Prof. Dr. Haiyan Kang | Network Security Awards | Best Researcher Award

Prof. Dr. Haiyan Kang | Network Security Awards | Best Researcher Award

Prof. Dr. Haiyan Kang , Beijing Information Science and Technology University, China

Prof. Dr. Kang Haiyan is a prominent academic in the field of Information Security, currently serving as a professor in the Department of Information Security at Beijing Information Science and Technology University, China. He earned his Ph.D. in Computer Application Technology from Beijing Institute of Technology in 2005. A senior member of the China Computer Federation and an ACM member, Prof. Kang has received recognition as an outstanding talent in Beijing and serves as an executive member of the Privacy Protection Committee of the China Confidentiality Association. He is the chief of the national first-class major in Information Security and has contributed significantly to the field through over 110 academic publications and six monographs. His research focuses on network security, blockchain technology, and privacy protection, resulting in six provincial and ministerial awards and 25 invention patents. Committed to education, he has been honored with national and local teaching achievement awards and recognized as an Excellent Graduate Thesis Supervisor in Beijing. Additionally, he holds editorial board positions with several academic journals in the field.

Professional Profile:

SCOPUS

Prof. Dr. Kang Haiyan for the Best Researcher Award

Prof. Dr. Kang Haiyan is a remarkable candidate for the Best Researcher Award due to his extensive contributions to the fields of network security, blockchain, and privacy protection, alongside his dedication to academic excellence and leadership in education.

Education

  • Ph.D. in Computer Application Technology
    Beijing Institute of Technology, China (2005) πŸŽ“

Work Experience

  • Professor
    Department of Information Security, Beijing Information Science and Technology University, Beijing, China
  • Chief
    National First-Class Major (Information Security) and Electronic Information (Network and Information Security) πŸ“š
  • Editorial Board Member
    • Journal of Information Security Research
    • Cyberspace Security
    • Journal of Cyberspace Security Science
    • Journal of Beijing University of Information Science and Technology

Achievements

  • Research Awards: 6 provincial and ministerial level awards πŸ†
  • Invention Patents: 25 patents for innovative contributions πŸ’‘
  • Publications: Over 110 academic papers and 6 monographs πŸ“–

Awards and Honors

  • National Teaching Achievements: 2 Third Prizes πŸ₯‰
  • Beijing Teaching Achievements: 1 Second Prize πŸ₯ˆ
  • Title: Excellent Graduate Thesis Supervisor in Beijing 🌟

PublicationΒ Top Notes:

Hierarchical Stackelberg Game Swarm Learning Incentive Method for Wireless Edge Network

Community overlap discovery algorithm based on industrial big data

Research on the Deep Learning Method Based on Data Feature Relevance and Adaptive Differential Privacy

Enhancing data security in massive data sets using blockchain and federated learning: a loosely coupled approach

Research on Federated Sharing Methods for Massive Data in Blockchain

Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher Award

Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher AwardΒ 

Assist Prof Dr. Loknath Sai Ambati, Oklahoma City University, United States

Dr. Loknath Sai Ambati is an accomplished academic and researcher specializing in Information Systems and Data Analytics. Currently serving as an Assistant Professor of Data Analytics at Oklahoma City University, Dr. Loknath Sai Ambati holds a Doctor of Philosophy in Information Systems, with a specialization in Artificial Intelligence, from Dakota State University, where they also earned two master’s degrees in Information Systems and Data Analytics. With over five years of teaching experience, they have instructed various courses at both undergraduate and graduate levels, focusing on business analytics, healthcare analytics, and social media mining.The Activity Detection Award celebrates innovations in behavioral recognition technology. Explore eligibility, qualifications, publications, and submission guidelines for this esteemed recognition.

Professional Profile:

SCOPUS

 

Summary of Suitability for Best Researcher Award: Loknath Sai Ambati

Based on Loknath Sai Ambati’s impressive educational background, research contributions, and professional experience, he is a highly suitable candidate for the Best Researcher Award.

Education

Dakota State University, Madison, South Dakota
Doctor of Philosophy in Information Systems (Artificial Intelligence)
Master of Science in Information Systems
Master of Science in Data Analytics
GPA: 4.0/4.0
August 2018 – April 2023 (PhD)
August 2019 – December 2020 (MS in Information Systems)
August 2016 – December 2017 (MS in Data Analytics)

VIT University, Chennai, India
Bachelor of Technology in Electronics and Communication Engineering
GPA: 8.55/10
July 2012 – May 2016

Work Experience

Assistant Professor of Data Analytics
Oklahoma City University
September 2023 – Present

  • Teaching graduate-level Data Analytics courses.
  • Engaging in research activities related to Information Systems and Data Analytics.
  • Participating in service activities, including serving on review committees for various conferences and journals.
  • Serving as the Faculty Advisor for the Indian Student Association at OCU.

Visiting Assistant Professor of Business Analytics
Indiana University
May 2022 – August 2023

  • Teaching various Business Analytics courses at both undergraduate and graduate levels.
  • Conducting research activities in healthcare and social media analytics.
  • Participating in service activities, including serving on review committees for conferences and journals.

Graduate Research Assistant
Dakota State University
August 2018 – May 2022

  • Worked on innovations in wearable technology integrated with Artificial Intelligence for healthcare.
  • Assisted the supervisor with research projects and interacted with students regarding course content.
  • Volunteered as an instructor for certain courses as needed.

Analytics Developer
Baylor Scott and White Health
February 2018 – August 2018

  • Applied machine learning algorithms to denial data, achieving savings of up to $0.5 million on denials.
  • Implemented statistical models to reduce denial claims and enhance revenue efficiency.
  • Analyzed correlations between physician coding behaviors and Medicare Risk Adjustment Factor (RAF) scores.
  • Technologies used: Power BI, R, SAS, Python, SQL, MicroStrategy, Advanced Excel.

Publication top Notes:

Human Body Full-body Motion Gesture Image Feature Capture in Mobile Sensor Networks

Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS

Explosive force acquisition of sprinter lower limb in training based on WSN

Two-phase classification: ANN and A-SVM classifiers on motor imagery BCI

Optimal trained long short-term memory for opinion mining: a hybrid semantic knowledgebase approach

FHE-Blockchain: Enhance the Scheme for Secret Sharing of IoMT Data using Decentralized Techniques

Design of Civil Aviation Security Check Passenger Identification System Based on Residual Convolution Network

 

Ms. MIRACLE UDURUME | Intrusion Detection | Best Researcher Award

Ms. MIRACLE UDURUME | Intrusion Detection | Best Researcher Award

Ms. MIRACLE UDURUME, Ulsan University, South Korea

Uduru Miracle is a researcher and graduate student at Kumoh National Institute of Technology in Gumi, Gyeongbuk, South Korea. With a strong academic background, he holds an MSc in Microbiology from Kumoh Institute of Technology, where he completed a thesis on real-time multimodal emotion recognition under the supervision of Professor Wansu Lim. He earned his BSc in Mathematics from Delta State University, Abraka, Nigeria, graduating with second-class upper division honors. His research interests span data generation, emotion recognition, and machine learning. During his time at Kumoh Institute of Technology, Miracle contributed to various lab projects, including the generation of synthetic data for supercapacitors, voice and face emotion recognition using machine learning models, and real-time multimodal emotion recognition. He also played a pivotal role in developing hybrid lithium-ion and ultra-capacitors for electric vehicles. His academic excellence and research contributions have been recognized through awards, including the Korean Government Scholarship Award (2021-2023) and the Christ High School Scholarships.

Professional Profile:

SCOPUS

 

Summary of Suitability for Best Researcher Award

Udurume Miracle is a highly promising candidate for the Best Researcher Award, showcasing an impressive academic background and research expertise in advanced areas such as data generation, emotion recognition, and machine learning. His work primarily focuses on real-time multimodal emotion recognition, utilizing sophisticated techniques like multithreaded weighted average fusion, which highlights his innovative approach to solving complex problems.

πŸŽ“ Education

  • MSc in Microbiology
    Kumoh National Institute of Technology, South Korea
    πŸ“… February 2023

    • Thesis: Real-time Multimodal Emotion Recognition Based on Multithreaded Weighted Average Fusion
    • Advisor: Professor Wansu Lim
  • BSc in Mathematics
    Delta State University, Abraka, Nigeria
    πŸ“… October 2019

    • Second Class Upper Division
    • Thesis: Counting Techniques in Discrete Mathematics
    • Advisor: Dr. J.S. Apanapudor

πŸ”¬ Research Interests

  • Data Generation
  • Emotion Recognition
  • Machine Learning

πŸ”¬ Research Experience

Kumoh National Institute of Technology, South Korea
πŸ“… June 2021 – November 2022

  • Worked on lab projects under the supervision of Professor Wansu Lim
  • Generated synthetic data for predicting the remaining useful life of supercapacitors using methods like GANs, Auto-encoders, and statistical approaches πŸ“Š
  • Conducted voice emotion recognition using machine learning models such as LSTM and CNNs πŸŽ™οΈ
  • Performed face emotion recognition on embedded hardware systems like Jetson Nano and Jetson TX2 πŸ“Έ
  • Developed real-time multimodal emotion recognition using multithreaded weighted average fusion πŸ”„
  • Researched hybrid lithium-ion and ultra-capacitors for electric vehicles πŸš—
  • Applied data fusion techniques for face and speech emotion recognition πŸ€–
  • Generated artificial data for ultra-capacitor projects πŸ”‹

πŸ… Honors and Awards

  • Christ High School Scholarships
    πŸ“… September 2012

    • Part-time scholarship for secondary school education πŸŽ“
  • Korean Government Scholarship Award
    πŸ“… 2021 – 2023

    • Full funding for Master’s program in South Korea πŸ‡°πŸ‡·

Publication top Notes:

 

Synthetic Data Generation Using GAN for RUL Prediction of Supercapacitors

Emotion Recognition Implementation with Multimodalities of Face, Voice and EEG