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Akriti Nigam

From ICANNWiki
Affiliation: Birla Institute of Technology, Mesra, Ranchi
Country: India
Email: aksways [at] gmail.com, akriti [at] bitmesra.ac.in
Facebook:    Akriti Nigam
LinkedIn:    [www.linkedin.com/in/dr-akriti-nigam Akriti Nigam]
Google+: https://scholar.google.co.in/citations?user=c1kpP-UAAAAJ&hl=en
Twitter:    @https://twitter.com/akritinigam

Akriti Nigam obtained her B. Tech degree in Information Technology in 2009 after which she did her Post Graduation from Indian Institute of Information Technology, Allahabad (now Prayagraj) and received her M.Tech degree in Human-Computer Interaction, a specialization of Information Technology in the year 2011. She then completed her Doctoral Research in the field of Image processing and obtained PhD degree from Indian Institute of Information Technology, Allahabad in the year 2017.

She joined as Assistant Professor in Computer Science & Engineering department of Birla Institute of Technology, Mesra, Ranchi in April 2015. She has been taking theory and lab courses on Image processing, Computer Graphics, Information Theory & Coding, MATLAB Programming, C Programming, Data Compression & Data Hiding, Cryptography etc. She has been continuously guiding graduate and postgraduate project students and has currently 3 doctoral research students under her supervision.

Her current research areas include Image Processing, Machine Learning, Applications of Image Processing in the fields of Additive manufacturing, Neuroimaging.

She is the recipient of a Fellowship from the National Internet Exchange of India.[1]

Nigam's first ICANN meeting was ICANN 49 in Singapore.[1]

ICANN49 at Singapore
ICANN 49- Singapore



International Collaboration:

International Science Partnership Fund (ISPF), funded by ‘DFE: NI Department for the Economy, UK. Project Title: "Digital twin-based process monitoring system for Laser directed energy deposition process". Fund amount £354,189. Involved as a Co PI.

Visited Ulster University, Londonderry from 11th Nov to 15th Nov '24 to participate in post project acceptance workshop. The trip was funded by the project.

Talk delivered at Ulster University, Northern Ireland

Indian Government project funding:

  1. Indian Council of Medical Research- INVESTIGATOR- INITIATED RESEARCH PROPOSALS FOR SMALL EXTRAMURAL GRANTS - 2024, (Call Released on 20-Dec-2023) Project Title: Development of a robust Machine Learning tool to support quick Malaria detection and parasite stage identification for reducing Malaria burden. Fund amount Rs 1,51,50,863. Duration-3 years PI- Dr Akriti Nigam Co-PI- Dr Manish Pandey (CQEDS)

Publcations

SCI/SCIE- 8

Scopus Non-paid- 5

Others- 3

Journal Publications

  1. Nigam, A., Garg, A. and, Tripathi, R.C. (2011), "Content Based Trademark Retrieval by Integrating Shape with Color and Texture Information", International Journal of Computer Applications, Vol. 22, pp 40-45.
  2. Nigam, A., Yadav, R., Tripathi, R.C. (2013), "Image Retrieval System for Composite Image Using Directional Chain Codes", International Journal of Advanced Science and Technology, Vol. 58, pp 51-64.
  3. Nigam, A., Indoria, A., Tripathi, R.C. (2013), "Fuzzy Clustering of Image Trademark Database and Pre processing using Adaptive Filters and Karhunen Loeve Transform", International Journal of Image and Graphics, Vol. 13, Pages 15. [Non paid SCOPUS]
  4. Nigam, A. and Tripathi, R.C (2016), "Trademark Image Retrieval Using Weighted Combination of SIFT and HSV Correlogram", International Journal of Computer Applications in Technology Vol. 54, No. 1, pp 61-67. [Non paid SCOPUS]
  5. Nigam, A., Singh, P., Singh, V.K., Tripathi, R.C., (2018), “A Multiple Feature Based Offline Handwritten Signature Verification System”, International Journal of Computer Applications in Technology, Vol 59, Issue 3, pp 214- 223. doi: 10.1504/IJCAT.2019.098602 [Non paid SCOPUS]
  6. Nigam, A., Singh, V. K., (2021), "Efficient Retrieval of Trademark Images from Large Database", International Journal of Intellectual Property Management, Vol.11 No.2, pp.165 - 184 [Non paid SCOPUS]
  7. Gupta, A., Nigam, A., (2020), “Development of general mathematical model for calculation of solar radiation on moving surfaces”, Vigyan Garima Sindhu (CSTT, MHRD), Vol. 112, Jan 2020, pp. 78-86, ISSN: 2320-7736.
  8. Kumari, R., Nigam, A. & Pushkar, S. (2020) Machine learning technique for early detection of Alzheimer’s disease. Microsyst Technol. 26, pp 3935–3944 https://doi.org/10.1007/s00542-020-04888-5 [SCOPUS, SCI, Q2 impact factor 1.73]
  9. Patil, D., Nigam, A., Mohapatra, S., (2020), "Automation of geometric feature computation through image processing approach for single-layer laser deposition process", International Journal of Computer Integrated Manufacturing, Vol 33, Issue 9, pp 895- 910, DOI 10.1080/0951192X.2020.1815843 [Scopus, SCIE, Q1 impact factor 3.2]
  10. Nigam, A., Gupta, A., Singh, Singh R. K., (2020), "Novel image analysis based method for residence time distribution analysis in steel making tundish", Transactions of the Indian Institute of Metals, Vol 74, Issue 2, pages 243- 254  DOI 10.1007/s12666-020-02142-0 [Scopus, SCIE, Q2 impact factor 1.2]
  11. Kumari, R., Nigam, A., Pushkar, S., (2021) “Multi- layered Convolutional neural network on multi modal images for classifying Alzheimer’s disease", Turkish Journal of Physiotherapy and Rehabilitation, Volume 32(3) Pages: 14506 – 14511 [Non paid Scopus, ESCI].
  12. Patil, D., Nigam, A., Mohapatra, S., (2021), "Image processing approach to automate feature measuring and process parameter optimizing of laser additive manufacturing process", Journal of Manufacturing Processes, Elsevier, Vol 69, pp 630-647. [Scopus, SCIE, Q1 impact factor 5.010]
  13. Kumari, R., Nigam, A., Pushkar, S., (2022) "An Efficient Combination of Quadruple Biomarkers in Binary Classification using Ensemble Machine Learning Technique for early onset of Alzheimer Disease", Neural Computing & Applications, Springer, DOI  10.1007/s00521-022-07076-w [Scopus, SCIE, Q1 impact factor 5.6].
  14. Kumari, R., Das, Subhranil, Nigam, A., Pushkar, S., (2023) “Patch-Based Siamese 3D Convolutional Neural Network for Early Alzheimer's Disease using Multi-Modal Approach ”, DOI: 10.1080/03772063.2023.2205857, IETE Journal of Research [Scopus, SCIE, impact factor 1.87].
  15. Patil, D., Nigam, A., Mohapatra, S., Nikam., S., (2023) "A deep learning approach to classify and detect defects in the components manufactured by laser direct energy deposition process", Machines 2023, 11(9), 854; https://doi.org/10.3390/machines11090854 [Scopus, SCIE, impact factor 2.6].
  16. Kumari, R., Das, Subhranil, Nigam, A., (2024) “ Multimodal diagnosis of Alzheimer's disease based on volumetric and cognitive assessment”, Multimedia Tools and Applications, https://doi.org/10.1007/s11042-024-19794-5 [SCIE, impact factor 3]

Conference Publications

  1. Nigam, A., Garg, A. and, Tripathi, R.C. (2012), "A Survey on Approaches for developing Content Based Trademark Retrieval System", National Conference on Emerging Trends in Intelligent Computing & Communication, Galgotias College of Engineering & Technology.
  2. Akriti Nigam, Ajay Indoria, R. C. Tripathi, (2013) “Fuzzy Clustering of Image Trademark Database and Pre processing using Adaptive Filters and Karhunen Loeve Transform”, Second International Conference On Intelligent Interactive Technologies And Multimedia, Springer,  pp297-305.
  3. Nigam, A., Singh, P., Tripathi, R.C. (2013), "Robust Offline Signature Identification and Verification System using Directional Chain Codes", International Conference on Computing Sciences, Lovely Professional University, Jalandhar.
  4. Nigam, A., Tripathi, R.C., (2016) “Novel system for retrieval of Composite Trademarks using Multi feature voting”, 15th International Conference on Information Technology, IIIT Bhubaneshwar, pp 254- 259.
  5. Srivastava, S., Nigam, A., Kumari, R., (2017) “Towards efficient and Scalable big data analytics: Mapreduce vs. RDD’s” In IEEE Proceedings of 16th International Conference on Information Technology, IIIT Bhubaneshwar, DOI: 10.1109/ICIT.2017.54, pp 272- 275.
  6. Aishwarya Jaiswal, Sneha Varma, Ayesha Mundu, Akriti Nigam, (2018), “Decoding Brain Signals Using DWT and MFCC” International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering-(ICRIEECE-2018) during 27- 28 July 2018, Bhubaneswar, India, In Press.
  7. Indoria, A. K., Singhal, V., Nigam, A., (2020), Multi oriented Trademark image text detection using Deep Learning, In proceedings of The International Conference on Intelligent Control and Computation for Smart Energy and Mechatronics Systems, In Press.
  8. Patil, D., Nigam, A., Mohapatra, S., (2020), "Investigation to identify most appropriate edge detection technique on a layer of deposition process", International Conference on Nano-electronics, Circuits & Communication Systems (NCCS-2020)
  9. Kumari, R., Nigam, A., & Pushkar, S. (2021) “Classification of MRI images for detecting Alzheimer’s disease using Convolutional Neural Network”, Soft Computing, Optimization Theory and Applications (SCOTA 2021). pringer Proceedings in Mathematics & Statistics, vol 404. Springer, Singapore. doi.org/10.1007/978-981-19-6406-0_1 .
  1. D. B. Patil, A. Nigam and S. Mohapatra, (2022) "An image processing approach to measure features and identify the defects in the laser additive manufactured components," 2021 4th International Conference on Recent Trends in Computer Science and Technology (ICRTCST), IEEE, pp. 62-66, doi:10.1109/ICRTCST54752.2022.9781953.
  2. Saxena, N., Nigam, A., (2022) “Performance evaluation of a variational Quantum Classifier” IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON). ISSN: 2687-7767,  ISBN:979-8-3503-3251-3,  DOI 10.1109/UPCON56432.2022.9986421
  3. Ohdar, K., Nigam, A., "A Robust Approach for Malaria Parasite Species Identification with CNN based Feature Extraction and Classification using SVM",14th IEEE International Conference on Computing, Communication & Networking Technologies, 6-8, July '23, IIT Delhi.
  4. Saxena, N., Nigam, A., (2023) "Utilizing Non Linear Functions Based Quantum Kernels to Categorize Small Datasets" IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET), 09-12 August 2023. DOI: 10.1109/SeFeT57834.2023.10245485

Book Chapters

  1. Nisheeth Saxena, Akriti Nigam, “Quantum Computing, Cyber Security, and Cryptography: Issues, Technologies, Algorithms, Programming, and Strategies” accepted, to be published by Springer
  2. Rashmi Kumari, Subhranil Das, Akriti Nigam, and Raghwendra Kishore Singh, “The Role of Artificial Intelligence in Medical Image Analysis for Disease Diagnosis”, published in Book: Machine Learning in Biomedical and Health Informatics Current Applications and Challenges, Jan 2025, AAP publisher.


Apart from work she enjoys music, playing badminton, gardening and fun driving. She has a son named Varenyam, who owns most of her time after work.

With Varenyam

References[edit | edit source]

  1. ↑ 1.0 1.1 ICANNWiki - ICANN 49 Intake Form, March 2014


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