Pritpal Singh | Ambiguous set theory | Best Researcher Award

Dr. Pritpal Singh | Ambiguous set theory | Best Researcher Award

Pritpal Singh is an Assistant Professor at the Department of Data Science and Analytics, Central University of Rajasthan, India. He earned his Ph.D. in Computer Science and Engineering from Tezpur (Central) University in 2015 and has held various academic and research positions in India, Taiwan, and Poland. His expertise includes soft computing, optimization algorithms, time series forecasting, image analysis, and machine learning. He has published extensively in high-impact journals like IEEE Transactions, Elsevier, and Springer. His research focuses on advanced computational techniques, including quantum-based optimization and fMRI data analysis. Dr. Singh has received prestigious research fellowships, including a Postdoctoral Fellowship from Taiwan’s Ministry of Science and Technology and an International Visiting Research Fellowship from Poland’s Foundation for Polish Science. His work significantly contributes to artificial intelligence, data science, and computational modeling, making him a key figure in these fields. 🚀📊📚

Profile

Education 🎓

Dr. Pritpal Singh obtained his Ph.D. in Computer Science and Engineering from Tezpur (Central) University, Assam, India, in 2015, specializing in soft computing applications for time series forecasting. He completed his Master in Computer Applications (MCA) from Dibrugarh University, Assam, in 2008, following a B.Sc. in Physics, Chemistry, and Mathematics from the same university in 2005. His academic journey began with Higher Secondary (2002) from the Assam Higher Secondary Education Council and HSLC (1999) from the Secondary Education Board of Assam. His doctoral dissertation focused on improving fuzzy time series forecasting models through hybridization with neural networks and optimization techniques like particle swarm optimization. His strong foundation in computational sciences, mathematics, and engineering has shaped his research in AI-driven predictive modeling, optimization, and data analytics. 🎓📚🔬

Experience 👨‍🏫

Dr. Singh has extensive academic and research experience. He is currently an Assistant Professor at the Central University of Rajasthan (since June 2022). Previously, he was an Assistant Professor at CHARUSAT University, Gujarat (2015-2019), and a Lecturer at Thapar University, Punjab (2013-2015). His research experience includes serving as an Adjunct Professor (Research) at Jagiellonian University, Poland (2020-2022) and a Postdoctoral Research Fellow at National Taipei University of Technology, Taiwan (2019-2020). Throughout his career, he has mentored students, led research projects, and contributed significantly to data science, artificial intelligence, and computational modeling. His global exposure has enriched his expertise in optimization, machine learning, and interdisciplinary AI applications. 🌍📊

Research Interests 🔬

Dr. Singh’s research revolves around ambiguous set theory, optimization algorithms, time series forecasting, image analysis, and machine learning. He specializes in hybrid computational techniques, particularly quantum-based optimization and soft computing applications. His work extends to fMRI data analysis, mathematical modeling, and simulation. His research has been published in leading journals such as IEEE Transactions on Systems, Elsevier’s Information Sciences, and Artificial Intelligence in Medicine. His focus on interdisciplinary AI applications, particularly in healthcare and data science, has positioned him as a key contributor to advancing machine learning methodologies. 🧠📊🤖Awards & Recognitions 🏅

Dr. Singh has received multiple prestigious fellowships and recognitions. In 2019, he was awarded a Postdoctoral Research Fellowship by the Ministry of Science and Technology, Taiwan. In 2020, he received the International Visiting Research Fellowship from the Foundation for Polish Science, Poland. His contributions to artificial intelligence, optimization, and data science have been recognized globally through research grants, invited talks, and publications in top-tier journals. His work in soft computing and AI-driven predictive modeling continues to impact both academic and industrial research. 🏅🎖️📜

Publications 📚

  • Scopus 1-2023: P. Singh, An investigation of ambiguous sets and their application to
    decision-making from partial order to lattice ambiguous sets. Decision Analytics
    Journal (Elsevier), 08, 100286, 2023.
  • Scopus 2-2023: P. Singh, A general model of ambiguous sets to a single-valued ambiguous numberswith aggregation operators. Decision Analytics Journal (Elsevier), 08,
    100260, 2023.
  • Scopus 3-2023: P. Singh, Ambiguous set theory: A new approach to deal with unconsciousness and ambiguousness of human perception. Journal of Neutrosophic and
    Fuzzy Systems (American Scientific Publishing Group), 05(01), 52–58, 2023.
  • Scopus 4-2022: P. Singh, Marcin W ˛atorek, Anna Ceglarek, Magdalena F ˛afrowicz, and
    Paweł O´swi˛ecimka, Analysis of fMRI Time Series: Neutrosophic-Entropy Based
    Clustering Algorithm. Journal of Advances in Information Technology, 13(3), 224–
    229, 2022.

Raveendra Pilli | Image Processing | Best Researcher Award

Mr. Raveendra Pilli | Image Processing | Best Researcher Award

He mentored B.Tech. projects focused on the early detection of Alzheimer’s Disease. One project involved utilizing multi-modality neuroimaging techniques, where MRI and PET images were collected from the OASIS database, preprocessed, and robust features were extracted for classification. MATLAB and the SPM-12 toolbox were used for this task. Another project focused on the early detection of Alzheimer’s Disease using deep learning networks, where an MRI dataset from the ADNI database was collected, preprocessed, and the performance was compared with baseline algorithms. For this project, he used MATLAB and Python.

NIT-Silchar, India

Profile

Education

A dedicated research scholar with a Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Silchar (Thesis Submitted, CGPA 9.0), specializing in brain age prediction and early detection of neurological disorders using neuroimaging modalities. With extensive teaching experience, a strong passion for research, and a proven ability to develop engaging curricula, deliver effective lectures, and guide students toward academic success, I am committed to contributing to the field through research, publications, and presentations. My academic journey includes an M.Tech. from JNTU Kakinada (76.00%, 2011) and a B.Tech. from JNTU Hyderabad (65.00%, 2007), along with a strong foundational background in science, having completed 10+2 (MPC) with 89.00% in 2003 and SSC with 78.00% in 2001.

Work experience

He worked as a Junior Research Fellow at the National Institute of Technology, Silchar, Assam, from July 2021 to June 2023, where he assisted professors with course delivery for Basic Electronics, conducted laboratory sessions, graded assignments, and provided office hours for student support. From July 2023 to December 2024, he served as a Senior Research Fellow at the same institute, taking on additional responsibilities, including mentoring B.Tech. projects and assisting with Digital Signal Processing laboratory duties. Prior to his research roles, he was an Assistant Professor at SRK College of Engineering and Technology, Vijayawada, Andhra Pradesh, where he taught courses such as Networks Theory, Digital Signal Processing, RVSP, SS, and LICA. He utilized innovative teaching methods, including active learning techniques, to enhance student engagement and learning outcomes. He also mentored undergraduate research projects in image processing and received positive student evaluations for his teaching effectiveness.

Publication

Ling Mei | Cognitive Science | Best Researcher Award

Dr. Ling Mei | Cognitive Science | Best Researcher Award

Doctorate at Wuhan University of Science and Technology, China

Dr. Ling Mei is an accomplished researcher in artificial intelligence and cognitive science, with a robust academic and professional background. He holds a Ph.D. in Engineering from Sun Yat-sen University, one of China’s top universities, and completed a prestigious visiting scholar program at the University of British Columbia (UBC). Currently serving as a tenured faculty and master’s supervisor, Dr. Mei has published 16 papers, including 7 in SCI-indexed journals, contributed to nine books, and has three national invention patents granted. Recognized as a Provincial Research Talent of China in 2024, he work integrates advanced computational models with societal needs, such as urban planning and public safety. Dr. Mei has collaborated internationally with top-tier institutions like UBC and Carnegie Mellon University, cementing he reputation as a leader in he field.

Profile

Google Scholar

Orcid

Education 🎓

Dr. Mei earned he Ph.D. in Engineering from Sun Yat-sen University in 2021, a prestigious institution ranked among China’s top 10 universities. He academic journey also includes a year-long visiting scholar program at the Department of Computer Science, UBC, as part of the National Outstanding Young Researchers Program. This international exposure provided he with cutting-edge knowledge and interdisciplinary skills, enabling he to excel in artificial intelligence and cognitive science.

Work Experience 💼

Currently, Dr. Mei is a tenured faculty member and master’s supervisor at a leading Chinese university. He experience includes overseeing multiple research projects, consulting on seven industry-sponsored projects, and serving as a reviewer for the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY. He has also been instrumental in fostering international collaborations with institutions like UBC and CMU, contributing to impactful research publications and patents.

Awards and Honors

In 2024, Dr. Mei was recognized as a Provincial Research Talent of China, highlighting he exceptional contributions to science and technology. He has also earned accolades through he impactful patents and high-quality publications.

Research Interests

Dr. Mei’s research focuses on artificial intelligence, pedestrian trajectory prediction, and public safety strategies. He innovations include the LSN-GTDA framework, which integrates behavioral and stochastic factors for better uncertainty management. He interdisciplinary approach bridges cognitive science, computational models, and societal applications, ensuring he work’s relevance and impact.

Research Skills

Dr. Mei possesses advanced skills in AI modeling, thermal diffusion processes, and signal and system theory. He expertise includes patent development, SCI journal publications, and interdisciplinary collaborations. He is adept at integrating computational techniques with practical applications, as seen in he trajectory prediction research.

📚 Publications

Crowd Density Estimation via Global Crowd Collectiveness Metric

  • Journal: Drones
  • Date: 2024-10-28
  • DOI: 10.3390/drones8110616
  • Contributors: Ling Mei, Mingyu Yu, Lvxiang Jia, Mingyu Fu

More Quickly-RRT: Improved Quick Rapidly-Exploring Random Tree Star Algorithm Based on Optimized Sampling Point with Better Initial Solution and Convergence Rate*

  • Journal: Engineering Applications of Artificial Intelligence
  • Date: 2024-07
  • DOI: 10.1016/j.engappai.2024.108246
  • Contributors: Xining Cui, Caiqi Wang, Yi Xiong, Ling Mei, Shiqian Wu

Learning Domain-Adaptive Landmark Detection-Based Self-Supervised Video Synchronization for Remote Sensing Panorama

  • Journal: Remote Sensing
  • Date: 2023-02-09
  • DOI: 10.3390/rs15040953
  • Contributors: Ling Mei, Yizhuo He, Farnoosh Fishani, Yaowen Yu, Lijun Zhang, Helge Rhodin

Illumination-Invariance Optical Flow Estimation Using Weighted Regularization Transform

  • Journal: IEEE Transactions on Circuits and Systems for Video Technology
  • Date: 2020-02
  • DOI: 10.1109/TCSVT.2019.2890861
  • Contributors: Ling Mei, Jianhuang Lai, Xiaohua Xie, Junyong Zhu, Jun Chen

Feature Visualization Based Stacked Convolutional Neural Network for Human Body Detection in a Depth Image

  • Type: Book Chapter
  • Year: 2018
  • DOI: 10.1007/978-3-030-03335-4_8
  • Contributors: Xiao Liu, Ling Mei, Dakun Yang, Jianhuang Lai, Xiaohua Xie

Conclusion 

Dr. Ling Mei is a strong contender for the Best Researcher Award due to he robust academic background, impactful research, and significant contributions to AI and cognitive science. To further enhance he candidacy, increasing citation influence and emphasizing community impact would solidify he position as an exemplary researcher deserving of recognition. 🌟