Arti Singh | Machine learning | Best Researcher Award

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Mrs. Arti Singh | Machine learning | Best Researcher Award

Assistant Professor at DYPIEMR, India

Mrs. Arti Singh is an accomplished academician and researcher with a robust background in Computer Science, Artificial Intelligence, and Data Science. She is currently serving as an Assistant Professor at Dr. D Y Patil Institute of Engineering Management and Research. With a passion for teaching and research, her expertise lies in machine learning, sentiment analysis, data science, and computational intelligence. Mrs. Singh has presented and published several research papers at national and international conferences. She is committed to continuous learning, having completed various industry-relevant certifications and training programs.

Publication Profile

Google Scholar

Educational Details

  • M.Tech in Computer Technology and Applications from National Institute of Technical Teachers’ Training and Research (RGPV, Bhopal) – 2016 (CGPA: 8.69)
  • B.E. in Computer Science Engineering from Sagar Institute of Research Technology and Science (RGPV, Bhopal) – 2014 (CGPA: 8.35)

Professional Experience

  • Assistant Professor in the Department of Artificial Intelligence and Data Science at Dr. D Y Patil Institute of Engineering Management and Research since July 1, 2022.
  • Lecturer in the Computer Department at Marathwada Mitra Mandal Polytechnic College.
  • Assistant Professor at Sri Sai Shail Manglam College, Singrauli (June 1, 2019, to June 30, 2021).
  • Resource Person for the B.C.A Vocational course at Babasaheb Bhimrao Ambedkar Bihar University, Muzaffarpur (May 30, 2017, to May 27, 2019).

Research Interest

  • Data Science
  • Machine Learning
  • Software Engineering
  • Operating Systems
  • Quantum Artificial Intelligence
  • Pattern Recognition
  • Computational Intelligence

Top Noted Publication

An Opinion Mining for Indian Premier League Using Machine Learning Techniques

  • Authors: KP Dubey, S Agrawal
  • Conference: 2019 4th International Conference on Internet of Things: Smart Innovation, Usage, and Application
  • Pages: 25
  • Year: 2019
  • Summary: This paper presents a sentiment analysis model for social media data related to the Indian Premier League (IPL). The authors employed machine learning techniques to classify public opinions, enabling better understanding of audience engagement and predicting trends in sports sentiment.

Comparing Classification and Regression Tree and Support Vector Machine for Analyzing Sentiments for IPL

  • Author: Arti Singh
  • Journal: International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC)
  • Volume: 4
  • Issue: 6
  • Pages: 172-175
  • Year: 2016
  • ISSN: 2321-8169
  • Summary: This study compares the performance of two machine learning algorithms, Classification and Regression Tree (CART) and Support Vector Machine (SVM), for sentiment analysis on IPL data. The research evaluates the accuracy and effectiveness of both approaches for sports sentiment analysis.

AI Application in Production

  • Author: Arti Singh
  • Publisher: Taylor & Francis
  • Book Title: Industry 4.0: Enabling Technologies and Applications
  • Chapter: AI Application in Production
  • Year: 2024
  • URL: Link to book
  • Summary: This book chapter explores the integration of Artificial Intelligence (AI) in manufacturing and production processes. It highlights AI-driven innovations, predictive maintenance, process optimization, and intelligent automation in modern industrial setups.

Automated Invoice Data Extraction: Advancements and Challenges in OCR-Based Approaches

  • Authors: Arti Singh, Sneha Kanwade, Siddhant Shendge, Amoksh Layane, Kohsheen Tikoo
  • Journal: International Journal of Scientific Research in Engineering and Management (IJSREM)
  • Volume: 8
  • Pages: 1-6
  • ISSN: 2582-3930
  • Year: 2024
  • Summary: This paper addresses the growing need for automated invoice data extraction using Optical Character Recognition (OCR) technologies. It discusses the latest advancements, the challenges faced, and potential solutions to enhance accuracy in invoice processing systems.

An In-Depth Analysis of Sentiment Polarity Using Various Machine Learning Algorithms

  • Author: Arti Singh
  • Conference: 8th International Conference on ISDIA 2024
  • Volume: 1107
  • Pages: 157–167
  • Year: 2024
  • Summary: This research investigates the effectiveness of different machine learning algorithms for sentiment polarity detection. The study evaluates models such as SVM, Random Forest, and Extremely Randomized Trees to improve sentiment classification accuracy in social media data.

Comparative Study of Machine Learning Algorithms for Sentiment Polarity

  • Author: Arti Singh
  • Conference: IRF International Conference
  • Pages: 1-5
  • Year: 2017
  • Summary: The paper compares several machine learning techniques, including Naive Bayes, Decision Trees, and SVM, for sentiment polarity classification. It emphasizes the importance of selecting the appropriate algorithm for accurate sentiment detection in online text data.

Conclusion:

Mrs. Arti Singh is a strong candidate for the Best Researcher Award, given her consistent research output in machine learning and applied AI domains, industry-relevant research contributions, and dedication to academic excellence. Her work bridges the gap between theory and practice, making her a valuable contributor to the field of computational intelligence and Industry 4.0 applications.

With increased focus on high-impact journals, research funding, and industry collaborations, she has the potential to emerge as a leading figure in her field. Therefore, she is highly deserving of recognition through the Best Researcher Award.

 

 

Isobel French | Cognitive Neuroscience | Best Researcher Award

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Ms. Isobel French | Cognitive Neuroscience | Best Researcher Award

Postgraduate researcher at National Central University, Taiwan

Ms. Isobel French is a Ph.D. candidate in Interdisciplinary Neuroscience, majoring in Cognitive Neuroscience at the National Central University and Academia Sinica, Taiwan. She holds a Master’s in Medical Science from the University of Malaya and a Bachelor’s in Biomedical Science from Management and Science University, Malaysia. Her research focuses on the neural mechanisms underlying Parkinson’s Disease and other neurodegenerative conditions, utilizing EEG and advanced analytical methods to develop early biomarkers for clinical diagnostics.

Publication Profile

Scopus

Orcid

Educational Details

  • BSc (Hons) in Biomedical Science, Management and Science University (MSU), Malaysia; CGPA: 3.26 (May 2008 – Jul 2012).
  • Master’s in Medical Science (Distinction), University of Malaya (UM), Malaysia; CGPA: 3.75 (Nov 2015 – Dec 2017, awarded Feb 2019).
  • Ph.D. Candidate in Interdisciplinary Neuroscience (major in Cognitive Neuroscience), Visual Cognitive Laboratory, Institute of Cognitive Neuroscience, National Central University & Academia Sinica, Taiwan (Sep 2020 – expected Jun 2025).

Professional Experience

Ms. Isobel French is a Ph.D. candidate and researcher at the Visual Cognitive Laboratory, Institute of Cognitive Neuroscience, National Central University and Academia Sinica, Taiwan. She is involved in interdisciplinary research focusing on cognitive neuroscience, neurodegenerative diseases, and advanced EEG analysis techniques. She has received training and internships under the guidance of academic professionals and neurosurgeons across Malaysia and Taiwan. Her work aims to bridge neuroscience and clinical applications, especially in neurodegenerative disease diagnosis and progression assessment.

Research Interest

  • Cognitive neuroscience
  • Neurodegenerative disorders (Parkinson’s Disease and Alzheimer’s Disease)
  • Brain imaging techniques (EEG, Diffusion Tensor Imaging, Tractography)
  • Nonlinear analytical methods (Holo-Hilbert Spectral Analysis)
  • Biomarkers for neurological diseases

Author Metric:

  • Publications in peer-reviewed journals: 6
  • Research focus: Parkinson’s Disease, Alzheimer’s Disease, Cognitive Neuroscience
  • Collaborations with international research teams
  • Published in high-impact journals including Frontiers in Aging Neuroscience, Movement Disorders, and NeuroImage: Reports

Top Noted Publication

  • French, I.T., & Muthusamy, K.A. (2016). A review of sleep and its disorders in patients with Parkinson’s disease in relation to various brain structures. Frontiers in Aging Neuroscience, 8, Article 114. https://doi.org/10.3389/fnagi.2016.00114

  • French, I.T., & Muthusamy, K.A. (2018). A review of the pedunculopontine nucleus in Parkinson’s disease. Frontiers in Aging Neuroscience, 10, Article 99. https://doi.org/10.3389/fnagi.2018.00099

  • Chang, K.H., French, I.T., Liang, W.K., Lo, Y.S., Wang, Y.R., Cheng, M.L., & Juan, C.H. (2022). Evaluating the different stages of Parkinson’s disease using electroencephalography with Holo-Hilbert spectral analysis. Frontiers in Aging Neuroscience, 14, 832637. https://doi.org/10.3389/fnagi.2022.832637

  • Chu, K.T., Lei, W.C., Wu, M.H., Fuh, J.L., Wang, S.J., French, I.T., & Juan, C.H. (2023). A holo-spectral EEG analysis provides early detection of cognitive decline and predicts the progression to Alzheimer’s disease. Frontiers in Aging Neuroscience, 15. https://doi.org/10.3389/fnagi.2023.1163472

  • Lee, C.H., Juan, C.H., Chen, H.H., Hong, J.P., Liao, T.W., French, I.T., & Chang, K.H. (2024). Long‐range temporal correlations in electroencephalography for Parkinson’s disease progression. Movement Disorders. https://doi.org/10.1002/mds.30052

Conclusion

Ms. Isobel French is a highly suitable candidate for the Best Researcher Award, particularly in Cognitive Neuroscience and Neurodegenerative Disease Research. Her cutting-edge work in EEG biomarkers and disease progression analysis places her at the forefront of this critical research area. While she would benefit from increased leadership roles and grant achievements, her research quality, technical innovation, and translational potential make her a compelling nominee.