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.

 

 

Mr. Simar Muratov | Data Analysis | Young Scientist Award

Mr. Simar Muratov | Data Analysis | Young Scientist Award

Postgraduate Student at Data Analysis, ITMO University, Russia

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:

Mr. Simar Muratov has a strong educational background in the field of computer science. He completed his studies in Information Security from 2016 to 2020 at Peter the Great St.Petersburg Polytechnic University. Following this, he pursued Artificial Intelligence and Machine Learning from 2020 to 2022, again at Peter the Great St.Petersburg Polytechnic University. Currently, he is studying Theoretical Informatics at ITMO University, with an expected completion date in 2025. This diverse educational journey indicates a well-rounded understanding of various aspects of computer science and technology.

Summary:

Mr. Simar Muratov holds a Master’s degree in Mathematics and Computer Science, specializing in Artificial Intelligence and Machine Learning, from Peter the Great St. Petersburg Polytechnic University. Currently, he works as a DevOps engineer in the infrastructure automation team at Sberbank of Russia, while also pursuing a Ph.D. in Theoretical Informatics at ITMO University. During his university years, he began working on a secure big data lake framework and has since gained expertise in developing CI/CD pipelines, customizing IaaC solutions, and designing architectures. Mr. Muratov is actively improving his skills in DevSecOps, MLOps, and cloud computing (SberCloud, YandexCloud). He holds certifications in Azure cloud services (AZ-900 and AI-900) and is preparing for the AWS Solutions Architect Associate certification, in addition to completing corporate training within the company.

Experience:

Mr. Simar Muratov has been employed as a DevOps engineer in the infrastructure development team at Sberbank of Russia since 2023. In this role, he is responsible for various tasks such as developing Ansible playbooks and roles, supporting server configuration setup, and administering Linux and PostgreSQL DBMS. Additionally, he is involved in the development of automation scripts in Python/bash, administration of k8s/OpenShift clusters, implementation of custom terraform modules, and setting up monitoring and logging systems. During his tenure, Mr. Muratov successfully addressed three key challenges, including creating a unified gateway inventory for component-based stands, developing a unified ansible inventory format for job customization, and implementing nginx PL/SPF auditing to streamline configuration alignment and monitor certificate expiry dates.

Skills:

Mr. Simar Muratov is proficient in a wide range of programming languages, DevOps tools, cloud computing, administration, build tools, and additional skills in data science, data engineering, databases, quality assurance, management, and documentation. He is certified in Python and also has expertise in C++. His scripting languages include bash and groovy. In DevOps, he has experience with version control (Github, BitBucket, GitLab), CI/CD tools (Jenkins, TeamCity, GitLab CI, CircleCI), and distribution repositories (Nexus, Artifactory, DockerHub, Azure CR). He is skilled in containerization/orchestration (Docker, docker-compose, docker-swarm, k8s, Openshift), configuration/infrastructure management (Ansible, Terraform), and cloud computing (AWS, Azure certified, SberCloud). Mr. Muratov is proficient in Linux and Windows administration and various build tools (make, maven, sbt, gradle, npm, PyInstaller, Cython, PyPy). His side skills include data science (Tensorflow, sklearn, numpy, pandas, matplotlib, seaborn, R, DVC, MLFlow), data engineering (Apache Spark, Apache Airflow, Apache Kafka, Redis, CTL, YARN, oozie, HDFS), databases (PostgreSQL, MongoDB, Apache HBase, ClickHouse, Greenplum), quality assurance (Selenium, PyTest, Lettuce, Robot), management (Jira), and documentation (Confluence). He is proficient in English (B2+) and has basic knowledge of German (A1).

Projects:

Mr. Simar Muratov has been involved in several notable projects, including the development of a secure operating system for the Parrot AR Drone 2.0, utilizing “iptables” rules and a proprietary cryptographic protocol. He has also demonstrated his skills in creating tasks for Yandex Alice’s “Tasks from Fractal” using Java, Maven, Tomcat, J2SE, servlets, JSON, XML, and PostgreSQL. The prototype for this project was hosted on Amazon services. Additionally, Mr. Muratov has worked on mobile device security tools leveraging deep learning and artificial intelligence hardware support, developed using TensorFlow Lite. He has contributed to the architecture of a secure big data lake framework and is currently involved in real-time log anomaly detection. His recent pet projects include a machine learning model project template implementing MLOps practices and an in-house developed matrix multiplication module for Python using Cython.

 

 

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’»

 

 

Dr. Sita Rani | Machine Learning | Women Researcher Award

Dr. Sita Rani : Leading Researcher in Machine Learning

Assistant Professor at Machine Learning, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

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:

Dr. Sita Rani has a distinguished academic background, including a Ph.D. in Computer Science and Engineering (CSE) from Inder Kumar Gujral Punjab Technical University (IKG PTU), Kapurthala, India, where she focused on the performance characterization of parallel computation in bioinformatics applications. She also holds a Master’s degree in CSE from GNDEC, Ludhiana, where she achieved a remarkable 73.68%, securing the 2nd position in her class. Dr. Rani’s academic journey began with a Bachelor’s degree in CSE from the same institution, where she secured a 73.2%, again achieving the 2nd position in her class. She also holds a Diploma in CSE from GPW, Ludhiana, where she graduated with honors and a notable 75.2% with a first division. Her academic excellence extends to her high school education, where she graduated from Govt. Sen. Sec. School., Lambra (Hoshiarpur) with a remarkable 78.8%, earning a first division with distinction. Additionally, Dr. Rani has recently completed a Post Graduate Certification Program in Data Science and Machine Learning from IIT, Roorkee, with distinction, further enhancing her expertise in the field.

Professional Experience:

Dr. Sita Rani completed her Postdoctoral research at the Big Data and Machine Learning Lab at South Ural State University (National Research University) in Chelyabinsk, Russian Federation. Her research was conducted under the project titled “Federated Learning for IoMT Applications” during the period from May 2022 to August 2023. This project likely involved exploring the applications of Federated Learning, a machine learning technique, in the context of the Internet of Medical Things (IoMT), which focuses on the use of interconnected medical devices and systems for healthcare applications.

Sita Rani ‘s citation metrics and indices from Google Scholar are as follows:

  • Cited by: All: 1338, Since 2018: 1325
  • Citations: 1338 (All), 1325 (Since 2018)
  • h-index: 21 (All), 20 (Since 2018)
  • i10-index: 39 (All), 39 (Since 2018)

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

Conferences:

Dr. Sita Rani actively participated in several international conferences, contributing to the field of data science and smart systems. She served as the Sessions Chair for the special session on “Data Mining and Software Engineering” at the 1st International Conference on “Applied Data Science and Smart Systems (ADSSS)” held at Chitkara University, Punjab, INDIA on 4th -5th November, 2022. Additionally, she chaired the special session on “Data Science and Data Analytics” at the “International Conference on Innovations in Data Analytics (ICIDA-2022)” organized by the “International Knowledge Research Foundation” in collaboration with Eminent College of Management and Technology (ECMT), West Bengal, India on 29-30 November, 2022. Dr. Rani also contributed as a member of the Technical Program Committee during the “International Conference on Innovations in Data Analytics (ICIDA-2022).” Furthermore, she chaired the special session on “Networking and Security” at the International Conference on Data Analytics and Management (ICDAM-2022), jointly organized by The Karkonosze University of Applied Science, Poland, in association with the University of Craiova Romania, Warsaw University of Life Sciences Poland, and Tun Hussein Onn University Malaysia, on 25th – 26th June, 2022. These engagements reflect her active involvement in the academic community and her commitment to advancing research in her field.

Research Interest:

Parallel and high-performance computing, Internet of Things (IoT), machine learning, blockchain, and healthcare are among Dr. Sita Rani’s areas of expertise and interest. Her work likely involves leveraging these technologies to advance various aspects of healthcare, such as data analysis, system optimization, and security within the context of healthcare systems and IoT devices. Dr. Rani’s focus reflects a multidisciplinary approach, integrating cutting-edge technologies to address complex challenges in healthcare and related fields.

Memberships:

Dr. Sita Rani holds memberships in several prestigious professional organizations:

  1. IEEE Membership (Yearly up to December 2023) with Membership Number: 97635456.
  2. IAEngg Membership (Lifetime) with Membership Number: 273196.
  3. ISTE Membership (Lifetime) with LM-131713.
  4. Women’s Indian Chamber of Commerce and Industry (WICCI) – Chandigarh SME & MSME Council – Vice-President.

Awards:

Dr. Sita Rani is an esteemed member of several renowned professional organizations. She holds an IEEE Membership, which is valid yearly until December 2023, with the membership number 97635456. Additionally, she is a lifetime member of the IAEngg with the membership number 273196 and the ISTE with LM-131713. Dr. Rani also holds a significant position as the Vice-President of the Women’s Indian Chamber of Commerce and Industry (WICCI) – Chandigarh SME & MSME Council, showcasing her active involvement in professional and leadership roles within her field.

Publications:

IoT equipped intelligent distributed framework for smart healthcare systems

  • Published in Energy in 2023 with 117 citations.

Cloud and fog computing platforms for internet of things

  • Published in Energy in 2022 with 113 citations.

AI-Centric Smart City Ecosystems: Technologies, Design and Implementation

  • Published in Energy in 2022 with 75 citations.

Amalgamation of advanced technologies for sustainable development of smart city environment: A review

  • Published in Energy in 2021 with 67 citations.

Threats and corrective measures for IoT security with observance of cybercrime: A survey

  • Published in Energy in 2021 with 66 citations.

Exploring the application sphere of the internet of things in industry 4.0: a review, bibliometric and content analysis

  • Published in Energy in 2022 with 57 citations.

Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse

  • Published in Energy in 2023 with 53 citations.

Fog computing in industry 4.0: Applications and challengesβ€”A research roadmap

  • Published in Energy in 2022 with 50 citations.