Ms. Ahona Ghosh, Maulana Abul Kalam Azad University of Technology, West Bengal, India
Ahona Ghosh is a promising researcher in the field of Computer Science and Engineering with a focus on artificial intelligence, machine learning, and rehabilitation technologies. Currently completing her Ph.D. at Maulana Abul Kalam Azad University of Technology, West Bengal, Ahona has made significant strides in the academic and research community. Her work involves a blend of deep learning, cognitive rehabilitation, and IoT-based systems for improving quality of life. With several publications in prestigious international journals and conferences, she has earned recognition for her contributions to the scientific community. Ahona has been awarded the Best Paper Award for her work on IoT-based waste management and has ranked highly in various competitions like MAKATHON’22. She is passionate about leveraging technology for social good, particularly in healthcare and rehabilitation systems.
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Ms. Ahona Ghosh, Summary of Suitability
Dr. Ahona Ghosh is an outstanding candidate for the Research for Best Researcher Award, demonstrating exceptional academic accomplishments, innovative research contributions, and consistent excellence throughout her career. Her extensive academic background includes a Ph.D. in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology, West Bengal, with her pre-submission and viva completed, reflecting her advanced expertise and dedication to her field. She has received accolades for her academic and research endeavors, such as the Best Paper Award for her IoT-based waste management system and the Academic Excellence Award from Brainware University.
Her robust portfolio of research contributions includes an impressive array of international journal articles, conference papers, patents, and book chapters. Dr. Ghosh’s work spans cutting-edge topics such as deep learning, cognitive rehabilitation, IoT applications, and fuzzy systems, addressing societal challenges like healthcare, rehabilitation, and sustainable development.
Education
Ahona Ghosh has a strong academic background, with a Ph.D. in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology (MAKAUT), where she is in the final stages of her thesis submission. She completed her Master of Technology (M.Tech.) in the same field at MAKAUT in 2019, with a CGPA of 8.73. Her Bachelor’s degree in Computer Science and Engineering (B.Tech.) was awarded by Techno India College of Technology in 2017, where she achieved a CGPA of 7.66. Ahona’s early education includes Higher Secondary in Science from Taki House Government Sponsored Girls High School, with an aggregate of 67.4%. She also passed the Madhyamik Pariksha (Class 10) from Duff High School for Girls with a remarkable score of 82.88%. Ahona is also certified in NTA-NET for the years 2018 and 2019.
Professional Experience
Ahona Ghosh has worked extensively in academia and research, focusing on artificial intelligence, IoT, and healthcare applications. Currently, she is a Doctoral Fellow at Maulana Abul Kalam Azad University of Technology (MAKAUT). Her research includes contributions to cognitive rehabilitation using machine learning and EEG-based sensor systems. She has also been involved in various projects concerning IoT-based solutions for healthcare, such as designing smart systems for cognitive rehabilitation and enhancing data-driven rehabilitation methods. In addition, Ahona has been a part of multiple international conferences where she presented papers, co-authored patents, and contributed to the scientific community with impactful research. Her teaching experience includes mentoring undergraduate students and guiding research projects, as well as working on industry collaborations in technology development. Ahona’s expertise in both theoretical and applied aspects of Computer Science has shaped her as a versatile professional in the field.
Awards and Recognition
Ahona Ghosh has received several accolades for her academic and research achievements. She won the Best Paper Award at the IETE Eastern Zonal Seminar with ISF Congress in 2017 for her paper on “Waste Management System Based on Internet of Things (IoT)”. Her innovative contributions earned her the Academic Excellence Award from Brainware University in January 2020, based on exceptional student feedback. She also achieved 2nd place in the MAKATHON’22 competition organized by MAKAUT’s Innovation Council. Ahona’s recognition extends beyond awards, as she is a prominent figure in academic circles, having presented her research at several prestigious IEEE conferences. Her qualifications include passing the NTA-NET exams in 2018 and 2019, reinforcing her academic prowess. Ahona’s dedication to research and innovation continues to receive recognition, making her an influential presence in her field.
Ahona Ghosh has developed a comprehensive set of research skills, particularly in the areas of Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Rehabilitation. Her expertise extends to using IoT for healthcare applications, including creating systems for rehabilitative therapy and mental health analysis. Ahona is proficient in data analysis, algorithm design, and modeling for both real-time and research-driven applications. Her experience with neural networks, sensor systems, and signal processing further enhances her ability to tackle complex problems. Ahona has contributed to developing innovative frameworks using fuzzy logic, sensor networks, and electroencephalography (EEG) in health-related projects. She excels in academic writing, having published in numerous peer-reviewed journals and international conferences. Additionally, she is well-versed in patent filing, research methodology, and project management, which are crucial in carrying out high-impact scientific work.
Publication Top Notes
Scope of Sentiment Analysis On News Articles Regarding Stock Market and GDP in Struggling Economic Condition
- Authors: S Biswas, A Ghosh, S Chakraborty, S Roy, R Bose
Journal: International Journal of Emerging Trends in Engineering Research, 8 (7), 3594
Citation: 30
Year: 2020
A Detailed Study on Data Centre Energy Efficiency and Efficient Cooling Techniques
- Authors: D Mukherjee, S Chakraborty, I Sarkar, A Ghosh, S Roy
Journal: International Journal of Advanced Trends in Computer Science and Engineering
Citation: 26
Year: 2020
Recognition of hand gesture image using deep convolutional neural network
- Authors: KM Sagayam, AD Andrushia, A Ghosh, O Deperlioglu, AA Elngar
Journal: International Journal of Image and Graphics, 22 (03), 2140008
Citation: 22
Year: 2022
Service aware resource management into cloudlets for data offloading towards IoT
- Authors: D Guha Roy, B Mahato, A Ghosh, D De
Journal: Microsystem Technologies, 1-15
Citation: 21
Year: 2022
Mathematical modelling for decision making of lockdown during COVID-19
- Authors: A Ghosh, S Roy, H Mondal, S Biswas, R Bose
Journal: Applied Intelligence
Citation: 17
Year: 2021
Secured Energy-Efficient Routing in Wireless Sensor Networks Using Machine Learning Algorithm: Fundamentals and Applications
- Authors: A Ghosh, CC Ho, R Bestak
Journal: Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
Citation: 12
Year: 2020
A survey on Internet-of-Thing applications using electroencephalogram
- Authors: D Chakraborty, A Ghosh, S Saha
Book: Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach, 21-47
Citation: 12
Year: 2020
Rehabilitation using neighbor-cluster based matching inducing artificial bee colony optimization
- Authors: S Saha, A Ghosh
Conference: 2019 IEEE 16th India Council International Conference (INDICON), 1-4
Citation: 12
Year: 2019
Dtnma: identifying routing attacks in delay-tolerant network
- Authors: S Chatterjee, M Nandan, A Ghosh, S Banik
Book: Cyber Intelligence and Information Retrieval: Proceedings of CIIR 2021, 3-15
Citation: 11
Year: 2022
Emotion detection using generative adversarial network
- Authors: S Das, A Ghosh
Book: Generative Adversarial Networks and Deep Learning, 165-182
Citation: 10
Year: 2023