Gan Xu – Artificial Intelligence – Best Researcher Award

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Gan Xu – Artificial Intelligence – Best Researcher Award

Mr. Gan Xu distinguished academic and researcher in the field Artificial Intelligence.

🌐 Professional Profile

Educations📚📚📚

He is currently pursuing a Ph.D. in Finance at the Capital University of Economics and Business in Beijing, China, since September 2021. Prior to this, he completed his Master’s in Finance from Beijing Union University, Beijing, China, graduating in June 2021. His academic journey began with a Bachelor’s degree in Biotechnology, which he obtained from Guilin Medical University, Guilin, Guangxi, China, in June 2010.

Research Experience

He participated in the Project of the National Social Science Foundation of China, focusing on the “Research on Level Measurement, Spatial and Temporal Divergence, and Improvement Path of Rural Financial Services for Rural Revitalization” (19BJY158), where he was mainly responsible for the research design of some sub-topics and participated in enterprise research. Additionally, he contributed to the Key Topic of the China Mobile Communication Federation on the “Research on the Application of Blockchain Technology in Finance” (CMCA2018ZD01), taking charge of the research design of certain sub-topics and writing research reports. Furthermore, he was involved in the research project on “Financial Support for Deepening Financial Services for Private and Micro and Small Enterprises” as part of the Comprehensive Reform Pilot City Project in Jincheng City, Shanxi Province, where he was responsible for independently participating in application writing.

Social Experience

He has co-authored several significant publications, including “Financial Density of Village Banks and Income Growth of Rural Residents” with Yang, G.Z., Xu, G., Zhang, Y., and others, published in Economic Issues in 2021. Additionally, he contributed to “Knowledge Mapping Analysis of Seven Decades of Rural Finance Research in China” with Zhang, F., Xu, G., Zhang, X.Y., and Cheng, X., which appeared in Rural Finance Research in 2020. He also co-authored “A Review of Blockchain Applications in the Financial Sector” with Zhang, F. and Cheng, X., published in Technology for Development in 2019.

Honors

  • Received Beijing Outstanding Graduates in 2020
  • Outstanding graduate of Beijing Union University in 2020
  • First Prize of Excellent Paper in the First Annual Meeting of the Financial Technology Professional Committee of the China Society for Technology Economics, 2019
  • Second Prize of Excellent Paper in the 13th China Rural Finance Development Forum, 2019
  • Second Prize of Excellent Paper of the 9th Annual Conference of China Regional Finance and Xiongnu Financial Technology Forum, 2019

📝🔬Publications📝🔬

Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

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Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

Dr. Micheal Olaolu Arowolo  distinguished academic and researcher in the field Artificial Intelligence. He holds several academic and professional memberships. In March 2021, he became a member of the Institute of Electrical and Electronics Engineers (IEEE), with membership number 96234988. He joined the Asia Pacific Institute of Science and Engineering (APISE) in September 2019, holding membership number M20190918110. In May 2019, he became a member of both the International Society for Computational Biology (ISCB) and the Nigerian Bioinformatics and Genomics Network (NBGN), with membership number NBGNI380. He also joined the Society of Digital Information and Wireless Communications (SDIWC) in March 2017 and the European Alliance for Innovation (EAI) in February 2017. Additionally, he has been a member of the International Association of Engineers (IAENG) since September 2015, with membership number 158851. His professional certifications include being an Oracle Database SQL Certified Expert from Oracle University, achieved in March 2014. Moreover, he is indexed on Scopus (57214819505), ORCID (0000-0002-9418-5346), and Web of Science Researcher (ABD-4157-202), all obtained in 2019.

 

🌐 Professional Profile

Educations📚📚📚

He attended several academic institutions, beginning with ECWA L.G.E.A Primary School ‘B’ in Ilorin, Kwara State, where he obtained his First School Leaving Certificate (FSLC) from 1991 to 1998. He then moved on to Modelak Science College in Ilorin, completing his Senior School Certificate Examination (SSCE) between 1998 and 2004. For his undergraduate studies, he attended Al-Hikmah University in Ilorin, Kwara State, earning a Bachelor of Science (B.Sc.) degree in Computer Science with Second Class Honors (Lower Division) from 2008 to 2012. Continuing his education, he obtained a Master of Science (M.Sc.) degree in Computer Science from Kwara State University in Malete, Kwara State, between 2014 and 2017. Finally, he completed his academic journey at Landmark University in Omu-aran, Kwara State, where he earned a Doctor of Philosophy (Ph.D.) in Computer Science from 2018 to 2021.

Work Experience:

He has held various academic and professional positions throughout his career. Since 2022, he has been serving as a Research Scholar, Instructor, and Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri, Columbia, specifically at the Christopher S. Bond Life Sciences Center. In 2021, he was a Lecturer II in the Department of Computer Science at Landmark University, Omu-Aran, Kwara State, Nigeria, and prior to that, from 2020 to 2021, he worked there as an Assistant Lecturer. From 2018 to 2020, he was a Graduate Lecturer in the Department of Computer Science at the Institute of Professional Studies, Kwara State University, Malete. In 2019, he served as an Ad-Hoc Staff for the Independent National Electoral Commission (INEC) in Nigeria, working as an Oke-Ode Ad-Hoc Registration Area Technician for the Kwara State Election. His earlier roles include being an IT Consultant at Dalayak IT Consults from 2016 to 2017, a Computer Analyst at Baylings Enterprises from 2013 to 2015, and a Computer Analyst for the Ogun-Oshun River Basin Development Authority during his National Youth Service Corps (NYSC) from November 2012 to October 2013.

Academic and Administrative Positions Held

He has served in various academic and administrative roles, including being the Academic Level Adviser for Computer Science 400L students and the Examination Officer for the Computer Science department at Landmark University from 2021 to 2022. Additionally, he was a member of the University Ranking Committee at Landmark University in 2022. He contributed to the university community by being a member of the Landmark University Sustainable Development Goal 9 group focused on industry, innovation, and infrastructure. He also served on the Local Organizing Committee (LOC) for the 2nd Nigerian Bioinformatics and Genomics Network (#NBGN21) Conference in 2021. Furthermore, he acted as the Social Director of the Al-Hikmah University Alumni Association and was an instructor for H3ABioNet’s Introduction to Bioinformatics course (IBT_2021).

His personal qualities include good logical skills, a strong personality, excellent communication abilities, keen observation, quick learning, multitasking, and proficiency in computing. Throughout his career, he has supervised over 40 undergraduate students (B.Sc.) on their projects, theses, and dissertations.

📝🔬Publications📝🔬

Esha Aftab – Neural Models – Best Researcher Award

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Esha Aftab – Neural Models – Best Researcher Award

Ms. Esha Aftab  distinguished academic and researcher in the field Neural Models.  She possesses a strong foundation in various undergraduate courses such as Introduction to Computing, Object-Oriented Programming (C++), Data Structures and Algorithms, Database Systems, Digital Logic Design, and Design and Analysis of Algorithms. Her technical proficiencies encompass a wide range of technologies and languages including C#, ASP, .NET Framework, PRISM Framework, MATLAB, MS SQL Server 2005, Oracle, Java, JavaScript, Java ME, and OpenGL.

🌐 Professional Profiles

Educations📚📚📚

She is currently pursuing her PhD at Punjab University College of Information Technology, with a focus on advancing her knowledge and expertise in her field. Prior to this, she completed her M.Sc in Computer Science at Lahore University of Management Sciences (LUMS) in 2012, achieving a commendable CGPA of 3.66 out of 4.0. Her academic journey commenced with a Bachelor’s degree in Computer Science from the National University of Computer & Emerging Sciences (NU-FAST), Lahore, where she graduated in 2009 with an impressive CGPA of 3.74 out of 4.0. Her educational background reflects a consistent dedication to academic excellence and a strong commitment to her field of study.

Work Experience

She has amassed a wealth of experience across academia and industry. Currently serving as an Assistant Professor at Punjab University College of Information Technology (PUCIT) since 2019, her role involves conducting programming and technical courses, with a particular focus on subjects such as Data Structures, Algorithms, and Machine Learning. Prior to this, she held the position of Lecturer at NUCES-FAST from 2012 to 2019, where she contributed significantly to the academic environment. Additionally, she served as Visiting Faculty in 2012, delivering the ‘Applied Programming’ course for MSc students. Her industry experience includes a stint as a Software Engineer at Techlogix Pvt. Limited from 2009 to 2010, where she was involved in designing and developing automated business processes for clients like Ufone, Motorola, and Nestle. Her projects ranged from enterprise application integration for Ufone using IBM WebSphere Integration Developer to implementing automated business processes for Motorola using Savvion BPM Software and devising algorithms for Nestle’s Milk Balancing System. She adeptly utilized various development tools such as Microsoft Visual Studio 2008, Silverlight, Telerik Toolkit, and .Net Framework to deliver innovative solutions across her diverse roles.

Technical Proficiencies
 She is adept at working in different development environments such as Linux (Ubuntu), MS Visual Studio (2008/2010), Netbeans IDE, Eclipse, Savvion BPM Software, and IBM Websphere Toolkit. Noteworthy among her major projects is her contribution to a Computer Vision Research Project focused on developing a Shape and color-based Jigsaw Puzzle Solver, achieving successful results in shape-based jigsaw piece identification and implementing piece placement algorithms using image stitching techniques. Additionally, she has contributed to a research-based project on Image Annotation, employing statistical methods to label images according to their content. Her diverse skill set and hands-on experience in both academic and research settings underscore her proficiency and versatility in the field of computer science

Academic Achievements

 Silver Medalist: 2nd position in BCS (FAST)
 Dean’s List Honor Certificate (FAST)

 

📝🔬Publications📝🔬

Serena Doria – Technological Networks – Women Researcher Award

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Serena Doria – Technological Networks – Women Researcher Award

Assoc Prof Dr. Serena Doria distinguished academic and researcher in the field Technological Networks. She was responsible for the Ud’A Scienza Project financed under the Call for Scientific Dissemination PANN2020 – Annual Contributions Law 113/91 D.D. 1524 of 21/01/2019, promoted by the MUR. The Ud’A Scienza Project was funded for a total of €72,176, ranking ninth with a score of 55/60 out of 71 admitted projects, and it has a duration of 12 months (from 15.12.2021 to 15.12.2022).

🌐 Professional Profiles

Educations📚📚📚

she graduated in Mathematics, with a focus on Applied Probability, from the University of Rome “La Sapienza” on January 29th, 1992. Since November 1st, 2022, she has been an associate professor in the scientific sector MAT 06 – Probability Calculus and Mathematical Statistics. From 1995 to 2022, she worked as a researcher in the scientific sector MAT 06 – Probability Calculus and Mathematical Statistics. Her research interests include coherent conditional forecasts and their extensions, Hausdorff measures and fractal sets, Choquet integral, representation of orderings, equivalences in complex decisions and complex systems, and knowledge representation in Artificial Intelligence.

Conferences

She attended the MTISD’06 Conference on Methods, Models, and Information Technologies to Support Decision Making, held at the University of Naples – L’Orientale, Procida from September 28th to 30th, 2006. She also participated in the MTISD’04 Conference on Methods, Models, and Information Technologies to Support Decision Making, hosted by the Faculty of Economics and Social Sciences, Benevento from June 24th to 26th, 2004. Additionally, she was present at the SIS Intermediate Conference on Process and Statistical Evaluation Methods in Rome from June 4th to 6th, 2001. She took part in the II Conference of the MURST co-financed Research Project on Models for Treating Partial Knowledge in Decision-Making Processes in Lipari, Sicily from July 22nd to 26th, 2000. Moreover, she attended the I Conference of the MURST co-financed Research Project on Models for Treating Partial Knowledge in Decision-Making Processes in Perugia from April 7th to 9th, 1999. She also participated in the Evolution of Mathematics, its Applications, and its Teaching Conference in Numana from June 4th to 10th, 1999, and the National Mathesis Conference in L’Aquila from October 19th to 21st, 1998. She attended the Days of Combinatorial Geometry in Rome on May 29th and 30th, 1997. Lastly, she was present at the Conference on Methods of Representing Uncertainty in Architecture in Pescara from November 27th to 30th, 1997, and the Conference on Uncertainty Analysis in Economic and Territorial Management in Benevento in May.

 

Internationalizations

She served as an editor, alongside Thomas Augustin and Massimo Marinacci, for the Special Issue of the Ninth International Symposium of Imprecise Probability: Theory and Applications – ISIPTA’15, published in the International Journal of Approximate Reasoning, Volume 84, 39-40, in 2015. Additionally, she was an editor, alongside Thomas Augustin, Enrique Miranda, and Erik Queguebeur, for the Proceedings of the Ninth International Symposium of Imprecise Probability: Theory and Applications – ISIPTA’15, published by Arcne Editrice in 2015. She organized the Ninth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA’15) in Pescara from July 20th to 24th, 2015. Furthermore, she organized the Fifth SIPTA Summer School on Imprecise Probability: Theories and Applications in Pescara from July 16th to 20th, 2012. Since 2001, she has been a member of SIPTA (International Society for Imprecise Probability: Theories and Applications). She served on the Executive Committee of SIPTA from July 14th, 2009, to July 24th, 2011. Since April 2008, she has been a reviewer for Mathematical Reviews (MR). She also served on the Program Committee of the International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’21) in Granada, Spain, from July 6th to 9th, 2021, and the Program Committee of the International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’19) in Ghent, Belgium, from July 3rd to 6th, 2019.

 

Scientific Activity

She participated in the PRIN 1997 Research Program – Partial Knowledge and Coherent Probability, led by Professor Romano Scozzafava at La Sapienza University. She also participated in the PRIN 1999 Research Program – Mathematical Models for Uncertainty Treatment and Alternative Project Selection in Architecture and Urban Planning, led by Professor Antonio Maturo at G. d’Annunzio University of Chieti-Pescara, with National Scientific Coordination by Professor Romano Scozzafava at La Sapienza University. She served as a reviewer for national projects as a member of REPRISE (the register of scientific experts established at the MIUR) for the following section: Basic Research. Additionally, she acted as a reviewer for scientific articles within the framework of the VQR 2015-2019. She also reviewed scientific articles for the following international journals indexed in Scopus and/or WoS: International Journal of Approximate Reasoning, Information Sciences, International Journal of Information Technology and Decision Making, Fuzzy Sets and Systems, British Journal of Mathematical and Statistical Psychology, Axioms, and Symmetry.

 

📝🔬Publications📝🔬

Jorge Laureano Moya Rodríguez – Neural Networks – Best Researcher Award

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Jorge Laureano Moya Rodríguez – Neural Networks

 Prof Dr.  Jorge Laureano Moya Rodríguez distinguished academic and researcher in the field Neural Network.  Jorge Laureano Moya Rodríguez is a Professor Emeritus at the Central University “Marta Abreu” de las Villas. Cuba. He received his Ph.D. in Mechanical Engineering at this university in 1994. He published over a three hundred papers in professional journals and he has authored several books in mechanical and electrical engineering. He has several international and national awards, including some from the Academy of Sciences of Cuba. He has lectured in different Universities of Spain, México, Nicaragua and Brazil. He is currently visiting professor at the Federal University of Bahia in Brazil. Dr. Moya’s research interests are Multiobjective Optimization, Logistics, Computer Aided Design, and Computer Aided Engineering.

Ele é também membro da ERASMUS MUNDUS ASSOCIATION (EMA) e da Associação Mexicana de Modelagem Numérica e Engenharia (AMMNI). Reconhecido como bolsista de produtividade em Pesquisa pelo CNPq (nível 2) e consultor ad hoc do CNPq, ele contribui como árbitro para diversas revistas científicas e instituições acadêmicas em países como Venezuela, Colômbia, Peru e Cuba. Com uma ampla lista de mais de 50 projetos de pesquisa concluídos e implementados em Cuba, ele é considerado Professor de Mérito pela Universidade Central Marta Abreu de Las Villas. Sua atuação como professor abrange cursos de pós-graduação e disciplinas de mestrado em várias universidades, incluindo a Universidade Federal do Espírito Santo (Brasil), Universidade Veracruzana (México), Universidade Técnica do Estado de Aragua (Venezuela) e Universidade Nacional de Engenharia (Nicarágua). Ele também coordenou o Mestrado em Engenharia Mecatrônica em várias universidades na Venezuela e trabalhou como professor convidado em diversas instituições no México, Peru e Espanha. Anteriormente, ele foi pesquisador do ITEGAM, professor visitante na Universidade Federal do Espírito Santo e na Universidade Federal da Bahia.

 

🌐 Professional Profiles

Educations: 📚🎓

Jorge Laureano Moya Rodríguez, known in bibliographic citations as J. L. M. Rodríguez, J. L. Moya, Jorge Moya, Jorge Laureano Moya Rodríguez, J. Moya, Jorge Rodríguez, Jorge L. Moya Rodríguez, or variations thereof, is affiliated with the University Federal da Bahia, where he works within the Program of Industrial Engineering Postgraduate Studies.

He completed a postdoctoral position in 2011 at the Universidad de Oviedo, UNIOVI, Spain, funded by the Agencia Española de Colaboración Internacional, AECI, Spain. The research was in the field of Engineering.

In 2008, he undertook a postdoctoral fellowship at the Universidad de Oviedo, UNIOVI, Spain, funded by ERASMUS MUNDUS, EM, Germany. The research focus was in Engineering.

In 2005, he conducted postdoctoral research at the Universidad Católica de Leuven, KLU, Belgium, supported by VLIR, VLIR, Belgium. The research was within the field of Engineering.

Publication

 

Guangli Wu – Video Summarization – Best Researcher Award

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Guangli Wu – Video Summarization

prof Dr. Guangli Wu  distinguished academic and researcher in the field  Video summarization.  The existence of software vulnerabilities will cause serious network attacks and information leakage problems. Timely and accurate detection of vulnerabilities in software has become a research focus on the security field. Most existing work only considers instruction-level features, which to some extent overlooks certain syntax and semantic information in the assembly code segments, affecting the accuracy of the detection model. In this paper, we propose a binary code vulnerability detection model based on multi-level feature fusion. The model considers both word-level features and instruction-level features. In order to solve the problem that traditional text embedding methods cannot handle polysemy, this paper uses the Embeddings from Language Models (ELMo) model to obtain dynamic word vectors containing word semantics and other information. Considering the grammatical structure in the assembly code segment, the model randomly embeds the normalized assembly code segment to represent it. Then the model uses bidirectional Gated Recurrent Unit (GRU) to extract word-level sequence features and instruction-level sequence features respectively.

Eduvation

He pursued his academic journey with a solid foundation in computer science and technology, earning a Bachelor’s degree from Shandong Technology and Business University in 2003. Building upon this, he delved into the realm of Computer Application Technology, completing his Master’s degree at Northwest Minzu University in 2007. Driven by a passion for cultural diversity and linguistic exploration, he further expanded his expertise by attaining a doctoral degree in Chinese Minority Ethnic Languages and Literature from Northwest Minzu University in 2011. This educational trajectory reflects his commitment to a multidisciplinary approach, seamlessly blending computer technology with a profound understanding of language and culture.
Professional Profiles:

RESEARCH INTEREST

⚫ Video Summarization
⚫ Temporal Language Localization in videos
⚫ Botnet Detection
⚫ Binary Code Vulnerability Detection
⚫ Video Abnormal Event Detection
FUND PROJECTS
1. Natural Science Foundation of Gansu Province (17JR5RA161, 21JR7RA570)
2. Gansu University of Political Science and Law Major Scientific Research and Innovation Projects
(GZF2020XZDA03)
3. Young Doctoral Fund Project of Higher Education Institutions in Gansu Province (2022QB-123)
4. Gansu Province Higher Education Innovation Fund Project (2017A-068)
5. University-level Innovative Research Team of Gansu University of Political Science and Law
6. Longyuan Youth Innovation and Entrepreneurship Talent Project (2022QB-123)

MAIN SCIENTIFIC PUBLICATIONS

1. Guangli Wu,ShengTao Wang,Shipeng Xu. “Feature fusion over hyperbolic graph convolution networks for
video summarization.” IET Computer Vision,2023.
2. Guangli Wu,Tongjie Xu. “Video Moment Localization Network Based on Text Multi-semantic Clues
Guidance.” Advances in Electrical and Computer Engineering,2023,23(3):85-92.
3. Guangli Wu,Huili Tang. “Binary Code Vulnerability Detection Based on Multi-Level Feature Fusion.” IEEE
Access,2023,11: 63904-63915.
4. Guangli Wu,Shanshan Song,Leiting Li. “Video Summarization Generation Model Based on Transformer
and Deep Reinforcement Learning.” in 2023 8th International Conference on Computer and
Communication Systems (ICCCS). IEEE, 2023: 916-921.
5. Guangli Wu,Shengtao Wang,Liping Liu. “Fast Video Summary Generation Based On Low Rank Tensor
Decomposition.” IEEE Access,2021,9:127917-127926.
6. Guangli Wu,Zhenzhou Guo,Mianzhao Wang,Leiting Li and Chengxiang Wang. “Video Abnormal Event
Detection Based on CNN and Multiple Instance Learning.” in twelfth international conference on signal
processing systems. SPIE,2021:134-139.
7. Guangli Wu,Zhenzhou Guo,Leiting Li and Chengxiang Wang. “Video Abnormal Event Detection Based on
CNN and LSTM.” in 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP).
IEEE,2020: 334-338.
8. Guangli WU,Leiting LI,Zhenzhou GUO,Chengxiang WANG and Yanpeng, YAO. “Video summarization
Based on ListNet Scoring Mechanism.” in 2020 5th International Conference on Computer and
Communication Systems (ICCCS). IEEE,2020: 281-285.
9. Guangli WU,Liping LIU,Chen Zhang and Dengtai TAN. “Video Abnormal Event Detection Based on ELM.”
in 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).IEEE,2019: 367-371