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Academic Experts
Dr. Manika Jha

Biography

Dr. Manika Jha is an academic and researcher specializing in Electronics and Communication Engineering, with expertise in signal processing and Artificial Intelligence (AI). She is currently serving as an Assistant Professor (Senior Grade) at the Jaypee Institute of Information Technology (JIIT), Noida.

She earned her Ph.D. in Electronics and Communication Engineering from JIIT in 2024, focusing on enhancing non-invasive disease detection through machine learning and signal processing techniques. She holds an M.Tech. in Robotics and Automation from Indira Gandhi Delhi Technical University for Women (2019) and a B.Tech. in Instrumentation and Control Engineering from Guru Gobind Singh Indraprastha University (2016).

With over six years of combined research and teaching experience, Dr. Jha has worked extensively in machine learning, deep learning, biomedical signal and image analysis, and pattern recognition. She has played key roles in academic development, including establishing Robotics and AI Centre of Excellence, mentoring students, and contributing to departmental academic initiatives.

Her research contributions include national and international collaborations, multiple Scopus and SCIE-indexed publications, and a patent published on smart lung disease detection. She has served as a reviewer for reputed journals such as Current Pharmaceutical Biotechnology, Current Medical Imaging, and BMC Medical Informatics and Decision Making.

Research Highlights

Her core research spans biomedical signal and image processing, AI-driven diagnostic systems, robotics and automation, and machine learning for healthcare analytics. Her work integrates advanced algorithms with real-world applications, focusing on non-invasive, intelligent solutions.

A few key innovations include:

  • Development of hybrid feature extraction and deep learning frameworks for early detection of brain tumours, lung cancer, and COVID-19-associated pulmonary fibrosis.
  • Application of advanced signal transforms for noise cancellation and enhancement in medical imaging, improving diagnostic precision.
  • Design of AI-enabled biosensor systems for non-invasive disease screening and wearable healthcare monitoring.
  • Integration of robotics and AI for healthcare and assistive technologies, including gesture-controlled robotic systems and object detection models for autonomous decision-making.
  • Exploration of Large Language Models (LLMs) for automated analysis of clinical notes, therapy session transcripts, and electronic health records.
  • Use of Generative AI in medical imaging for synthetic data generation, rare disease simulation, and anomaly detection to strengthen diagnostic models.

Her research is strongly application-oriented, with potential for point-of-care devices, robotic assistance in surgeries, gesture-based rehabilitation systems, wearable health technologies, and telemedicine platforms. She is also working on multimodal AI systems that integrate imaging, speech, and bio-signals for holistic healthcare diagnostics.

Areas of Interest
  • Signal Processing
  • Signal Transforms
  • Machine Learning
  • Deep Learning
  • Pattern Recognition
  • Biomedical Signal Processing
  • Generative AI, Robotics
  • AI for Robotic Systems
Patents

1. Smart Lung Disease Detection System

  • Application ID: 202211069830 (Filed)
  • Status: Published
  • Specification: AI-enabled system for non-invasive detection of lung diseases using hybrid signal and image processing techniques.