Jingquan Li | Records | Best Researcher Award

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Dr. Jingquan Li | Records | Best Researcher Award

Associate Professor at Hofstra University, United States

Dr. Jingquan Li is a distinguished academic with a broad range of expertise in computer science, business administration, and information technology. Dr. Li’s academic journey includes a Doctor of Philosophy in Business Administration with a supporting area in Computer Science (Artificial Intelligence and Data Science) from the University of Illinois at Urbana-Champaign, a Master of Science in Manufacturing Management from the College of Business and Innovation at the University of Toledo, and a Bachelor of Engineering in Computer Engineering from Xi’an Jiaotong University. With over a decade of experience in academia, Dr. Li has held various teaching positions, including Associate Professor at Hofstra University, Tenured Associate Professor at Texas A&M University-San Antonio, and Assistant Professor at both Texas A&M University-San Antonio and Texas A&M University-Kingsville. Dr. Li’s teaching portfolio includes a diverse range of courses such as Information Systems in Organizations, Business Analytics, and Data Mining and Text Mining.

Profile:

Education

Dr. Jingquan Li holds a Doctor of Philosophy in Business Administration with a supporting area in Computer Science (Artificial Intelligence and Data Science) from the University of Illinois at Urbana-Champaign, earned in 2004. Prior to this, Dr. Li completed a Master of Science in Manufacturing Management at the College of Business and Innovation, University of Toledo, in 1997. Dr. Li’s academic journey began with a Bachelor of Engineering in Computer Engineering from the School of Electronic and Information Engineering at Xi’an Jiaotong University, obtained in 1987. Dr. Li’s educational background reflects a strong foundation in both business administration and computer science, with a focus on information systems, artificial intelligence, and data science.

Work Experience:

Dr. Jingquan Li has an extensive academic and professional background. Since September 2017, Dr. Li has served as an Associate Professor at Hofstra University in New York. Prior to joining Hofstra, from September 2010 to August 2017, Dr. Li held the position of Tenured Associate Professor at Texas A&M University-San Antonio in Texas. Before achieving tenure, Dr. Li was an Assistant Professor at Texas A&M University-San Antonio from September 2009 to August 2010 and at Texas A&M University-Kingsville from September 2004 to August 2009. Dr. Li’s academic positions are complemented by substantial professional experience as a Computer Engineer at the North China Institute of Computing Technology in Beijing, China, from 1987 to 1995. This combined background has equipped Dr. Li with a comprehensive understanding of both academia and industry, enriching their teaching and research endeavors.

Teaching Interest:

Dr. Jingquan Li’s teaching portfolio encompasses a wide array of courses focused on computer concepts and software tools in business. These include courses such as Information Systems in Organizations, Business Analytics, Database Management, Systems Analysis and Design, Big Data Management, Data Mining and Text Mining, Data Visualization, Machine Learning and Deep Learning, Enterprise Systems, Telecommunications and Networking, Information Security and Privacy, Cyber Security, Programming Languages, and Health Informatics. Dr. Li’s expertise in these areas is underpinned by their academic background and professional experience, making them a versatile and knowledgeable educator in the field of computer science and business administration.

Research Interest:

Dr. Jingquan Li’s expertise extends across a broad spectrum of specialized topics within the realm of computer science and business administration. Dr. Li’s proficiency includes Information Security and Privacy, Cybersecurity, Business Analytics, Big Data Management, Data Mining and Text Mining, Online Social Networks, Health Information Technology, AI Ethics, public health management and policy, and the Economics of Information Sharing. This diverse range of subjects underscores Dr. Li’s comprehensive understanding of the intersection between technology and business, making them a valuable resource in academia and beyond.

Research and Grants:

Dr. Jingquan Li has secured a diverse range of grants and research funding throughout their career, demonstrating a strong commitment to advancing knowledge in various fields. These include upcoming projects such as “The Health Benefits and Social Effects of Exercise Games” funded by the Agency for Health Research and Quality, as well as past endeavors like “Ensuring Privacy of Personal Health Records (PHRs): A Health Record Trust Architecture” funded by the Texas Area 41 Institute, where Dr. Li served as the Principal Investigator. Other notable projects led by Dr. Li include “Students’ and Faculty’s Perceptions of Hybrid Courses: A Comparative Study,” which received funding from the Texas A&M University-San Antonio Research Award in 2009-2010. Additionally, Dr. Li has been involved in projects such as “Privacy-Enhancing Data Mining” at Texas A&M University-Kingsville in 2007 and “Business Measurement for Fraud Detection with Privacy Protection” funded by KPMG LLP and the KPMG Foundation in 2004. Dr. Li’s collaborative efforts have also been recognized, as seen in projects like “On the Development and Quantification of Privacy-Enhancing Data Mining Methods” and “Supply Chain Management: A Multi-Agent Approach,” both of which were Research Board Award recipients at the University of Illinois, where Dr. Li served as a Co-Principal Investigator with Michael Shaw as the Principal Investigator. Another notable collaboration was with Motorola Inc. on “Information Technology for Managing Global Supply Chain Networks,” which was funded through the Motorola Manufacturing Systems Research Grant in 1999.

Awards and Honors:

Dr. Jingquan Li has been recognized with several prestigious awards and honors for their outstanding contributions to teaching and scholarship. In 2010, Dr. Li received the College of Business Faculty Excellence in Teaching Award from Texas A&M University-San Antonio, acknowledging their exceptional skills in educating students. Additionally, Dr. Li was twice honored with the College of Business Faculty Excellence in Scholarship Award, in both 2010 and 2009, highlighting their significant contributions to research and academic scholarship. Dr. Li’s dedication to excellence in academia is further underscored by the Seymour Sudman Award, which they received in 1999 and 1998. This award recognizes individuals who have demonstrated excellence in research methodology and survey statistics, reflecting Dr. Li’s commitment to advancing knowledge in their field. Furthermore, Dr. Li was the recipient of the College of Commerce Fellowship at the University of Illinois at Urbana-Champaign in 1998, further highlighting their academic prowess and dedication to scholarly pursuits.

 

Anwesha Sarkar | Public Health |Best Researcher Award |

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Ms. Anwesha Sarkar, Public Health, Best Researcher Award

Ms. anwesha Sarkar at Indian Institute of Technology Patna, India

Anwesha Sarkar is a Ph.D. candidate in the Social Sciences Lab at the Indian Institute of Technology Patna. She holds a Master of Science degree in Geography from the University of Calcutta and a Bachelor of Science degree in Geography from Presidency University, Kolkata. Anwesha’s research interests lie in the intersection of geography, social sciences, and public health, with a focus on understanding the impact of neighborhood environments on women’s health. She has presented her work at various international conferences and workshops and has published papers in reputable journals. Anwesha is also a recipient of prestigious fellowships and grants, including a Ph.D. fellowship from the University Grants Commission (UGC). She is skilled in statistical analysis, GIS techniques, and various data analysis software.

Education:
  • Ph.D. Candidate in Social Sciences Lab, Indian Institute of Technology Patna (July 2021 – Present)
  • Master of Science in Geography, University of Calcutta, Kolkata, India (07/2017 to 08/2019), CGPA 4.41/6.00
  • Bachelor of Science in Geography, Presidency University, Kolkata, India (07/2014 to 06/2017), CGPA 7.51/10.00
  • Senior Secondary Examination, Bhavans Gangabux Kanoria Vidyamandir, Kolkata, India (2014), Percentage 91.75
  • Secondary Examination, Kendriya Vidyalaya No 2, Kolkata, India (2012), CGPA 10.0/10.0 .

Profile:

Research And Publication:

  • Published paper titled “A Comprehensive Trajectory Analyzing the Impact of Neighborhood on Women’s Health” in Health Care for Women International (2024).
  • Presented papers at various international conferences and workshops, including the International Conference on Social and Regional Resilience and the International Conference on Future Earth and Humanities.

Selected Cource And Workshops:

  • Attended workshops and courses on GIS tools and techniques, statistical data analysis using SPSS and R, qualitative techniques in geospatial sciences, and more.

Grant And Fellwship:

  • Awarded a Ph.D. fellowship by the UGC, with Junior Research Fellowship (07/2021 to 07/2023) and Senior Research Fellowship (08/2023 to 07/2026).
  • Qualified for the Junior Research Fellowship (UGC), India, in 2020, and the National Eligibility Test University Grants Commission (UGC), India, in 2019.

Internship:

  • Worked as a Recruitment Officer and Climate Counsellor at the International Centre for Culture & Education, contributing to the Green (R)evolution College Program and Global Certification Program.

Professional Membership:

  • Life member of the Indian Public Health Association (IPHA) since 08/2023.

Skills:

  • Proficient in statistical analysis (quantitative and mixed methods), cartographic techniques (remote sensing and GIS), and various data analysis software such as SPSS, STATA, R Programming, ArcMap, QGIS, Erdas Imagine, AutoCAD Map, and others.

Kalimuthu Marimuthu | Disease Prediction |Best Researcher Award

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Dr.Kalimuthu Marimuthu,  Disease Prediction, Best Researcher Award

 Dr. Kalimuthu Marimuthu at Gitam University, India

Dr. Kalimuthu Marimuthu is a distinguished academician and researcher with over 18 years of experience in the field of information technology. He holds a Ph.D. in Information Technology from Anna University, Chennai, where he was recognized for his highly commendable research. Dr. Marimuthu’s expertise spans various areas including big data analytics, cloud computing, data mining, and soft computing. He has contributed significantly to the academic community through his numerous publications in both national and international journals and conferences. With a strong commitment to excellence in education and research, Dr. Marimuthu continues to inspire and mentor students and professionals in the field of information technology.

Education:

Dr. Kalimuthu Marimuthu is a highly accomplished individual with a strong educational background. He obtained his Ph.D. (Doctor of Philosophy) from Anna University, Chennai, in April 2017, where he was recognized for his highly commendable research. Prior to his Ph.D., he completed his M.Tech. (Master of Technology) in Information Technology at Bharath University, Chennai, in May 2005, achieving a First Class with Distinction with a remarkable score of 8.4 out of 10. Earlier in his academic journey, Dr. Marimuthu earned his MCA (Master of Computer Applications) from Madras University, Chennai, in April 2002, securing a First Class with a notable percentage score of 66. These educational achievements underscore his dedication to academic excellence and his expertise in the field of information technology.

Profile:

Professional Experience:

Dr. Kalimuthu Marimuthu boasts a rich and diverse professional background in the field of information technology. Commencing his career journey as a Lecturer at SNS College of Technology (Autonomous) in Coimbatore in June 2005, he progressively advanced to higher positions, including Senior Lecturer, Assistant Professor, and Associate Professor. Throughout his career, Dr. Marimuthu has held various academic leadership roles, serving as the Academic Coordinator for implementing the Choice Based Credit System (CBCS), NBA Coordinator for the department, and overseeing Board of Studies and Head of Department (HOD) responsibilities. His contributions extend to quality assurance and enhancement initiatives, where he has served as the NAAC Coordinator and IQAC In charge for his college. Furthermore, Dr. Marimuthu actively engages in conducting workshops, seminars, and faculty development programs, demonstrating his commitment to the continuous professional development of his peers. With a prolific publication record in both national and international journals, Dr. Marimuthu’s research interests encompass a broad spectrum of topics, ranging from multi-class facial emotion recognition to gastric cancer classification and intelligent vision camera systems. Presently, as an Associate Professor at GITAM University, Bengaluru, Dr. Marimuthu continues to inspire students and fellow academics alike through his exemplary teaching, groundbreaking research, and effective administrative leadership.

Research interests:

Dr. Kalimuthu Marimuthu’s research interests encompass a broad spectrum of topics within the field of information technology. His focus areas include multi-class facial emotion recognition and gastric cancer classification using innovative approaches such as hybrid deep learning models. Additionally, Dr. Marimuthu is deeply engaged in the development of intelligent vision camera systems and their integration into smartphone architectures. Furthermore, he has a keen interest in big data analytics, cloud computing, operating systems, data mining, and soft computing, exploring these domains to uncover novel insights and solutions. Through his diverse research interests, Dr. Marimuthu demonstrates a commitment to advancing knowledge and technology in the ever-evolving landscape of information technology.

Publications:
  1. Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
    • Authors: A. Mogadala, M. Kalimuthu, D. Klakow
    • Journal: Journal of Artificial Intelligence Research (JAIR)
    • Citations: 126
    • Year: 2021
  2. Fusion models for improved image captioning
    • Authors: M. Kalimuthu, A. Mogadala, M. Mosbach, D. Klakow
    • Conference: International Conference on Pattern Recognition (ICPR)
    • Citations: 17
    • Year: 2021
  3. Automatic conversion of dialectal Tamil text to standard written Tamil text using FSTs
    • Authors: K. Marimuthu, SL Devi
    • Conference: Proceedings of the 2014 Joint Meeting of SIGMORPHON and SIGFSM
    • Citations: 8
    • Year: 2014
  4. A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task
    • Authors: M. Kalimuthu, F. Nunnari, D. Sonntag
    • Conference: ImageCLEF-2020
    • Citations: 7
    • Year: 2020
  5. Incremental domain adaptation for neural machine translation in low-resource settings
    • Authors: M. Kalimuthu, M. Barz, D. Sonntag
    • Conference: Association for Computational Linguistics (ACL)
    • Citations: 6
    • Year: 2019
  6. Named entity recognizer for Indian languages
    • Authors: SL Devi, CS Malarkodi, K. Marimuthu, C Chrompet
    • Conference: International Conference on Natural Language Processing (ICON)
    • Citations: 6
    • Year: 2013
  7. How human analyse lexical indicators of sentiments-a cognitive analysis using reaction-time
    • Authors: K. Marimuthu, SL Devi
    • Conference: Proceedings of the 2nd workshop on sentiment analysis where AI …
    • Citations: 4
    • Year: 2012
  8. Word boundary identifier as a catalyzer and performance booster for Tamil morphological analyzer
    • Authors: K. Marimuthu, K. Amudha, T. Bakiyavathi, SL Devi
    • Conference: Proceedings of 6th Language and Technology Conference, Human …
    • Citations: 2
    • Year: 2013
  9. Named entity recognizer for Indian languages (ICON NLP tool contest 2013)
    • Authors: SL Devi, CS Malarkodi, K. Marimuthu, C Chrompet
    • Conference: 10th International Conference on Natural Language Processing (ICON)
    • Citations: 1
    • Year: 2013