Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools.Ā šŸŒšŸ“ŠšŸ”¬

Publication Profiles

Googlescholar

Education and Experience

Education

  • šŸŽ“Ā Ph.D. in Information Technology, University of Nebraska, 2010
  • šŸŽ“Ā M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • šŸŽ“Ā B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • šŸ“šĀ Tenured Associate Professor, Penn State Great Valley (2019ā€“Present)
  • šŸ“šĀ Assistant Professor, Penn State Great Valley (2013ā€“2019)
  • šŸ”¬Ā Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011ā€“2013)
  • šŸ’»Ā Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010ā€“2011)
  • šŸ› ļøĀ Project Assistant, IIT Kharagpur (2001ā€“2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship.Ā šŸŒŸšŸ”

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work inĀ data miningĀ andĀ machine learningĀ aims to uncover patterns and develop predictive models for diverse applications. InĀ bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends toĀ cybersecurity, where he explores cryptographic techniques to enhance internet security, andĀ distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridgesĀ artificial intelligence,Ā predictive analytics, andĀ software engineeringĀ to create impactful solutions.Ā šŸŒšŸ”¬šŸ“Š

Awards and Honors

  • šŸ†Ā Awarded research grants for innovative bioinformatics tools.
  • šŸ“œĀ Recognized for contributions to cybersecurity and internet authentication.
  • šŸŒŸĀ Acknowledged as a leading researcher in predictive analytics and machine learning.
  • šŸ“ŠĀ Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detectionĀ  ā€“Ā Cited by 93, 2021Ā šŸ“ŠšŸ“š
  • LocSigDB: A database of protein localization signalsĀ  ā€“Ā Cited by 49, 2015Ā šŸ§¬šŸ“–
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genesā€“Ā Cited by 46, 2020Ā šŸ§ŖšŸ“Š
  • Mining for class-specific motifs in protein sequence classificationĀ ā€“Ā Cited by 29, 2013Ā šŸ”¬šŸ“œ
  • Web app security: A comparison and categorization of testing frameworksā€“Ā Cited by 27, 2017Ā šŸ”’šŸ–„ļø
  • MetaID: A novel method for identification and quantification of metagenomic samplesĀ ā€“Ā Cited by 23, 2013Ā šŸŒšŸ”
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellersĀ ā€“Ā Cited by 21, 2019Ā āœˆļøšŸ§ 
  • Cybersecurity for AI systems: A surveyĀ ā€“Ā Cited by 20, 2023Ā šŸ¤–šŸ”

Dr. Fatemeh Aghagoli | Machine Learning Awards | Best Researcher Award

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Dr. Fatemeh Aghagoli | Machine Learning Awards | Best Researcher Award

Dr. Fatemeh Aghagoli, Iran University of Science and Technology, IranĀ 

šŸŽ“ Fatemeh Aghagoli is a Ph.D. student at the Iran University of Science and Technology, specializing in Mathematics and Computer Science. She is affiliated with the Faculty of Mathematics and Computer Science and is a member of the National Elite Foundation of Iran, recognized for her academic excellence. šŸ” Her primary research interests encompass machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling, particularly focusing on applications in medical science. šŸŒ Actively contributing to cutting-edge research initiatives, Fatemeh leverages her expertise to address complex challenges in medical science, aiming to advance diagnostics and treatment methodologies. šŸ“Š With a commitment to interdisciplinary applications, she has demonstrated exceptional academic prowess and a dedication to pushing the boundaries of knowledge in her field.

Professional Profile:

Google Scholar

šŸŽ“ Education:

Fatemeh Aghagoli is a Ph.D. student at the Iran University of Science and Technology, specializing in Mathematics and Computer Science. She is also a member of the National Elite Foundation of Iran, recognizing her academic excellence.

šŸ” Research Interests:

Fatemeh’s primary research interests revolve around machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling, particularly in the field of medical science.

šŸ“Š Expertise:

With a focus on interdisciplinary applications, Fatemeh leverages her expertise in machine learning and image processing to address complex challenges in medical science, aiming to advance diagnostics and treatment methodologies.

šŸŒŸ Achievements:

As a member of the National Elite Foundation, Fatemeh has demonstrated exceptional academic prowess and a commitment to pushing the boundaries of knowledge in her field.

Publications Top Note :

A novel approach for automatic tumor detection and localization in mammography images via mixture of factor analyzers based on co-clustering

  • Published in Biomedical Signal Processing and Control in 2024.

 

 

 

 

 

Dr. Bechoo Lal | Machine Learning Award | Best Faculty Award

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Dr. Bechoo Lal | Machine Learning Award | Best Faculty Award

Dr. Bechoo Lal, KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoo Lal šŸŽ“ is an accomplished academic with expertise in Data Science, Machine Learning, and Big Data Analytics. He holds a Ph.D. in Computer Science and Information Systems from prestigious universities in India and the USA. Currently serving as an Associate Professor at KLEF-KL Deemed University, he has extensive teaching experience spanning over two decades across various institutions. Dr. Lal is deeply involved in research, with a focus on predictive modeling using Machine Learning and Data Science. He has received numerous certifications and training in Data Science-related fields, including from Stanford University and IBM. With a commitment to academic excellence, Dr. Lal has contributed significantly to the field through publications, projects, and memberships in professional organizations. šŸ“ššŸ’»

Professional Profile:

Scopus

Orcid

Google Scholar

šŸŽ“ Education:

Dr. Bechoo Lal holds a PhD in Information Systems from the University of Mumbai, specializing in Data Analytics. He also completed a PhD in Computer Science from SJJT University, focusing on Machine Learning, and a Master of Technology in Computer Science and Engineering from AAI-Deemed University.

šŸ‘Øā€šŸ’¼ Experience:

With over two decades of experience in academia, Dr. Lal has served as an Associate Professor at KLEF University, Vijayawada Campus, and as an Assistant Professor at various institutions including the University of Mumbai and King Khalid University in Saudi Arabia. He has expertise in teaching Data Science, Machine Learning, Database, and Programming Languages.

šŸ”¬ Research:

Dr. Lal’s research interests lie in Machine Learning and Data Science, with a focus on predictive modeling and big data analytics. He has supervised numerous PhD and master’s dissertations and has contributed significantly to research with over 60 publications, including patents, books, journals, and conference papers.

šŸŒ Skills:

Dr. Lal possesses strong technical skills in machine learning, data visualization, and predictive modeling, along with proficiency in programming languages such as Python, C/C++, and Java. He is well-versed in DBMS/RDBMS systems and statistical analysis tools like SPSS and R.

šŸ‘Øā€šŸ’» Teaching:

As a dedicated educator, Dr. Lal has taught courses in Computer Science, Information Technology, and Software Engineering. He has also held administrative roles such as coordinator and examination chairperson, demonstrating leadership and organizational abilities.

šŸ“š Memberships:

Dr. Lal is a member of several prestigious organizations including the International Association of Engineers (IAENG) and the Indian Society for Technical Education (ISTE). He also serves as a research supervisor and adjunct faculty for international universities.

Scopus Metrics:

  • šŸ“Ā Publications: 20 documents indexed inĀ Scopus.
  • šŸ“ŠĀ Citations: A total of 06 citations for his publications, reflecting the widespread impact and recognition of Dr. Bechoo Lalā€™s research within the academic community.

Publications Top Notes :

  1. A road map: e-commerce to world wide web growth of business world
    • Published in Global Journal of Management and Business Research in 2019.
    • Cited by 6 articles.
  2. Analysis of Business Processes and Modeling Approach to Business Process Re-Engineering
    • Published in International Journal of Computer Science and Information Technology in 2012.
    • Cited by 5 articles.
  3. Analysis Report on Attacks and Defence Modeling Approach to Cyber Security
    • Published in International Journal of Scientific Research in Science and Technology in 2019.
    • Cited by 2 articles.
  4. Critical Review of Success Factors of Knowledge Management System (KMS) on Competency Building on IT Based Organization
    • Published in British Journal of Research in 2014.
    • Cited by 1 article.
  5. An optimization approach to analysis of success factors and significance of IT enabled services in business process re-engineering
    • Published in International Journal of Computer Applications in Engineering Sciences in 2012.
    • Cited by 1 article.