intelligence in Industrial Applications. Learning and Analytics in Intelligent Systems, vol 25. Springer, Cham.
      DOI: https://doi.org/10.1007/978-3-030-85383-9_4
    • Bhatt, C., Kumar, I., 2022, Extensive Study of WBC Segmentation Using Traditional and Deep Learning Methods, In Application of Deep Learning Methods in Healthcare and Medical Science, AAP & CRC Press.
    • Kumar, A., Rawat, J., Kumar, I., Rashid, M., Singh, KU., Al‐Otaibi, YD., Tariq, U. 2022. Computer-Aided Deep Learning Model for Identification of Lymphoblast Cell using Microscopic Leukocyte Images. Expert Systems, 39(4), e12894
      DOI: https://doi.org/10.1111/exsy.12894
    • 16. Kumar, I., Bhatt, C., Vimal, V., and Qamar, S., 2022. Automated White Corpuscles Nucleus Segmentation using Deep Neural Network from Microscopic Blood Smear. Journal of Intelligent & Fuzzy Systems. DOI:10.3233/JIFS-189773.
    • 17. Kumar, I., Rawat, J., Mohd, N., & Husain, S. 2021. Opportunities of Artificial Intelligence and Machine Learning in the Food Industry. Journal of Food Quality, 2021.
      DOI: https://doi.org/10.1155/2021/4535567
    • Kumar, I.; Alshamrani, S. S.; Kumar, A.; Rawat, J.; Singh, K. U.; Rashid, M.; AlGhamdi, A. S.. 2021. Deep learning approach for analysis and characterization of COVID-19, Computers, Materials and Continua; 70(1):451-468.
      DOI:10.32604/cmc.2022.019443
    • Bhadauria, N., Kumar, I., Bhadauria, HS., Patel, RB., 2021. Hemorrhage Detection using Edge-based Contour with Fuzzy Clustering from Brain Computed Tomography Images, International Journal of System Assurance Engineering and Management (Springer Nature).
      DOI: https://doi.org/10.1007/s13198-021-01269-7
    • Bhatt, C., Kumar, I., Vijayakumar, V., Singh, K.U. and Kumar, A., 2020. The state of the art of deep learning models in medical science and their challenges. Multimedia Systems, pp.1-15.
      DOI: https://doi.org/10.1007/s00530-020-00694-1
    • Rawat, J., Virmani, J., Singh, A., Bhadauria, H.S., Kumar, I. and Devgan, J.S., 2020. FAB classification of acute leukemia using an ensemble of neural networks. Evolutionary Intelligence, pp.1-19.
      DOI: https://doi.org/10.1007/s12065-020-00491-9
    • Kumar, I., Mohd, N., Bhatt, C. and Sharma, S.K., 2020. Development of IDS Using Supervised Machine Learning. In Soft Computing: Theories and Applications (pp. 565-577). Springer, Singapore.
      DOI: https://doi.org/10.1007/978-981-15-4032-5_52
    • Kumar, I., Virmani, J. and Bhadauria, H.S., 2019. A Computerised framework for characterisation of breast tissue using mammographic images. International Journal of Computational Systems Engineering, 5(4), pp.193-210.
      DOI: https://doi.org/10.1504/IJCSYSE.2019.101703
    • Kumar, I., Virmani, J., Bhadauria, H.S. and Thakur, S., 2019. A breast tissue characterization framework using PCA and weighted score fusion of neural network classifiers. In Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis (pp. 129-151). Academic Press.
      DOI: https://doi.org/10.1016/B978-0-12-818004-4.00006-6
    • Kumar, I., Virmani, J. and Bhadauria, H.S., 2019. Optimization of ROI size for development of computer assisted framework for breast tissue pattern characterization using digitized screen film mammograms. In Machine Learning in Bio-Signal Analysis and Diagnostic Imaging (pp. 127-157). Academic Press.
      DOI: https://doi.org/10.1016/B978-0-12-816086-2.00006-0
    • Kumar, I., Bhadauria, H.S. and Virmani, J., 2018. A computerised framework for prediction of fatty and dense breast tissue using principal component analysis and multi-resolution texture descriptors. International Journal of Computational Systems Engineering, 4(2-3), pp.73-85.
      DOI: 10.1504/IJCSYSE.2018.091386
    • Kumar, I., Virmani, J., Bhadauria, H.S. and Panda, M.K., 2018. Classification of Breast Density Patterns Using PNN, NFC, and SVM Classifiers. In Soft Computing Based Medical Image Analysis (pp. 223-243). Academic Press.
      DOI: https://doi.org/10.1016/B978-0-12-813087-2.00012-9
    • Kumar, I., Bhadauria, H.S., Virmani, J. and Thakur, S., 2017. A hybrid hierarchical framework for classification of breast density using digitized film screen mammograms. Multimedia Tools and Applications, 76(18), pp.18789-18813.
      DOI: https://doi.org/10.1007/s11042-016-4340-z
    • Kumar, I., Bhadauria, H.S., Virmani, J. and Thakur, S., 2017. A classification framework for prediction of breast density using an ensemble of neural network classifiers. Biocybernetics and Biomedical Engineering, 37(1), pp.217-228.
      DOI: https://doi.org/10.1016/j.bbe.2017.01.001
    • Kumar, I., Bhadauria, H.S. and Virmani, J., 2015. Wavelet packet texture descriptors based four-class BIRADS breast tissue density classification. Procedia Computer Science, 70, pp.76-84. DOI: https://doi.org/10.1016/j.procs.2015.10.042
  • Referred Conference Publications
    • M. Bohra, I. Kumar and Shivam, “Automated Music Genre Classification Using Modified MobileNet Deep Learning Model,” 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS), Coimbatore, India, 2024, pp. 767-772, doi: 10.1109/ICSCSS60660.2024.10625448.
    • V. Chauhan, H. Singh, K. Dewari and I. Kumar, “Efficient Employee Tracking with Smart Attendance System Using Advanced Face Recognition and Geofencing,” 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS), Coimbatore, India, 2024, pp. 750-755, doi: 10.1109/ICSCSS60660.2024.10625038.
    • Kumar, I., Bhatt, H., Raza, K., Maithani, A., & Singh, T. (2024, March). Computational analysis of clothing detection and segmentation in virtual dressing room. In AIP Conference Proceedings (Vol. 3072, No. 1). AIP Publishing.
    • Ghosh, D., Ghosh, C., Dey, P., Ali, A., Bohra, M., Kumar, I., & Mohd, N. (2024, March). Automated cricket commentary generation using deep learning. In American Institute of Physics Conference Series (Vol. 3072, No. 1, p. 030005).
    • Kumar, I., Mohd, N., Kumar, D., Dwivedi, A., & Chaudhary, V. (2024, March). Traffic Density Monitoring and Controller using RFID. In 2024 International Conference on Automation and Computation (AUTOCOM) (pp. 675-679). IEEE.
    • Nautiyal, I., Kumar, I., Singh, T., & Chauhan, R. (2023, November). Forged News Recognition Using Ensemble Machine Learning Classification Techniques. In 2023 2nd International Conference on Futuristic Technologies (INCOFT) (pp. 1-6). IEEE.
    • Mohd, N., Agrawal, M., Kesarwani, D., Garg, A., & Kumar, I. (2023, October). A Hybrid Model for Identifying Social Media Addiction Patterns Among Young People. In 2023 International Conference on Computer Science and Emerging Technologies (CSET) (pp. 1-4). IEEE.
    • Chauhan, S., Singh, V., Pundir, M., Sisodiya, N., Mohd, N., & Kumar, I. (2023, October). Online Money Transaction Security. In 2023 International Conference on Computer Science and Emerging Technologies (CSET) (pp. 1-5). IEEE.
    • Kumar, I., Chauhan, R., Negi, A., Singh, T., & Mohd, N. (2023, September). Tweets Sentiment Analysis Using Machine Learning and Modified BERT Methods. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 395-400). IEEE.
    • Chauhan, A., Kumar, I., Singh, K. U., & Singh, P. (2023, September). Deep Architecture for Breast Cancer Detection: Using Optimized VGG16 Model and Transfer Learning. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 853-858). IEEE.
    • Gupta, R., Rawat, J., Kumar, I., Singh, T., Bohra, M., & Kumar, D. (2023, September). Diagnosis of Heart Failure Using AI Techniques. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 795-800). IEEE.
    • Bohra, M., Kumar, I., & Singh, T. (2023, September). Pneumonia Identification Using Deep Learning Models. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 441-445). IEEE.
    • Yadav, R., Chaudhary, R., Istwal, S., Kumar, S., Bohra, M., & Kumar, I. (2023, September). Development of an AI Enabled Yoga Posture (Aasans) Prediction System Using Deep Neural Network Model. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 386-390). IEEE.
    • Joshi, B., Pathak, V., Kumar, I., Mohd, N., Prakash, S., & Kumar, L. (2023, September). Development And Implementation of the Ganga Water Quality Monitoring System. In 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) (pp. 864-868). IEEE.
    • Gairola, R., Chaudhary, P. S., Chaudhary, A., Singh, S. K., & Kumar, I. (2023, August). Action Analyzer for Differently Abled People. In 2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON) (pp. 1-5). IEEE.
    • Jain, H., Kumar, I., Jain, K., Porwal, I. N., Singh, T., & Mohd, N. (2023, July). Revealing Multiple Lung Condition Using Deep Neural Network Models from X-RAY Images. In 2023 IEEE World Conference on Applied Intelligence and Computing (AIC) (pp. 728-734). IEEE.
    • Rawat, A. S., Devrani, H., Yaduvanshi, A., Bohra, M., Kumar, I., & Singh, T. (2023, July). Surveillance System using Moving Vehicle Number Plate Recognition. In 2023 2nd International Conference on Edge Computing and Applications (ICECAA) (pp. 940-945). IEEE.
    • Yadav, O., Dangi, Y., Mohd, N., & Kumar, I. (2023, July). Predictive Model for M-Health (Cardiovascular Diseases) using ML Application. In 2023 World Conference on Communication & Computing (WCONF) (pp. 1-5). IEEE.
    • Gusain, A., Rawat, A. S., Bohra, M., Kumar, I., & Singh, T. (2023, July). Distracted Driver Detection and Driver Rating System using Deep Learning. In 2023 World Conference on Communication & Computing (WCONF) (pp. 1-6). IEEE.
    • Pal, A., Kumar, I., Bhatt, C., & Mohd, N. (2023, June). A Stock Market Trends Analysis of Google using Convolutional Neural Network based Techniques. In 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN) (pp. 97-102). IEEE.
    • P. K. Kumar, I. Kumar, S. Kumar, P. Kumar, J. Harshith and A. Dutta, “Diagnosing Phytophthora infestans infestations on Solanum tuberosum leaves using Machine Learning Classifiers,” 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), Greater Noida, India, 2023, pp. 95-99, doi: 10.1109/CISES58720.2023.10183419.
    • L. Kumar, K. U. Singh and I. Kumar, “A Compreshensive review on Digital Image Watermarking Techniques,” 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), Greater Noida, India, 2023, pp. 737-743, doi: 10.1109/CISES58720.2023.10183418.
    • Rawat, J., Kumar, I., Mohd, N., Maheshwari, A., Sharma, N. (2023). Analysis of Top Vulnerabilities in Security of Web-Based Applications. In: Hassanien, A.E., Castillo, O., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. ICICC 2023. Lecture Notes in Networks and Systems, vol 703. Springer, Singapore. https://doi.org/10.1007/978-981-99-3315-0_55
    • Rawat, J., Kumar, I., Mohd, N., Rana, K.K.S., Pathak, N., Gupta, R.K. (2023). IoT-Based Home Automation System Using ESP8266. In: Hassanien, A.E., Castillo, O., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. ICICC 2023. Lecture Notes in Networks and Systems, vol 703. Springer, Singapore. https://doi.org/10.1007/978-981-99-3315-0_53
    • A. Giri, D. S. Bisht, A. Chauhan and I. Kumar, “Computerized Face Mask Detection System Using Deep CNN and Transfer Learning,” 2023 International Conference on Device Intelligence, Computing and Communication Technologies, (DICCT), Dehradun, India, 2023, pp. 457-462, doi: 10.1109/DICCT56244.2023.10110187.
    • A. Chauhan, I. Kumar, C. Bhatt and A. Agnihotri, “Computer aided Breast lesions classification system using digitized fine needle aspirate images,” 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON), Raigarh, Chhattisgarh, India, 2023, pp. 1-6, doi: 10.1109/OTCON56053.2023.10113974.
    • N. Mohd, K. Joshi, S. Husain, I. Kumar, P. Srivastava, and N. Chaturvedi, “LTE Based Comparative Analysis of Routing Protocols in Heterogeneous Network (HETNet) Environment,” In Proceedings of the 4th International Conference on Information Management & Machine Intelligence (pp. 1-12), 2022.
    • Jain, H., Kumar, I., Porwal, I. N., Jain, K., Kunwar, K., Kumar, L., & Mohd, N. (2022, December). Lung Conditions Prognosis Using CNN Model. In International Conference on Cybersecurity in Emerging Digital Era (pp. 225-234). Singapore: Springer Nature Singapore.
    • Surya Pratap Singh, Shivam, Indrajeet Kumar, 2022. Temperature Prognosis Using Regression Techniques, In 2nd IEEE International Conference on Intelligent Technologies, Hubballi, Karnataka, India. 2022, pp. 1-5.
      DOI: 10.1109/CONIT55038.2022.9847902..
    • Surya Pratap Singh, Shivam, Indrajeet Kumar, 2022. Edge Detection Based Medical Denoising using Wavelet Domain, In 2nd IEEE International Conference on Intelligent Technologies, Hubballi, Karnataka, India. pp. 1-5.
      DOI: 10.1109/CONIT55038.2022.9848203.
    • Surya Pratap Singh, Shivam, Indrajeet Kumar, 2022. Orange Fruit Recognition using Neural Networks, In International Conference on Computational Intelligence & Sustainable Technologies (ICoCIST-2021), NIT SILCHAR AND NIT SIKKIM, India.
      DOI: https://doi.org/10.1007/978-981-16-6893-7_38
    • Jyoti Rawat, Sachin Rawat, Indrajeet Kumar, JS Devgun, 2022. Identification of Malignant Lymphoblast Cell in Bone Marrow using Machine Learning, In International Conference on Computational Intelligence & Sustainable Technologies (ICoCIST-2021), NIT SILCHAR AND NIT SIKKIM, India.

      • DOI: https://doi.org/10.1007/978-981-16-6893-7_25

    • Priya Kohli, Indrajeet Kumar, Vrince Vimal. 2022. Plant Leaf Disease Identification using Unsupervised Fuzzy C-Means Clustering and Supervised Classifiers. ICCEDE, 2020, India.

      • DOI: https://doi.org/10.1007/978-981-16-8012-0_22

    • Vikas Thapliyal, Indrajeet Kumar, Palak Sharma, Harvendra Singh Bhadauria and Annapurna Singh. 2021. Automated Brain Hemorrhage Segmentation using Deep Neural Network. SMARTCOM-2020.
    • Shivam, S.P Singh, I. Kumar. Rice Plant Diseases Identification using Deep Neural Network Methods. MISRNLP-2021.
    • Indrajeet Kumar, Noor Mohd, Chandradeep Bhatt, Shashi Kr Sharma, 2020, “Development of IDS using Supervised Machine Learning”, In Soft Computing: Theories and Applications at NIT Patna.
    • Mukesh Sidhwan, H.S Bhadauria, VM Thakkar, Indrajeet Kumar, “Mammogram’s denoising in spatial and frequency domain”, In Next Generation Computing Technologies (NGCT), 2016 2nd International Conference on (pp. 654-659). IEEE.
    • Indrajeet kumar, Dr. H.S Bhadauria, Dr. Jitendra Virmani, “A review of breast tissue density classification” INDIACOM 2015, DOI: 978-9-3805-4416-8/15/$31.00©2015 IEEE.
    • Jyoti Rawat, Dr. Annapurna Singh, Dr. H.S. Bhadauria, Indrajeet Kumar, “Comparative Analysis of Segmentation Algorithms for Leukocyte Extraction in the Acute Lymphoblastic Leukemia Images”, IEEE PDGC 2014, JUIT, SOLAN, HP, INDIA.
    • Indrajeet kumar, Dr. H.S. Bhadauria, Jyoti Rawat, “Reduction of Speckle noise from medical Images using Principal component analysis image fusion”, 9th IEEE International Conference (ICIIS2014), 15-17 December, 2014 at IIITM, Gwalior, India.
    • Jyoti Rawat , Dr. H.S. Bhadauria, Indrajeet Kumar, “A Study on Segmentation of Leukocytes in Microscopic Blood Images”, ICSCTET-2014” Sponsored by IEEE at Graphic Era Hill University Bhimatal Nainital. INDIA, Paper Id: ICSCTET240.
    • Indrajeet Kumar, Dr. H.S. Bhadauria, Jyoti Rawat, “Liver Tumor Classification Using Medical modalities by neural network as classifier: A Comprehensive Review”, ICSCTET-2014” Sponsored by IEEE at Graphic Era Hill University Bhimatal Nainital. INDIA, Paper Id: ICSCTET234.
    • Indrajeet Kumar, Jyoti Rawat, H.S. Bhadauria, “A Conventional And Comparative Study Of Edge Detection Technique In Digital Image Processing”, National Conference on Emerging Trends in Engineering Science and Technology(NCETEST-ET-104) 2014.
    • Parul Tomar, Indrajeet Kumar, Jyoti Rawat, “An Intrusion Detection System for Black Hole Attack In MANET”, In Proceeding of 2nd International conference on Emerging Trends in Computer Science & Information Technology (ICETCSIT)-2014.

      • Indrajeet kumar, Jyoti Rawat, Dr. H.S. Bhadauria, “A Review On Classification Of Liver Tumor By Image Processing Of Ultrasound Images”, 9th Symposium on ‘Frontiers in Biomedical Research’ during 2014 at Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, INIDA.

  • Edited Book/Special Issue
    • Applications of Parallel Data Processing for Biomedical Imaging, (2024). Edited by R. Khan, I. Kumar, & P. Praveen, ISBN13: 9798369324264, EISBN13: 9798369324271. IGI Global Publication.
    • Advancements in Bio-Medical Image Processing and Authentication in Telemedicine (2023), Edited by R. Khan & I. Kumar, DOI: 10.4018/978-1-6684-6957-6, ISBN13: 9781668469576, ISBN10: 166846957X, EISBN13: 9781668469583. IGI Global Publication.
  • Grant Recieved
      Hemorrhagic Volume detection from Brain CT Images under Collaborative Research Proposal- TEQIP-III, at Uttarakhand Technical University, Dehradun. (Budget: 2.7 L)
  • Reviewer of Journals
    • Ain Shams Engineering Journal, Elsevier
    • Multimedia tools and applications, Springer
    • World Journal of Gastroenterology
    • World Journal of Clinical Cases
    • International Journal of Communication Systems
    • International Journal of Computational Intelligence and Applications
    • International Journal of Computer Information Systems and Industrial Management Applications
    • MDPI journals like Bioengineering, Applied sciences, Cancers, Mathematics, Sensors, Remote sensing


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