Nitika Dhingra | Health Professions | Best Researcher Award

Dr. Nitika Dhingra | Health Professions | Best Researcher Award

Chitkara University | India

Dr. Nitika Dhingra  is an academic and researcher at Chitkara University, Punjab, India, with expertise in machine learning–integrated sensor development, non-destructive spectroscopy, and RF-based sensing technologies. She holds a Ph.D. in Electronics and Communication Engineering from Chitkara University, supported by an M.Tech from Punjabi University and a B.Tech from Punjab Technical University. Her research advances applications in food adulteration detection, construction material classification, and structural health monitoring of heritage sites. She has contributed significantly as a Junior and Senior Research Fellow under a DST-SHRI scheme, focusing on sensor design, embedded systems, and machine learning integration. In 2024, she secured a DST-funded research grant worth 27 Lakhs as Principal Investigator, demonstrating her leadership in high-impact projects. Her scholarly contributions include 12 publications indexed in Scopus, 9 citations across 8 documents, and an h-index of 2, along with several granted and filed patents. She has been honored with the Gandhian Young Technological Innovation Award, DST Senior Research Fellowship, and the Best Paper Presentation Award at ICAMSE, and was a semi-finalist in the DST–Texas Instruments Innovation Challenge. Dr. Nitika Dhingra’s career exemplifies innovation, academic excellence, and impactful contributions to science and technology.

Profile: Scopus

Featured Publications

  • Dhingra, N., Saluja, N., Garg, R., & Kanwar, V. (2023). Radio frequency as a non-destructive approach to concrete structure health monitoring. Iranian Journal of Science and Technology, Transactions of Civil Engineering. Cited by: 3.

  • Dhingra, N., Ghosh, D., Saluja, N., & Sabapathay, T. (2023). Radio frequency based sensor for adulteration measurement in a continuous two phase-flow of alcoholic beverages. Sensing and Imaging, 24(1), 32. Cited by: 2.

  • Dhingra, N., Saluja, N., Kanwar, V., & Garg, R. (2021). Moisture sensitive electrical property measurement in concrete slab with step graded antenna. Materials Today: Proceedings, 45, 5172–5176. Cited by: 2.

  • Dhingra, N., & Saluja, N. (2024). RF sensor-based adulterant discriminant estimation in mustard oil. Sensing and Imaging, 25(1), 59. Cited by: 1.

  • Dhingra, N., & Saluja, N. (2024). A novel non-destructive technique-based automated classification of construction material using machine learning. Asian Journal of Civil Engineering, 25(1), 805–810. Cited by: 1.

  • Geetanjali, Jindal, P., Saluja, N., Kashyap, N., & Dhingra, N. (2023). Design and optimization of wideband RF energy harvesting antenna for low-power wireless sensor applications. Proceedings of International Conference on Data Science and Applications. Cited by: 1.

Niloofar Choobin | Health Professions | Best Researcher Award

Dr. Niloofar Choobin | Health Professions | Best Researcher Award

Hormozgan University of Medical Sciences | Iran

Dr. Niloofar Choobin is an accomplished Iranian researcher and healthcare informatics specialist, renowned for her pioneering work in artificial intelligence applications in healthcare. With a Master’s degree in Health Information Technology (expected 2025) and a strong academic foundation, she has emerged as a dynamic contributor to clinical decision support systems, digital health innovations, and AI-driven diagnostics. Her research spans key domains including cardiovascular health, oncology, and telemedicine. Recognized through multiple national awards and academic honors, she also serves as a mentor, workshop organizer, and reviewer for various research initiatives in Iran.

Author Profile👤

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Scopus

Strengths for the Awards✨

Niloofar Choobin stands out as a forward-thinking and technically adept researcher in the field of Health Information Technology, with a unique focus on AI-powered clinical diagnostics and digital health innovation. Her academic training—spanning a BSc and an ongoing MSc at Hormozgan University—has been translated into impactful research projects such as machine learning models for coronary artery disease and hypertension prediction using cohort data. She has presented her work at multiple national and international congresses and led workshops on systematic reviews and AI-driven healthcare tools, showcasing strong communication and mentoring abilities.

Her award history—including honors like the Top Researcher award, Innovation Finalist at the National Olympiad, and a 2nd place at the Health IT Innovation Festival—reinforces her standing as a leader among young Iranian researchers. Her cross-disciplinary expertise, including NLP, wearable tech, and IoT in medicine, bridges clinical and computational sciences. These achievements, along with her active involvement in peer review and academic organizing roles, reflect the hallmark of a researcher poised for global recognition.

🎓 Education

Niloofar completed her Bachelor of Science in Health Information Technology from Hormozgan University of Medical Sciences, Iran, in 2015. Currently, she is pursuing her Master of Science in Health Information Technology from the same institution (2023–2025), where her thesis focuses on the development and validation of machine learning models for early detection of coronary artery disease. Her academic path reflects a strong blend of theoretical learning and real-world clinical research applications.

💼 Experience

With a decade of progressive professional experience, Niloofar has held pivotal roles across Iran’s healthcare system. She currently serves as the Educational Affairs and Medical Student Coordinator at the Children’s Hospital in Bandar Abbas, where she facilitates medical education and research training. She has previously worked as a Medical Records Analyst at Chamran Trauma Hospital and as a Clinical Admissions Officer at Kosar Heart Hospital, demonstrating her extensive background in health data management and clinical informatics operations.

🧠 Research Interests On Health Professions

Niloofar’s research interests lie at the intersection of artificial intelligence and clinical medicine. She specializes in:

  • AI-powered clinical decision support

  • Machine learning models for cardiovascular and oncology diagnostics

  • Digital health innovations including IoT and smart monitoring

  • Natural language processing in medical documentation and text data

Her interdisciplinary approach bridges informatics, machine learning, and real-time patient care.

🏅 Awards

Niloofar’s innovative spirit has earned her numerous accolades. She was honored as the Top Researcher by the Hormozgan Student Research Committee (2014–2015) 🥇. In 2023, she was a finalist in the National Olympiad in Entrepreneurship and AI, and secured 2nd place at the National Health IT Innovation Festival in Mashhad (2022). She also won the Provincial Innovation Award in 2015, cementing her status as a promising researcher and innovator in digital health and AI.

📚 Publications

Niloofar has contributed to both academic literature and national congresses with a strong focus on AI applications in healthcare. Selected publications include:

  • Tracking Health: Wearable Technology in Cancer Care – A systematic review analyzing wearable solutions in oncology monitoring. (Published 2023)

  • Smart Post-Chemotherapy Care: IoT and AI-based Monitoring System for Breast Cancer Patients (Submitted, 2024)

  • Telemedicine in Hypertension Management During COVID-19 – A comprehensive review of remote care strategies during the pandemic. (Published 2022)

She has delivered numerous national/international presentations on topics such as:

  • VR in surgical simulations

  • OCT image analysis for cardiovascular diseases

  • Machine learning in PCO and osteosarcoma

  • Applications of ChatGPT in modern medicine

🧾 Conclusion

🔍 With a rare blend of technical depth, research acumen, and healthcare domain experience, Niloofar Choobin is a standout candidate for any prestigious research award in health informatics or AI in medicine. Her continued efforts to integrate machine learning into clinical workflows and her passion for digital transformation of healthcare highlight her future potential as a global thought leader in this field. From winning national competitions to mentoring future researchers, she embodies the qualities of innovation, dedication, and academic excellence.