Dr. Lipismita Panigrahi is a dedicated AI and Machine Learning researcher, currently a Postdoctoral Research Scholar at the University of Texas, San Antonio. Her expertise spans Explainable AI, Mechine Learning, and AI applications in medical image analysis. With a Ph.D. in Computer Applications from NIT Raipur, she holds a patent and authored a reference book. Dr. Panigrahi has a strong publication record in reputed journals and conferences, receiving accolades such as the Best Paper Award. She has received Chhattisgarh Young Scientist Award-2015. She has also actively contributed to academia, holding positions at esteemed institutions in India. Dr. Panigrahi is an IEEE member, showcasing leadership in scientific activities, research, and teaching.

Research Interests

1. Machine Learning
2. Deep Learning
3. Artificial Intelligence
4. Image Processing
5. Explainable AI

Work Experience

• Postdoc research fellow, University of Texas at San Antonio, USA, April 2023-August 2024.
• Assistant Professor, KIIT University, Odisha, India, Nov. 2022- April 2023.
• Assistant Professor, GITAM University, Visakhapatnam, India, April 2022- Nov. 2023.
• Assistant Professor, O.P. Jindal University, Raigarh, India, March 2021- April 2022.
• Assistant Professor, BCET, Odisha, India, Aug. 2012- Aug. 2015.

Education

• Ph.D. in Computer Application, NIT Raipur, India, 2020
• M.Tech in Computer science ans Data Processing, S.O.A. University, India 2012
• B.Tech in Information Technology, BPUT, India, 2010

Publications

Patent

• Panigrahi, L., Jha, Avaneesh, “Novel Compilation System For Accepting Non-English Based Programming Languages”, Application no 2022/09958, 2022

Reference Book

• Panigrahi L., Biswal S., Bhoi A.K., Kalam A.and Barsocchi, P, “Machine Learning and AI Techniques in Interactive Medical Image Analysis" published by  IGI Global., USA. (ISBN13: 9781668446713, ISBN10: 1668446715, EISBN13: 9781668446737). DOI: 10.4018/978-1-6684-4671-3.

International / National Journals

• Panigrahi, Lipismita, Chandra, T. B., Srivastava, A. K., Varshney, N., Singh, K. U., Mahato, S. “mBCCf: Multilevel Breast Cancer Classification Framework using Radiomic Features”. Accepted in International Journal of Intelligent Systems, 2023.
• Panigrahi, Lipismita, Kesari Verma, and Bikesh Kumar Singh. "Evaluation of image features within and surrounding lesion region for risk stratification in breast ultrasound images." IETE Journal of Research 68.2 (2022): 935-946.
• Panigrahi, Lipismita, Kesari Verma, and Bikesh Kumar Singh. "Ultrasound image segmentation using a novel multi-scale Gaussian kernel fuzzy clustering and multi-scale vector field convolution." Expert Systems with Applications 115 (2019): 486-498.
• Panigrahi, Lipismita, Kesari Verma, and Bikesh Kumar Singh. "Hybrid segmentation method based on multi‐scale Gaussian kernel fuzzy clustering with spatial bias correction and region‐scalable fitting for breast US images." IET Computer Vision 12.8 (2018): 1067-1077.
• Singh, Bikesh Kumar, et al. "Integrating radiologist feedback with computer aided diagnostic systems for breast cancer risk prediction in ultrasonic images: An experimental investigation in machine learning paradigm." Expert Systems with Applications 90 (2017): 209-223.
• Panigrahi, Lipismita, Kaberi Das, and Debahuti Mishra. "Missing value imputation using hybrid higher order neural classifier." Indian Journal of Science and Technology 7.12 (2014): 2007.

International / National Conferences

• Panigrahi, Lipismita, Raghab Ranjan Panigrahi, and Saroj Kumar Chandra. "Hybrid Image Captioning Model." 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON). IEEE, 2023.
• Kumar, Sourabh, et al. "Industry 4.0 based Machine Learning Models for Anomalous Product Detection and Classification." 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON). IEEE, 2023.
• Panigrahi Lipismita. and Panigrahi Raghab. “An Enhancement in K-means algorithm for Automatic Ultrasound image segmentation” accepted in 2nd International Conference on Biomedical Engineering Science and Technology: Roadway from Laboratory to Market (ICBEST), 2023.
• Panigrahi, Lipismita, and Kesari Verma. "Segmented Region based Feature Extraction for Image Classification." 2021 Emerging Trends in Industry 4.0 (ETI 4.0). IEEE, 2021.
• Bafna, Yash, et al. "Automated boundary detection of breast cancer in ultrasound images using watershed algorithm." Ambient Communications and Computer Systems: RACCCS 2017. Springer Singapore, 2018.
• Panigrahi, Lipismita, Keshri Verma, and Bikesh Kumar Singh. "An enhancement in automatic seed selection in breast cancer ultrasound images using texture features." 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2016.
• Panigrahi L., "A hybrid segmentation method for automated segmentation of ultrasound images," 15th Chhattisgarh Young Scientists Congress 2017.
• Pati, Prem Pujari, et al. "Sampling correctly for improving classification accuracy: a hybrid higher order neural classifier (HHONC) approach." Proceedings of the International Conference on Advances in Computing, Communications and Informatics. 2012.
• Panigrahi, Lipismita, et al. "Removal and interpolation of missing values using wavelet neural network for heterogeneous data sets." Proceedings of the International Conference on Advances in Computing, Communications and Informatics. 2012.
• Das, K., Pati, P. P., Mishra, D., & Panigrahi, L. (2012). Empirical comparison of sampling strategies for classification. Procedia engineering, 38, 1072-1076.