CSIR-Senior Research Fellow at CSIR-CEERI, India
Seema Choudhary is a passionate and skilled Project Associate at the Council of Scientific and Industrial Research Central Electronics Engineering Research Institute (CSIR-CEERI), Pilani, Rajasthan. With expertise in computer vision, machine learning, and artificial intelligence, she has contributed to developing innovative AI-driven solutions in healthcare, surveillance, and industrial automation. Her professional journey reflects a strong commitment to applying deep learning and embedded systems for real-world challenges such as UAV-based monitoring, medical imaging, driver drowsiness detection, and infrastructure inspection. She has published research in reputed journals, including Springer’s Applied Intelligence, and is actively engaged in collaborative scientific programs such as Japan’s prestigious Sakura Science Program Fellowship. Known for her strong analytical mindset, adaptability, and leadership, Seema blends technical depth with teamwork to drive impactful research outcomes. She continues to pursue excellence in AI applications, aiming to bridge advanced algorithms with practical social and industrial benefits.
Professional Profile
Google Scholar
Education
Seema Choudhary holds a strong academic foundation in electronics, VLSI design, and artificial intelligence. She earned her M.Tech. in VLSI Design from Mody University of Science and Technology, Sikar, Rajasthan, graduating. Prior to this, she completed her B.Tech. in Electronics and Telecommunication from the same university. During her academic journey, she undertook significant thesis projects, including Vehicle Detection in Aerial Images using Hardware Accelerator, where she explored feature extraction, selection techniques, and deep learning-based classification methods for aerial image analysis. Seema’s education also included practical exposure through industrial training at Hewlett Packard Enterprise, Jaipur, where she gained insights into embedded systems and robotics. Complementing her formal education, she has pursued certifications in AI, machine learning, TensorFlow, and robotics, further strengthening her technical skill set. Her academic background seamlessly aligns with her research and professional pursuits.
Experience
Seema Choudhary professional experience highlights her ability to integrate deep learning with practical engineering challenges. She began as a Project Associate-I in the Intelligent Systems Group at CSIR-CEERI, where she developed deep learning-based algorithms for UAV object detection, face recognition attendance systems, and AI-based COVID-19 testing tools using chest X-rays. Since December , she has been working as a Project Assistant-III in the Cognitive Computing Group at CSIR-CEERI, focusing on computer vision algorithms for fatigue and drowsiness detection in drivers and industrial workers. Her contributions include designing AI models for healthcare, such as fall detection in elderly care, and developing drone-based monitoring systems for power lines and communication towers. Her work has been instrumental in applying AI solutions for safety, surveillance, and industrial automation. Seema’s experience demonstrates her ability to bridge cutting-edge AI research with impactful societal applications, reflecting her dedication to applied machine learning and computer vision.
Research Interest
Seema Choudhary’ research interests lie at the intersection of artificial intelligence and real-world problem-solving. Her focus areas include computer vision, deep learning, machine learning, and medical imaging, where she applies AI algorithms to challenges in healthcare, surveillance, and industrial monitoring. She has worked extensively on driver drowsiness detection, fall detection for elderly care, UAV-based monitoring, and AI-powered COVID-19 screening tools, showcasing her ability to address critical societal and safety needs. Beyond healthcare, her interest extends to embedded AI implementation, where she integrates algorithms with hardware platforms for practical deployment in resource-constrained environments. She is also deeply engaged in data handling, anomaly detection, and image processing, with applications ranging from aerial object detection to power line inspections. With growing expertise in TensorFlow, Keras, PyTorch, and cloud-native tools like Kubernetes and Docker, Seema continues to expand her research toward intelligent, scalable, and socially impactful AI-driven systems.
Award and Honor
Seema Choudhary has been recognized for her academic and professional excellence through multiple honors. A key highlight of her career is being awarded the Sakura Science Program Fellowship by the Government of Japan , which allowed her to visit Nagasaki University under the prestigious international exchange initiative. She is also a Member of the Institution of Engineering and Technology (IET) – India, reflecting her professional recognition within the engineering community. Beyond formal fellowships, Seema has been active in co-curricular and scientific engagements, including participation in the India International Science Festival in Goa, and contributing to creative and academic events during her university studies. Her early achievements include securing the Gargi Prize and Certificate by the Government of India and excelling in sports, notably earning second place in a state-level Kabaddi competition. These honors reflect her versatile talents, leadership qualities, and commitment to academic and professional growth.
Research Skill
Seema Choudhary possesses an extensive range of research and technical skills that bridge theory with application. She is proficient in machine learning, deep learning, computer vision, and medical imaging, enabling her to design and implement AI-driven solutions for real-world problems. Her software expertise includes Python, C, C++, MATLAB, and libraries such as TensorFlow, Keras, PyTorch, Scikit-Learn, NumPy, Pandas, SciPy, and Matplotlib. She is skilled in data analysis, data management, image processing, and applying ensemble learning methods. Her technical toolkit extends to modern infrastructure technologies like Docker and Kubernetes, allowing her to build scalable AI deployments. Seema is equally adept in project management, teamwork, and leadership, making her effective in collaborative research settings. With hands-on experience in algorithm development for UAVs, driver monitoring, healthcare AI, and power line inspection, she demonstrates the ability to translate complex AI concepts into deployable, high-impact systems across diverse industries.
Publication Top Notes
Title: Capsule Networks for Computer Vision Applications: A Comprehensive Review
Authors: S. Choudhary, S. Saurav, R. Saini, S. Singh
Journal: Applied Intelligence, Springer, Vol. 53(19), pp. 21799–21826
Year: 2023
Citations: 24
Title: LPC-Det: Attention-Based Lightweight Object Detector for Power Line Component Detection in UAV Images
Authors: S. Choudhary, S. Saurav, P. Gidde, R. Saini, S. Singh
Journal: Computers and Electrical Engineering, Elsevier, Vol. 126, Article 110476
Year: 2025
Title: Benchmarking YOLO Object Detectors for Component Detection in Power Line Infrastructure: Dataset and Results
Authors: S. Choudhary, S. Saurav, R. Saini, S. Singh
Conference: International Conference on Computer Vision and Image Processing (CVIP).
Year: 2024
Conclusion
Seema Choudhary has established herself as a dedicated researcher in the domains of Computer Vision, Artificial Intelligence, and Deep Learning with strong applications in healthcare, UAV-based surveillance, and infrastructure monitoring. Her academic background in Electronics, Telecommunication, and VLSI Design, coupled with her professional experience at CSIR-CEERI, reflects her ability to bridge theory with practical innovations. Her research contributions, including a comprehensive review on Capsule Networks Applied Intelligence with significant citations, development of, and benchmarking YOLO-based detectors , highlight her expertise in designing efficient AI-driven systems for real-world applications. Recognized with honors such as the Sakura Science Program Fellowship from the Government of Japan, she continues to advance impactful solutions for automation, safety, and healthcare. With a strong skill set in deep learning frameworks, programming, and data handling, she stands as a promising researcher whose work contributes meaningfully to both academia and industry.