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

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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. Tee Connie | Machine Learning Awards | Best Researcher Award

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Dr. Tee Connie | Machine Learning Awards | Best Researcher Award

Dr. Tee Connie , Multimedia University , Malaysia

Dr. Tee Connie is a distinguished academic and researcher in the field of Information Technology, specializing in machine learning, pattern recognition, computer vision, and biometrics. She is currently a Professor at the Faculty of Information Science and Technology, Multimedia University, Malaysia, where she also serves as Dean of the Institute for Postgraduate Studies. Dr. Tee holds a Ph.D. and Master’s in Information Technology from Multimedia University, and a Bachelorā€™s degree in Information Technology with First Class Honours from the same institution. Her research is widely recognized, evidenced by numerous funded projects and publications, including notable grants for innovative applications in gait analysis, vehicle traffic analysis, and computer vision solutions. She has also contributed to the field with a patent for a hand geometry and palm print verification system. Her extensive experience and leadership in both research and academic administration underscore her significant impact in advancing information technology.

Professional Profile:

Scopus

Orcid

Summary of Suitability for the Research for Best Researcher Award: Tee Connie

Introduction: Dr. Tee Connie, a Professor at Multimedia University, is a distinguished candidate for the Research for Best Researcher Award. Her extensive background in machine learning, computer vision, and biometrics, coupled with her leadership roles and significant research contributions, positions her as a highly suitable nominee.

šŸŽ“Education:

Dr. Tee Connie completed her Doctor of Philosophy in Information Technology at Multimedia University, Malaysia, in 2015. Prior to this, she earned a Master of Science in Information Technology from the same institution in 2005. She also holds a Bachelor of Information Technology, with a major in Information System Engineering, graduating with First Class Honours and a CGPA of 3.92/4.00 in 2003.

šŸ¢Work Experience:

Dr. Tee Connie has held several academic and administrative positions at Multimedia University, Malaysia. She has been a Professor at the Faculty of Information Science and Technology since 2023 and currently serves as the Dean of the Institute for Postgraduate Studies, a role she has held since April 2022. Prior to this, she was the Deputy Dean of the Institute for Postgraduate Studies from April 2021 to April 2022. Dr. Tee’s career at the university began as a Lecturer in 2005, and she was promoted to Senior Lecturer in 2008, a position she held until 2021. She has also worked as an Associate Professor at the Faculty of Information Science and Technology since 2021 and served as a Tutor from 2003 to 2005.

šŸ†Awards and Grants:

Dr. Tee Connie has been awarded several significant research grants. She is leading the Malaysia-Jordan Matching Grant project on “A Non-Invasive Gait Analysis for Parkinsonā€™s Disease Screening Using Computer Vision and Machine Learning Techniques,” which runs from September 2024 to August 2026, with a funding amount of RM 23,000. She is also a project member for the TM R&D Fundā€™s “Smart-VeTRAN: Smart Vehicle Traffic Impact Analysis Using 4G/5G Network” (RM 678,453) and the “Machine Learning Based Distributed Acoustic Sensing (DAS) for Fiber Break Prevention” projects (Sub-project 1: RM 638,731; Sub-project 2: RM 599,061), both running from August 2022 to July 2024. Other notable grants include the Fundamental Research Grant Schemeā€™s “Confined Parking Spaces and Congestion Prediction using Deep Q-Learning Strategy” (RM 89,093) and the “Few-shot Learning Approach for Human Activity Recognition and Anomaly Detection” (RM 113,850), both spanning from September 2022 to April 2024. Additionally, she has secured funding for projects such as the “Cryptographically Secure Cloud-Based Infrastructure (CryptCloud)” (RM 917,504), the IR Fundā€™s “Gender and Age Estimation using Human Gait for Smart Cities Surveillance” (RM 24,000), and the Multimedia University-Telkom University Joint Research Grant for “Gait Analysis for Neurodegenerative Disorders using Computer Vision and Deep Learning Approaches” (RM 20,000). Her past projects include contributions to the International Collaboration Fundā€™s “Design and Development of A Drone Based Hyperspectral Imaging System for Precision Agriculture” (RM 264,660) and several other notable grants in fields related to computer vision, biometrics, and security surveillance.

Publication Top Notes:

  • Visual-based vehicle detection with adaptive oversampling
  • A Robust License Plate Detection System Using Smart Device
  • Review on Digital Signal Processing (DSP) Algorithm for Distributed Acoustic Sensing (DAS) for Ground Disturbance Detection
  • A Review of AI Techniques in Fruit Detection and Classification: Analyzing Data, Features and AI Models Used in Agricultural Industry
  • Boosting Vehicle Classification with Augmentation Techniques across Multiple YOLO Versions

 

 

 

 

Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

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Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

Mrs. Kavitha Duraipandian, Sathyabama Institute of Science and Technology, India

Mrs. Kavitha Duraipandian is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai, and is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology. She holds a Master’s degree in Computer Science from Anna University and a Bachelor’s degree from Madras University. With a rich teaching career spanning roles at SRM Institute of Science and Technology, Dhaanish Ahmed College of Engineering, and other institutions, Kavitha has instructed various subjects, including Machine Learning and Cloud Computing. She has earned accolades such as “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award. Kavitha also mentors over 75 students in Indo-Global internships, focusing on ML, DL, AI, and Cybersecurity.

Professional Profile:

Scopus
Orcid
Google Scholar

šŸŽ“ Education:

Kavitha Duraipandian is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology, Kattankulathur (since January 2020). She holds a Master of Engineering in Computer Science from Anna University (2009-2011) with a 79% score and a Bachelor of Engineering in Computer Science from Madras University (1997-2001) with a 70% score.

šŸ’¼ Academic Experience:

Kavitha is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai (since June 2024). She has previously served as an Assistant Professor at SRM Institute of Science and Technology, Ramapuram (2019-2024), and Dhaanish Ahmed College of Engineering, Chennai (2011-2019). Her earlier roles include Lecturer positions at Tagore Engineering College, Sri Sai Ram Engineering College, and Thiruvalluvar College of Engineering and Technology.

šŸ† Awards and Achievements:

Kavitha has coordinated and mentored a team that won first prize in the International App Development Competition (2020) and has received several accolades, including “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award.

šŸŒ International Mentorship:

She mentors over 75 students in Indo-Global Summer/Winter Internships, focusing on ML, DL, AI, and Cybersecurity, in collaboration with MIT Square, London, and foreign universities.

šŸ“š Subjects Handled:

Kavitha has taught a wide range of subjects under both deemed universities and Anna University-affiliated institutions, including Information Storage and Management, Machine Learning applications, Cloud Computing, Database Management Systems, Data Structures, Software Engineering, and more.

Publication Top Notes: