Mrs. Mandana Sadatghafourian, Ferdowsi University of Mashhad, Iran
Mandana Sadat Ghafourian is a dedicated biomedical engineer 🎓 with a B.Sc. (Ranked 1st), M.Sc., and ongoing Ph.D. in Biomedical Engineering from prestigious Iranian institutions 🇮🇷. She specializes in machine learning 🤖, neuroscience 🧠, signal/image processing 📊, and deep learning. A lecturer at Sajjad University, she has led groundbreaking projects, including Alzheimer’s diagnosis and seizure prediction using AI. Recognized with the Eiffel France Scholarship 🇫🇷 and National Elites Foundation honors, her work spans publications, workshops, and technical supervision in medical equipment. Fluent in English and Persian, she enjoys basketball 🏀, swimming 🏊, and music 🎶.
Publication Profile
Google Scholar
Education 🎓
Mandana Sadat Ghafourian has an impressive academic background in Biomedical Engineering. She earned her B.Sc. (Ranked 1st among 69 students) from Sajjad University, Mashhad, Iran (2011-2015) 🏅, with a GPA of 17.69. She pursued her M.Sc. at Khajeh Nasir University of Technology, Tehran, Iran (2015-2017) 📚, achieving a GPA of 16.61. Currently, she is completing her Ph.D. at Ferdowsi University of Mashhad (2018–Present) 📖, with a GPA of 17.57. Mandana also conducted a one-year doctoral research project in Neuroscience 🧠 at the University of Picardy Jules Verne, Amiens, France 🌍, supported by a joint Iran-France Scholarship.
Fields of Interest 🌟
Mandana Sadat Ghafourian is deeply passionate about advancing technology and science in several cutting-edge fields. Her interests include Machine Learning and Artificial Intelligence 🤖, where she explores intelligent systems and predictive models. She is equally engaged in Neuroscience 🧠, delving into brain functions and neural dynamics. Mandana specializes in Signal and Image Processing 📊, working on innovative techniques to analyze complex biomedical data. Her expertise extends to EEG and ECG 🩺, focusing on brain and heart signal analysis, and she is proficient in Deep Learning 📈, leveraging neural networks to solve complex biomedical engineering challenges.
Teaching Experience 🎓
Mandana Sadat Ghafourian has an extensive teaching portfolio in biomedical engineering and related fields. She has conducted courses on Brain Signal Processing 🧠 and Python to Deep Learning 💻 at Sajjad University. Mandana has led hands-on workshops, including EEG Brain Signal Recording 📊 at Khavaran University and Artificial Intelligence Applications 🤖 at Mashhad University of Medical Sciences. Her experience includes teaching Physiology Laboratory Courses 🧪, Hospital and Medical Clinic Equipment 🏥, and Bioelectric Phenomena ⚡ at Sajjad University. Additionally, she has developed curricula and taught Electrical Safety in Hospitals ⚕️, Electronics, and Linear Control courses, showcasing her academic versatility.
Honors and Awards 🏆
Mandana Sadat Ghafourian has earned several prestigious accolades during her academic journey. She ranked 1st overall in her Bachelor’s degree program among 69 students 🥇. Her exceptional performance granted her admission to the Ph.D. program through the Outstanding Talent pathway 🎓. Mandana was also selected as a National Elites Foundation scholar 🌟 at Ferdowsi University of Mashhad during the 2019-2020 academic year. Adding to her achievements, she was awarded the esteemed Eiffel France Scholarship 🇫🇷 in 2019, reflecting her dedication and excellence in biomedical engineering and research.
Work Experience 💼
Mandana Sadat Ghafourian has a robust professional background in biomedical engineering and education. She served as a Medical Equipment Specialist at Mashhad University of Medical Sciences from 2018 to 2020 🏥. Since 2018, she has been a dedicated Lecturer at Sajjad University 🎓, where she has delivered Python to Deep Learning courses and conducted three Signal Processing courses 💻. Additionally, she works as a Technical Supervisor for the production and distribution of medical equipment, a role she has held since 2018 and 2021, respectively 🔧. Her expertise bridges academia and industry with a focus on innovation and practical application.
Research Focus 🔬💻
Mandana Sadat Ghafourian’s research centers on biomedical engineering, signal processing, and artificial intelligence. She has extensively explored medical applications of machine learning, including optimizing anesthesia systems using fuzzy logic 🤖, diagnosing obstructive sleep apnea through HRV signal processing 🫁, and developing neural network-based models for controlling Hepatitis B infections 🧬. Her work also delves into epilepsy prediction and seizure detection using deep learning and EEG signal analysis 🧠. Additionally, she has investigated stress and anxiety control through Q-learning models 🩺. Her interdisciplinary approach bridges neuroscience, AI, and biomedical signal processing, focusing on innovative healthcare solutions. 🌟
Publication Top Notes
- Applying GA optimization algorithm for interval type-2 Fuzzy logic controller parameters of multivariable anesthesia system
Cited by: 6 🔢 | Year: 2018 📅
- Obstructive sleep apnea syndrome diagnosis using HRV signal processing
Cited by: 4 🔢 | Year: 2019 📅
- Controlling Hepatitis B virus infection using PID like neural network
Cited by: 1 🔢 | Year: 2019 📅
- Predicting Epilepsy and Deep Learning
Year: 2021 📅
- Predicting Epilepsy and Deep Learning. Some Aspects of Epilepsy
Year: 2021 📅
- Glucose Control Level Using Radial Basis Function Network and Gradient Descent
Year: 2020 📅
- P81: Detection of Epileptic Seizures Using EEG Signal Processing
Year: 2018 📅
- Stress Detection and Control According to the Skin Signal of Electrical Resistance and Heart Rate Using Reinforcement Learning
Year: 2018 📅
- Designing an intelligence model for seizure prediction using ECG signal
Year: 2017 📅
- P14: Anxiety Control Using Q-Learning
Year: 2016 📅
- The 2nd International Neuroinflammation Congress and 2nd Student Festival of Neuroscience
- The Third International Anxiety Congress
Conclusion
Mrs. Mandana Sadat Ghafourian is an outstanding candidate for the Research for Best Researcher Award. Her exemplary academic record, impactful research, teaching contributions, and practical applications in biomedical engineering and neuroscience make her a deserving nominee. 🌟