Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

PhD Student at Artificial Intelligence, INTI International University, Malaysia

πŸ‘¨β€πŸŽ“He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

πŸ”¬ He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

πŸ† The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

πŸ‘¨β€πŸŽ“ Xiaofeng Wang (1980) is a PhD candidate in the Faculty of Data Science and Information Technology at INTI International University, Nilai, Malaysia. Originally from Shanxi, China, he graduated from Xinzhou Normal University with a major in Computer Science and Technology. He furthered his education at Shanxi University, specializing in Computer Systems Engineering.

Other Activity:

πŸ‘¨β€πŸ« Currently, Xiaofeng Wang is a lecturer in the Department of Computer Science at Xinzhou Normal University in Shanxi. His primary research interests revolve around the Internet of Things, cyberspace security, artificial intelligence, and deep learning. Over the past few years, he has made significant contributions to his field, with 3 SCI papers, 1 EI paper, 2 Scopus papers, 1 book, and involvement in several research projects.

Publications:

  1. Wang, X., Othman, M., Dewi, D.A., Wang, Y. (2024). WSLC: Weighted semi-local centrality to identify influential nodes in complex networks. Journal of King Saud University – Computer and Information Sciences, 36(1), 101906.
  2. Wang, X., Wang, Y., Javaheri, Z., Moghadamnejad, N., Younes, O.S. (2023). Federated deep learning for anomaly detection in the internet of things. Computers and Electrical Engineering, 108, 108651.
  3. Wang, Y., Wang, X., Ariffin, M.M., Alqhatani, A., Almutairi, L. (2023). Attack detection analysis in software-defined networks using various machine learning methods. Computers and Electrical Engineering, 108, 108655.
  4. Wang, X. (2013). The research of digital recognition technology based on bp neural network. BioTechnology: An Indian Journal, 8(2), 180–185.

 

 

Ms. Brittany Ho | Machine Learning | Best Researcher Award

Ms. Brittany Ho | Machine Learning | Best Researcher Award

Ph.D. Scholar at Climate Change , Beijing Normal University, China

πŸ‘¨β€πŸŽ“She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

πŸ”¬ She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

πŸ† The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Brittany Ho is currently pursuing a Bachelor of Science in Computer Science at the University of the Pacific, with an anticipated graduation date in Fall 2024. She has consistently achieved high academic performance, earning a place on the Dean’s Honor Roll with a GPA of 3.88 out of 4.00. Brittany’s coursework has focused on areas relevant to her field, including Artificial Intelligence, Computer Game Technologies, Computer Systems & Networks, and Analytics Computing Data Science. Her dedication to her studies and her coursework selection demonstrate her commitment to gaining a well-rounded understanding of computer science πŸŽ“.

Skills:

Ms. Brittany Ho is proficient in several programming languages, including Java (advanced), C++ (advanced), Python (intermediate), Swift (beginner), and R (beginner). Her technical skills extend to working with relational databases, the MQTT protocol, the Linux operating system, GPT 3.5 Turbo, Logic Pro, and Unity. Additionally, she holds certifications and has completed training in various areas such as IP Addressing (LinkedIn), Cloud Computing (Coursera), Arduino Foundation (LinkedIn), MacOS System Administrators (LinkedIn), Unity Essentials (Unity), C# with Unity (LinkedIn), Social and Behavioral Research (CITI), and Learning Deep Learning (NVIDIA). πŸ–₯οΈπŸ“ŠπŸ”§

Projects and Research:

Ms. Brittany Ho has been making significant contributions in her roles. As a Performance Engineer Intern at NVIDIA Corporation, she is involved in comprehensive GPU performance benchmarking for High-Performance Computing (HPC) and Deep Learning (DL) frameworks and applications. Her responsibilities include developing Python scripts for automating testing and collaborating with the engineering team to troubleshoot and resolve performance issues, gaining valuable hands-on experience in problem-solving. Additionally, at the University of the Pacific, as a Research Assistant, she has played a pivotal role in developing an advanced NLP and Generative AI tool using Python and GPT 3.5 Turbo, contributing to a book chapter on “Machine Learning in Educational Sciences,” and leading a journal publication on ChatGPT integration in an NLP framework for targeted user review analysis. πŸš€πŸ”¬πŸ‘©β€πŸ’»

 

 

Mr.Syamasudha Veeragandham | Deep learning | Best Researcher Award

Mr.Syamasudha Veeragandham| Deep learning | Best Researcher Award

Research Scholar, Vellore Institute of technology, Vellore

πŸ‘¨β€πŸŽ“She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

πŸ”¬ She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

πŸ† The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

EDUCATION:

The user is currently pursuing a full-time Ph.D. in the School of Computer Science and Engineering at Vellore Institute of Technology-Vellore, starting from July 2019. They have previously completed an M.Tech in Computer Science and Engineering from PBR Visvodaya Institute of Technology, Kavali, affiliated with J.N.T.U.A, A.P, with an aggregate of 74.07% in 2011. Their undergraduate degree is a B.Tech in Computer Science and Engineering from Chadalawada Ramanamma Engineering College, Tirupati, with an aggregate of 60.78% in 2009. They completed their Intermediate education in M.P.C from Sri Sai Junior College, Kavali, with a percentage of 87.1% in 2005, and their SSC from Z.P.H. School, Gudlur, with a percentage of 61.00% in 2003.

EXPERIENCE:

The user has accumulated 8 years of teaching experience as an Assistant Professor in the CSE department at various institutions, including Annamacharya Institute of Technology & Sciences-Tirupati, Sree Rama Engineering College-Tirupati, and Ramireddy Subbaramireddy Engineering College-Kavali. They have been ratified as an assistant professor from JNTU-Anathapuramu. Their teaching portfolio includes a wide range of subjects at both undergraduate and postgraduate levels, such as Artificial Intelligence, Machine Learning, Deep Learning, Computer Organization, Microprocessors and interfacing, Computer Graphics, Data Mining, Data Warehousing, Discrete Mathematics (MFCS), C-Programming, Data Structures, Advanced Computer Network, and Java and Web Technologies. Additionally, they have guided numerous B.Tech and M.Tech projects, with 12 and 5 projects guided, respectively. In addition to teaching, they have taken on various administrative responsibilities, including acting as an in-charge for CO’S, PO’S, PSO’S, PEO’S in NBA and NAAC, as well as serving as a time-table in-charge, class in-charge, and project coordinator.

Syamasudha Veeragandham ‘s citation metrics and indices from Google Scholar are as follows:

  • Cited by: All: 33, Since 2018: 31
  • Citations: 33 (All), 31 (Since 2018)
  • h-index: 4 (All), 4 (Since 2018)
  • i10-index: 1 (All), 1 (Since 2018)

These metrics showcase the impact of Veeragandham ‘s work within the academic community, demonstrating the number of citations his publications have received and the influence of his research output.

WORKSHOPS ATTENDED:

The user has actively participated in a wide array of workshops and training sessions covering diverse topics. These include sessions on Virtualization and Cloud Computing, Implementation of ICT in Engineering Education, Design of Experiments-Research Orientation, Industrial IoT training using LoRaWAN Technology, Deep drive into Machine Learning Algorithms for Natural Language Processing, Machine Learning for IOT Data Analysis using Raspberry pi and Tensor flow, Deep Learning Concepts with Convolutional Neural Network, Deep Drive in Cloud computing and hands-on Kubernetes, Effective Tools and Methodologies for NLP and Computational Linguistics, Emerging Trends and Research Directions in Cryptography and Information Security, Laughter yoga-The Hilarious Stress Buster, IoT in Cybersecurity, Accreditation: Its Benefits –Multidisciplinary approach, Mathematica for Education & Research, Developing Blockchain-based Smart Contracts on Ethereum using Solidity Language, Web 3.0 and Semantic Web, Statistical tools for effective research, Addressing challenges in medical image processing using Deep learning techniques, an Online user awareness session to demonstrate Springer Nature platforms, Fitness is your wealth, FOP-HR Policies, Avoiding Common Errors in English, Assessment of Python programming using MoodleCoderunner/VPL, Recent trends in Machine/Deep Learning for Computer Vision and Biomedical Applications, AI Tools for Scientific writing, Machine Learning and Deep Learning techniques in applied research, and A practical approach to real-world problems using AI and Deep Learning.

RESOURCE PERSON:

The user has actively contributed as a resource person at several engineering colleges, where they conducted training sessions for faculty members on Outcome-Based Curriculum, Cooperative and Collaborative Learning, Designing Question Papers, and Outcome-Based Assessment. Their engagements included sessions at Annamacharya Institute of Technology and Sciences-Tirupati, Nalla Narasimha Reddy Education Society’s Group of Institutions-Hyderabad, and Sree Venkateswara College of Engineering-Nellore.

CERTIFICATIONS ON OUTCOME BASED EDUCATION:

The user has actively pursued professional development in the field of education and curriculum design. They completed the IUCEE International Engineering Educator Certification program in three phases through APSSDC from January 2018 to July 2018. Additionally, they attended a one-week workshop on Curriculum Design, Measurement, and Evaluation through NITTTR-Kolkata from November 22, 2016, to November 27, 2016. They also participated in a one-week workshop on Outcome-Based Education and accreditation through NITTTR-Kolkata from September 24, 2018, to September 28, 2018. Furthermore, they attended a one-week workshop on Evaluating Students’ Performance and Designing Question Papers through NITTTR-Kolkata from February 25, 2019, to March 1, 2019.

Publications:

A review on the role of machine learning in agriculture

  • Published in Energy in 2020 with 11 citations.

A detailed review on challenges and imperatives of various CNN algorithms in weed detection

  • Published in Energy in 2021 with 8 citations.

Role of IoT, image processing and machine learning techniques in weed detection: a review

  • Published in Energy in 2022 with 6 citations.

Effectiveness of convolutional layers in pre-trained models for classifying common weeds in groundnut and corn crops

  • Published in Energy in 2022 with 4 citations.

The Solutions of SQL Injection Vulnerability in Web Application Security

  • Published in Energy in 2019 with 2 citations.