Boquan Li | Cyber Threat | Best Researcher Award

Posted on by ScienceFather

Dr. Boquan Li | Cyber Threat | Best Researcher Award

Assistant Professor at College of Computer Science and Technology, Harbin Engineering University, China

Dr. Boquan Li is a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he has served since January 2024. Prior to this, he was a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. Dr. Li holds a Ph.D. in Information Engineering from the University of Chinese Academy of Sciences and a Bachelor of Engineering from Harbin Engineering University. His research interests focus on artificial intelligence, cybersecurity, deepfake detection, and speaker recognition, with numerous publications in leading international conferences and journals. Dr. Li is also an active peer reviewer for prestigious journals like IEEE Transactions on Software Engineering.

Profile:

Education:

Dr. Boquan Li holds a Doctor of Philosophy (Ph.D.) from the University of Chinese Academy of Sciences, where he specialized in Information Engineering at the Institute of Information Engineering. He completed his Ph.D. in January 2022, building a strong foundation in artificial intelligence, cybersecurity, and data science. Prior to his doctoral studies, Dr. Li earned a Bachelor of Engineering degree from the School of Software at Harbin Engineering University in June 2016. His comprehensive academic background has equipped him with expertise in cutting-edge technologies, enabling him to contribute significantly to research in AI and cybersecurity.

Professional Experience:

Dr. Boquan Li has a diverse professional background in both academia and research. Since January 2024, he has been serving as a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he contributes to teaching and research in artificial intelligence and cybersecurity. Prior to this role, Dr. Li worked as a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. In this capacity, he was involved in cutting-edge research on deepfake detection, speaker recognition, and digital forensics. His professional experience highlights his expertise in developing innovative solutions to cybersecurity challenges and advancing research in AI-driven technologies.

Research Interests:

Dr. Boquan Li’s research interests focus on cutting-edge areas of artificial intelligence, cybersecurity, and multimedia forensics. He is particularly interested in deepfake detection, where he explores the vulnerabilities and robustness of detection systems across various domains. His work also covers speaker recognition, digital forensics, and adversarial attacks, aiming to develop defense mechanisms against cyber threats. Additionally, Dr. Li has a strong interest in cross-modal fusion techniques, particularly in audio-visual speech recognition, and domain adaptation methods for enhancing the accuracy of AI models across diverse datasets. His research contributes to advancing secure and reliable AI systems.

Skills:

Dr. Boquan Li possesses a diverse skill set that encompasses advanced computational techniques and a robust understanding of artificial intelligence and machine learning algorithms. He is proficient in developing and implementing deep learning models, particularly for applications in image and audio processing. His expertise extends to cybersecurity measures, with a focus on identifying vulnerabilities in AI systems and creating effective defense strategies against adversarial attacks. Additionally, Dr. Li is skilled in data analysis and statistical methods, enabling him to interpret complex datasets and derive meaningful insights. His strong programming skills in languages such as Python and proficiency with machine learning frameworks like TensorFlow and PyTorch further enhance his research capabilities in the field of computer science and technology.

Conclusion:

Dr. Boquan Li’s research addresses critical issues in AI security, deepfake detection, and adversarial defenses, areas of increasing importance in today’s technological landscape. His innovative work, combined with his academic and research experience, positions him as a strong candidate for the Best Researcher Award. His contributions have practical applications in cybersecurity and AI ethics, demonstrating both academic excellence and real-world impact.

Publication Top Noted:

  • How Generalizable are Deepfake Image Detectors? An Empirical Study
  • Two-stage Semi-supervised Speaker Recognition with Gated Label Learning
    • Authors: Xingmei Wang, Jiaxiang Meng, Kong Aik Lee, Boquan Li, Jinghan Liu
    • Year: 2024
    • Conference: International Joint Conference on Artificial Intelligence
    • Type: Conference paper
  • Assessing Backdoor Risk in Deepfake Detectors
    • Authors: Jiawen Wang, Boquan Li, Min Yu, Kam-Pui Chow, Jianguo Jiang, Fuqiang Du, Xiang Meng, Weiqing Huang
    • Year: 2024
    • Conference: IFIP WG 11.9 International Conference on Digital Forensics
    • Type: Conference paper
  • CATNet: Cross-Modal Fusion for Audio–Visual Speech Recognition
    • Authors: Xingmei Wang, Jiachen Mi, Boquan Li, Yixu Zhao, Jiaxiang Meng
    • Year: 2024
    • Journal: Pattern Recognition Letters
    • DOI: 10.1016/j.patrec.2024.01.002
  • A Residual Fingerprint-Based Defense Against Adversarial Deepfakes
  • FakeFilter: A Cross-Distribution Deepfake Detection System with Domain Adaptation
    • Authors: Jianguo Jiang, Boquan Li, Baole Wei, Gang Li, Chao Liu, Weiqing Huang, Meimei Li, Min Yu
    • Year: 2021
    • Journal: Journal of Computer Security
    • DOI: 10.3233/jcs-200124
  • Restoration as a Defense Against Adversarial Perturbations for Spam Image Detection
    • Authors: Jianguo Jiang, Boquan Li, Min Yu, Chao Liu, Weiqing Huang, Lejun Fan, Jianfeng Xia
    • Year: 2019
    • Conference: International Conference on Artificial Neural Networks
    • DOI: 10.1007/978-3-030-30508-6_56

Christian Delgado | Cybersecurity | Excellence in Research

Posted on by ScienceFather

Mr. Christian Delgado | Cybersecurity | Excellence in Research

Researcher at University of Vigo, Spain

Summary:

Mr. Christian Delgado is an accomplished professional with over 18 years of experience in information systems management and education. Currently serving as Co-responsible for the Department of Information Systems at IESIDE, he oversees campus virtual platforms, ERP systems, and web infrastructures. Christian is also an Associate Professor at UNIR Universidad Internacional de La Rioja, specializing in blockchain technology. His expertise spans cybersecurity, educational technology, and ICT business development.

Profile:

Education:

Mr. Christian Delgado is currently pursuing his doctoral studies in Telecommunication Engineering with a specialization in Blockchain and Cybersecurity at the Universidade de Vigo. He holds a Master’s degree in Computer Security from UNIR Universidad Internacional de La Rioja, earned in 2018. His undergraduate education includes a degree in Telecommunication Engineering from the Universidade de Vigo. Additionally, he completed advanced German language studies at Universität Wien and received specialized training in creating ICT businesses from the Escuela de Organización Industrial in 2006

Professional Experience:

Mr. Christian Delgado brings over 18 years of expertise in information systems management and educational leadership. Currently, he holds the position of Co-responsible for the Department of Information Systems at IESIDE, where he manages campus virtual platforms, ERP systems, and web infrastructures across their campuses in A Coruña and Vigo. Since May 2006, he has been an Associate Professor at UNIR Universidad Internacional de La Rioja, specializing in blockchain technology. Christian’s career also includes significant roles such as Director of IT at Dentcard GmbH in Germany, focusing on implementing information systems and leveraging ICT for operational efficiency. Prior to this, he served as an Engineer at Artel Ingenieros, where he oversaw projects involving network interconnection and video conferencing systems. His diverse experience underscores his proficiency in cybersecurity, educational technology, and ICT business development.

Research Interests:

Mr. Christian Delgado’s research interests primarily revolve around the intersection of information systems, cybersecurity, and educational technology. His focus includes exploring the applications of blockchain technology in enhancing data security and transparency within educational and organizational contexts. He is also interested in the integration of ICT (Information and Communication Technology) into educational infrastructures to improve learning outcomes and operational efficiency. Christian’s academic pursuits aim to contribute insights into the evolving landscapes of cybersecurity and educational technology, particularly in fostering innovative approaches to data protection and digital learning environments.

Skills:

Mr. Christian Delgado possesses a comprehensive skill set encompassing over 18 years of experience in information systems management, educational leadership, and cybersecurity. He excels in overseeing campus virtual platforms, ERP systems, and web infrastructures as Co-responsible for the Department of Information Systems at IESIDE. With a robust background as an Associate Professor at UNIR Universidad Internacional de La Rioja, he specializes in blockchain technology, leveraging his expertise to enhance data security and transparency. Christian’s proficiency extends to ICT business development, where he has demonstrated strategic implementation of information systems at Dentcard GmbH in Germany. His skills underscore a deep commitment to advancing educational technology and cybersecurity frameworks, contributing to innovative solutions in digital learning and organizational efficiency.

 

Publications:

Blockchain applications in education: A systematic literature review

  • Authors: C Delgado-von-Eitzen, L Anido-Rifón, MJ Fernández-Iglesias
  • Journal: Applied Sciences
  • Volume: 11
  • Issue: 24
  • Article Number: 11811
  • Year: 2021
  • Citations: 57

Application of blockchain in education: GDPR-compliant and scalable certification and verification of academic information

  • Authors: C Delgado-von-Eitzen, L Anido-Rifón, MJ Fernández-Iglesias
  • Journal: Applied Sciences
  • Volume: 11
  • Issue: 10
  • Article Number: 4537
  • Year: 2021
  • Citations: 27

Blockchain for the scalable issuance and verification of private academic information

  • Authors: C Delgado-von-Eitzen, L Anido-Rifón, MJ Fernández-Iglesias
  • Conference: 2021 International Conference on Advanced Learning Technologies (ICALT)
  • Pages: 436-438
  • Year: 2021
  • Citations: 4

NFTs for the issuance and validation of academic information that complies with the GDPR

  • Authors: C Delgado-von-Eitzen, L Anido-Rifón, MJ Fernández-Iglesias
  • Journal: Applied Sciences
  • Volume: 14
  • Issue: 2
  • Article Number: 706
  • Year: 2024

Varietal Susceptibility and Assessment of Losses Caused by Pulse Beetle Callosobruchus Chinensis (L.) in Green Gram Under Laboratory Conditions

  • Authors: AS Meena, RS Meena, MA Laichattiwar
  • Journal: Journal of Pure and Applied Microbiology
  • Volume: 11
  • Issue: 1
  • Pages: 259-263
  • Year: 2017

 

Yanqiu Song | Defense Economics | Best Researcher Award

Posted on by ScienceFather

Ms. Yanqiu Song | Defense Economics | Best Researcher Award

PhD student at Central University of Finance and Economics, China

Summary:

Ms. Yanqiu Song is a dedicated researcher and PhD student in Defense Economics at the Central University of Finance and Economics (CUFE). With a solid foundation in economics, she holds a Master’s degree in Regional Economics from the Party School of the Central Committee of CPC, and a Bachelor’s degree in International Economics and Trade from Northeastern University. Her research focuses on advanced economic theories and their practical applications, particularly in regional development and the optimal allocation of state-owned assets. Ms. Song has participated in significant projects, published research articles, and gained valuable experience through various internships and assistant roles, showcasing her commitment to academic excellence and practical implementation.

Profile:

Education:

Ms. Yanqiu Song is currently a PhD student in Defense Economics at the Central University of Finance and Economics (CUFE), focusing on advanced courses such as Microeconomics, Macroeconomics, and Econometrics. She earned her Master’s degree in Regional Economics from the Party School of the Central Committee of CPC, where she wrote her thesis on the optimal allocation of state-owned assets based on high-quality regional development. She also holds a Bachelor’s degree in International Economics and Trade from Northeastern University, where her graduation thesis explored the impact of northeast China’s opening to the outside world on economic development.

Professional Experience:

Ms. Yanqiu Song has accumulated diverse professional experience across various roles. Currently a Project Participant at the Institute of Defense Economics and Management, CUFE, she has co-authored notable publications, including an article in Resources Policy. She previously interned at Beijing Chaoyang International Technology Innovation Service Co., LTD, where she contributed to the “Urban Economic Brain” project. As a Research Assistant at China Construction Fangcheng Investment & Development Group Co., LTD, she was involved in benchmarking smart city projects and published related research. Additionally, she served as a Student Assistant at the China Academy of Northeast Revitalization, NEU, participating in significant evaluation projects on regional revitalization.

Research Interest:

Ms. Yanqiu Song’s research interests lie primarily in defense economics, regional economics, and international trade. Her PhD research at the Central University of Finance and Economics focuses on the intersection of defense economics and advanced economic theories, with particular attention to topics like risk aversion and financing in terrorism. She has explored the optimal allocation of state-owned assets for regional development during her master’s studies at the Party School of the Central Committee of CPC. Additionally, her undergraduate research at Northeastern University involved empirical studies on the economic impact of northeast China’s international trade policies. Ms. Song’s work often intersects with public policy, strategic economic planning, and the integration of advanced economic methodologies to address contemporary economic challenges.

Skills:

Ms. Yanqiu Song possesses a diverse set of skills that complement her academic and professional pursuits. She has strong English literacy and practical application abilities, as evidenced by her IELTS score of 6.0 and CET-6 score of 530, enabling her to communicate fluently with individuals from various backgrounds. Ms. Song is proficient in data analysis software, including Stata, Eviews, and SPSS, as well as Office software. She holds national computer certificates in C Language (Level II) and Network Technology (Level III), demonstrating her technical competence. Her skills are further enhanced by her experience in rigorous research, organizational planning, coordination, and teamwork, cultivated through her extensive academic and professional experiences.

Publications:

Article: The role of gold in terrorism: Risk aversion or financing source?

  • Journal: Resources Policy
  • Publication Date: 2024-07-01
  • Type: Journal article
  • DOI: 10.1016/j.resourpol.2024.105201
  • ISSN: 0301-4207
  • Contributors: Yu Song, Yanqiu Song, Shiwei Chang, Lele He