Dr. Manika Jha

Education

• Ph. D (JIIT NOIDA)
• M.TECH. IN ROBOTICS & AUTOMATION (IGDTUW, NEW DELHI)
• B.TECH. IN INSTRUMENTATION AND CONTROL (GGSIPU, NEW DELHI)

Work Experience

• 6 years (research + teaching)

Biography

She is an academic and researcher specializing in Electronics and Communication Engineering with a focus on signal processing and Artificial Intelligence (AI). She is currently serving as an Assistant Professor (S.G.) at the Jaypee Institute of Information Technology (JIIT), Noida. Manika completed her Ph.D. from JIIT in 2024, where her thesis explored enhancing non-invasive disease detection using machine learning and signal processing techniques. Prior to this, she earned her M.Tech. in Robotics and Automation Engineering from Indira Gandhi Delhi Technical University for Women in 2019, and a B.Tech. in Instrumentation and Control Engineering from Guru Gobind Singh Indraprastha University in 2016.

With a strong academic background, Manika has developed expertise in several domains, including supervised and unsupervised machine learning, deep learning, signal and image analysis, and pattern recognition. She is proficient in programming languages such as Python, R, and MATLAB, and has experience working with machine learning frameworks like TensorFlow and PyTorch. Her research is primarily centered on analyzing biomedical data, with a strong interest in developing algorithms for various applications.

Interest Areas

• Signal Processing, Signal Transforms, Machine Learning, Deep Learning, Pattern Recognition, Generative Models, Natural Language Processing (NLP), Biomedical signal processing

Journal Publications

• M. Jha, R. Gupta and R. Saxena, "A Precise method to detect COVID-19 associated Pulmonary Fibrosis through Extreme Gradient Boosting," SN Computer Science, vol. 4, no. 89, pp. 1-12, 2022. https://doi.org/10.1007/s42979-022-01526-x (Springer, Scopus indexed)
• M. Jha, R. Gupta and R. Saxena, "A framework for in-vivo human brain tumor detection using image augmentation and hybrid features," Health Information Science and Systems, vol. 10, no. 23, pp. 1-12, 2022. https://doi.org/10.1007/s13755-022-00193-9 (Springer IF- 6.00, SCIE indexed)
• M. Jha, R. Gupta and R. Saxena, "Fast and precise prediction of non-coding RNAs (ncRNAs) using sequence alignment and k-mer counting," International Journal of Information Technology, vol. 14, no. 6, pp. 1-9, 2022. https://doi.org/10.1007/s41870-022-01064-y (Springer, Scopus indexed)
• M. Jha, R. Gupta and R. Saxena, " Noise cancellation of polycystic ovarian syndrome ultrasound images using robust two-dimensional fractional fourier transform filter and VGG-16 model," International Journal of Information Technology, vol. 16, no. 3, pp. 1-12, 2024. https://doi.org/10.1007/s41870-022-01064-y (Springer, Scopus indexed)
• M. Jha, R. Gupta and R. Saxena, " Convolutional neural network based detection of lung adenocarcinoma by amalgamating hybrid features," International Journal of Advanced Technology and Engineering Exploration, vol. 11, no. 111, pp. 160-176, 2024. https://doi.org/10.1007/s41870-022-01064-y (Scopus indexed)

Conference publications

• M. Jha and N.R. Chauhan, “A review on Snake-like Continuum Robots for Medical Surgeries,” IOP Conference Series: Materials Science and Engineering, vol. 691, 2019. doi:10.1088/1757-899X/691/1/012093 (Conference Proceedings)
• M. Jha, R. Gupta and R. Saxena, "Cervical Cancer Risk Prediction Using XGboost Classifier," 2021 7th International Conference on Signal Processing and Communication (ICSC), 2021, pp. 133-136. https://doi.org/10.1109/ICSC53193.2021.9673474 (IEEE Proceedings, Scopus indexed)
• M. Jha, R. Gupta and R. Saxena, "Potential Point-of-Care Biosensors for the detection of COVID-19," International conference on Advances in Biosciences and Biotechnology (ICABB), 2021, pp. 39-42. (Conference Abstract Proceedings)
• M. Jha, R. Gupta and R. Saxena, "A Review on Non-Invasive Biosensors for Early Detection of Lung Cancer," 2020 6th International Conference on Signal Processing and Communication (ICSC), Noida, India, 2020, pp. 162-166. https://doi.org/10.1109/ICSC48311.2020.9182775 (IEEE Proceedings, Scopus indexed)
• M. Jha, R. Gupta and R. Saxena, "Potential point-of-care Biosensors for the detection of COVID-19," in Recent Trends in Biosciences and Biotechnology, Ed. Vidya Kutir Foundation, ch. 3, pp. 27-42. (Book Chapter)

Patent Filed On

• Smart Lung Disease Detection System (Patent application no. 202211069830)

Book Chapter

• M. Jha, R. Gupta and R. Saxena, “Potential point-of-care Biosensors for the detection of COVID-19,” in Recent Trends in Biosciences and Biotechnology, Ed. Vidya Kutir Foundation, ch. 3, pp. 27-42. doi: https://doi.org/10.48002/BOOK

Reviewer

• Current Pharmaceutical Biotechnology
• Current Medical Imaging
• Health Information Science and Systems (HISC)
• BMC Medical Informatics and Decision Making