Sulyman Abdulkareem – Network Intrusion Detection – Best Researcher Award

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Sulyman Abdulkareem – Network Intrusion Detection – Best Researcher Award

Assoc Prof Dr. Sulyman Abdulkareem  distinguished academic and researcher in the field Network Intrusion Detection. He is a performance-driven Project Manager with an extensive academic background in Management and Information Systems and over 10 years of experience managing cross-functional teams to drive cost-effective technology solutions and execute key business projects in a technical environment. He has a proven ability to effectively manage knowledge, communicate, collaborate, and coordinate core IT functions, third parties, and vendors on initiatives to ensure project integration and alignment with overall requirements, security, compliance, standards, and quality assurance. Adept at managing all aspects of solution delivery, he excels in research, analysis, scope definition, resource planning and allocation, budget management, document development, status reporting, risk management, and change control.

🌐 Professional Profile

Educations📚📚📚

He holds a Doctor of Philosophy in Information and Communication Systems from the University of Surrey and a Master of Science in Management Information Systems with Distinction from Coventry University. Additionally, he has earned several professional certifications, including PRINCE 2 Foundation, CMI Level 7 in Professional Consulting, CMI Level 7 in Strategic Management and Leadership, and a certification in Security Policy Development.

 

PROFESSIONAL EXPERIENCE

Since October 2019, he has been serving as a Project Manager at IMBIL Consultancy Services Limited in London. In this role, he implemented a new Case Management System (CMS) tailored to the department’s specific needs, leading to a 40% increase in workflow efficiency and overall productivity of the legal department. He oversaw the development and implementation of a comprehensive enterprise resource planning (ERP) system for a major client, coordinating cross-functional teams, managing timelines and budgets, and ensuring the project met all specified requirements. He led the integration of a machine learning model into a client solution to predict customer behavior for e-commerce activities, enhancing business intelligence and personalized marketing strategies. Additionally, he implemented a data security system for a financial client in compliance with GDPR, ensuring all project activities adhered to relevant industry standards. He conducted daily stand-ups, regular project retrospectives, and feedback sessions, identifying areas for improvement and implementing process optimizations. By refining development processes, improving communication within the project team, and adopting new tools, he enhanced team efficiency and project quality. He standardized the filing system and promoted the use of cloud documentation and storage via SharePoint. Efficiently organizing and coordinating meetings with stakeholders, he scheduled, sent out invitations, prepared meeting agendas, took minutes, and distributed them promptly to ensure clear communication and accountability. He successfully optimized project processes by conducting gap analysis, gathering data on current processes, identifying associated KPIs, and redesigning these processes to improve alignment with desired outcomes, achieving a 65% improvement in these processes.

 

Doctoral Researcher –University of Surrey

He coordinated the DEDICAT 6G project in collaboration with industry giants like Airbus, Nokia, and Orange under the EU’s Horizon 2020 program, securing over €6 million in funding to enhance network efficiency and security. He led the design and implementation of an advanced Network Intrusion Detection Classifier for IoT networks, achieving superior efficiency and effectiveness compared to existing solutions. His groundbreaking research efforts culminated in the publication of a paper titled “IoT Network Intrusion Detection with Ensemble Learners,” detailing the development and success of an innovative network intrusion detection classifier. He collaborated effectively with project team members and security consultants at Mafic Ltd, contributing significantly to the successful completion of IoT solutions by documenting crucial research findings. He demonstrated proficiency in stakeholder management, and agile, waterfall, lean, PRINCE 2, SAFe, and SDLC methodologies. His expertise spans service management, risk and business analysis, process optimization, planning and budgeting, user acceptance testing (UAT), system administration, change management, requirements analysis, and documentation and reporting. He secured smooth laboratory operations and maintained up-to-date standardized operating procedures, resulting in a remarkable 90% success rate in meeting project deadlines. His planning and organizational skills ensured smooth operations by designing a comprehensive weekly schedule, maximizing productivity and efficiency.

As a lecturer at the University of Ilorin from February 2018 to September 2019, he collaborated with a software firm to develop new cybersecurity protocols, providing students with practical experience and creating innovative solutions that benefited the company. He established numerous partnerships with tech companies to collaborate on applied research projects. He led a pioneering research project on renewable energy technologies, engaging undergraduate and graduate students, yielding sustainable energy solutions and publishable research findings that significantly advanced the academic community’s understanding and the industry’s capabilities. He led annual research conferences and regular workshops at the university, where students and faculty could present their project findings, focusing on trending topics such as AI and inviting industry experts to provide networking opportunities for students. He supervised undergraduate projects, guiding more than 20 students through their research endeavors, achieving a remarkable 100% pass rate and witnessing a notable 20% increase in student engagement and active participation in various research and development initiatives. He successfully managed undergraduate class assignments and assessments, resulting in a high 95% completion rate and a notable 15% grade improvement by implementing strategies such as ensuring 95% lecture attendance and enhancing lecture materials, which reduced failure rates by 5% and fostered increased student engagement.

IT Project Manager

• Successfully led the Lifestalia Loan app project delivery within budget and ahead of schedule; Partnered with Apple and Google to deploy
on the App Store and Google Play store. Collaborated with cross-functional teams to uphold the Agile methodology in delivering this project,
resulting in a 30% improvement in project delivery time and a 15% increase in team productivity.
• Implemented UX enhancements based on findings, conducted comprehensive user research and analysis, and identified pain points and
areas for improvement within the app interface. Achieved a 25% increase in user satisfaction and a 20% decrease in user churn rate.
• Collaborated with the Power BI team to create real-time dashboards accessible to cross-functional teams, providing actionable insights into
current user trends, app usage metrics, and the impact of new and already-existing processes, improving decision-making by 60%.
• Effectively managed a high caseload of tasks while maintaining standards and adhering to established protocols. Prioritised tasks based on
urgency, efficiently allocating time and resources to assist clients and attend to other essential duties.
• Responsible for developing and maintaining project documentation. Utilised Trello, Jira, SharePoint, MS Project, and Visio in managing
multiple projects simultaneously within tight deadlines, ensuring seamless communication among stakeholders by preparing project status
& progress reports. Oversaw project timelines, budget tracking, and risk management to ensure the timely delivery of high-quality solutions
that meet client expectations and drive business growth.
• Oversaw transitioning on-premises servers, applications, and data to cloud-based platforms, AWS specifically. Elicited and documented
requirements for the change and developed UAT scripts and comprehensive migration steps.
• Established a robust risk management framework using the RAID log to identify, assess, and mitigate risks across project operations.
Conducted risk assessments, developed risk registers, and implemented risk mitigation strategies, resulting in a proactive approach to risk
management and a 15% reduction in compliance-related incidents.
• Prepared business and financial cases that contained forecasts, methods, assumptions, adopted metrics and sensitive analysis to help
management and other stakeholders make informed decisions before, during, and after any project.

📝🔬Publications📝🔬

Om Prakash – Computer Vision – Best Researcher Award

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Om Prakash – Computer Vision – Best Researcher Award

Dr. Om Prakash  distinguished academic and researcher in the field Computer Vision.

🌐 Professional Profile

Educations📚📚📚

He earned his Doctor of Philosophy from the University of Allahabad, Allahabad, U.P., India, in November 2014. He has extensive experience in academia and industry. Since March 2020, he has been an Assistant Professor at Academic Pay Level-10 in the Department of Computer Science and Engineering, School of Engineering and Technology, HNB Garhwal University, Srinagar Garhwal, Uttarakhand, India. From May 2019 to February 2020, he worked as a Computer Vision Scientist at Inferigence Quotient LLP, Bengaluru, Karnataka, India. Prior to this, he served as an Assistant Professor in the Department of Computer Science and Engineering at NIRMA University, Ahmedabad, Gujarat, India, from May 2018 to April 2019. Between March 2016 and April 2018, he was a faculty member at the Centre of Computer Education, University of Allahabad, U.P., India. He also completed a Postdoctoral Fellowship at the Gwangju Institute of Science and Technology, South Korea, from March 2015 to February 2016. His earlier experience includes serving as a faculty member at the Centre of Computer Education, University of Allahabad, U.P., India, from August 2007 to February 2

Research Interests

• Computer Vision
• Image and Video Processing
• Wavelet transforms
• Multisensory data fusion
• Video surveillance
• Machine Learning/Deep Learning
• Thermography
• Medical Imaging

Book Edited as Guest Editor

AKS Kushwaha, Om Pakash, M. Khare, J. Gwak, N.T. Binh, “Visual and Sensory Data Processing
for Real Time Intelligent Surveillance System”, Multimed Tools Appl, vol.81, pp. 42097–42098
(2022). https://doi.org/10.1007/s11042-022-14263-3, Springer

 

📝🔬Publications📝🔬

1. Pratibha Maurya, Arati Kushwaha, Ashish Khare, Om Prakash, Balancing Accuracy and
Efficiency: A Lightweight Deep Learning Model for Covid-19 Detection” Journal
Engineering Applications of Artificial Intelligence. vol. 136, Part B, July 2024, 108999,
ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2024.108999., Elsevier. (SCI).
2. Arati Kushwaha, Ashish Khare, Om Prakash, Human activity recognition algorithm in video
sequences based on the fusion of multiple features for realistic and multi-view
environment. Multimedia Tools and Applications. vol.83, pp. 22727-22748, August 2024,
Springer (SCI)
(https://doi.org/10.1007/s11042-023-16364-z)
3. Neha Sisodiya, Nitant Dube, Om Prakash, Priyank Thakkar, Scalable Big Earth
Observation Data Mining Algorithms: A Review. Earth Science and Informatics, vol.16,
pp. 1993–2016, June 2023, Springer (SCI). https://doi.org/10.1007/s12145-023-01032-5.
4. Ashish Khare, Arati Kushwaha and Om Prakash, Human Activity Recognition in a Realistic
Unconstrained and Multiview Environment using 2D-CNN. Journal of Artificial
Intelligence and Technology (JAIT). vol.3, pp. 100-107, May 2023, Intelligence Science
and Technology Press. (ISTP) (Scopus). (https://doi.org/10.37965/jait.2023.0163)
5. Arati Kushwaha, Ashish Khare, Om Prakash, “Micro-network-based deep convolutional
neural network for human activity recognition from realistic and multi-view visual
data”, Neural Comput & Applic (2023). vol.35, pp.13321–13341, Springer (SCI).
(https://doi.org/10.1007/s00521-023-08440-0)
6. Arati Kushwaha, Ashish Khare, Om Prakash and Manish Khare, “Dense optical flow
based background subtraction technique for object segmentation in moving camera
environment”, IET Image Processing, vol. 14, no. 14, pp. 3393-3404, December 2020, IET
Publication. (SCI)
(https://doi.org/10.1049/iet-ipr.2019.0960).
7. Mounika B. Reddy, Om Prakash, Ashish Khare, “Keyframe extraction using Pearson correlation
coefficient and color moments,”. Multimedia Systems, vol. 26, pp.267–299 (2020), Springer. (SCI)
(https://doi.org/10.1007/s00530-019-00642-8).

8. Mounika B. Reddy, Om Prakash, Ashish Khare, “Video Superpixels Generation through
Integration of Curvelet transform and Simple Linear Iterative Clustering”, Multimedia Tools and
Applications, vol. 78, pp. 25185–25219, March 2019, Springer. (SCI)
(https://doi.org/10.1007/s11042-019-7554-z).

9. Om Prakash, Chang Min Park, Ashish Khare, Moongu Jeon, Jeonghwan Gwak, “Multiscale
Fusion of Multimodal Medical Images using Lifting Scheme based Biorthogonal Wavelet
Transform,” Optik, vol. 182, pp.995-1014, April 2019, Elsevier (SCI)
(https://doi.org/10.1016/j.ijleo.2018.12.028)
10. Manish Khare, Om Prakash and Rajneesh Kumar Srivastava, “Combining Zernike moment and
Complex wavelet transform for Human object classification,” Int. J. Computational Vision and
Robotics, May 2018, vol.18, no.2, pp.140-167, Inderscience Publishers. (Scopus)
(https://doi.org/10.1504/IJCVR.2018.091983)
11. Om Prakash, Jeonghwan Gwak, Manish Khare, Ashish Khare, Moongu Jeon, “Human detection in
complex real scenes based on combination of biorthogonal wavelet transform and Zernike
moments,” Optik, vol. 157, pp. 1267-1281, March 2018, Elsevier. (SCI)
(https://doi.org/10.1016/j.ijleo.2017.12.061)
12. Richa Srivastava, Om Prakash and Ashish Khare, “Local Energy based Multimodal Medical
Image Fusion in Curvelet Domain,” IET Computer Vision, vol.10, issue 6, pp. 513-527, 2016. IET
digital library.(SCI)
(https://doi.org/10.1049/iet-cvi.2015.0251)
13. Om Prakash and Ashish Khare, “Tracking of moving object using energy of Biorthogonal wavelet
transform,” Chiang Mai Journal of Science, vol.42, no.3, pp. 783-795, July 2015, Chiang Mai
University. (SCI)
(https://thaiscience.info/Journals/Article/CMJS/10972713.pdf)
14. Om Prakash and Ashish Khare, “Medical Image Denoising based on Soft thresholding using
Biorthogonal Multiscale Wavelet Transform,” International Journal of Image and Graphics, vol.
14, no. 1 & 2, pp. 1450002 (30 pages), March 2014, World Scientific. (SCI)
(https://doi.org/10.1142/S0219467814500028)
15. Alok Kumar Singh Kushwaha, Chandra Mani Sharma, Manish Khare, Om Prakash and Ashish
Khare, “Adaptive real-time motion segmentation technique based on statistical background model,”
The Imaging Science Journal, vol. 62, no.5, pp. 285-302, 2014, Royal Photographic Society.(SCI)
(https://doi.org/10.1179/1743131X13Y.0000000056)
16. Rajiv Singh, Richa Srivastava, Om Prakash and Ashish Khare, “Multimodal medical image fusion
in Dual tree complex wavelet domain using maximum and average fusion rules,” Journal of
Medical Imaging and Health Informatics, vol. 2, no. 2, pp. 168-173, June 2012, American
Scientific Publishers. (SCI)
(https://doi.org/10.1166/jmihi.2012.1080)

Publications in International Conference Proceedings

  • B. Reddy Mounika, Om Prakash, Ashish Khare, “Key Frame Extraction using Uniform Local Binary Pattern,” 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T), University of Allahabad, Allahabad, 21-23 Sept 2018. IEEE
  • Abhishek Srivastava, Pronaya Bhattacharya, Arunendra Singh, Atul Mathur, Om Prakash, Rajeshkumar Pradhan, “A Distributed Credit Transfer Educational Framework based on Blockchain,” 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T), University of Allahabad, Allahabad, 21-23 Sept 2018. IEEE
  • Om Prakash, Alok Kumar Singh Kushwaha, Moongu Jeon, “An approach towards Object Tracking based on Rotation Invariant Moments of Complex Wavelet Transform,” in International Conference on Advances in Computing, Control and Communication Technology (IAC3T-2016), University of Allahabad, Allahabad, 25-27 March 2016.
  • Arati Kushwaha, Ashish Khare, Om Prakash, Jong-In Song, Moongu Jeon, “3D Medical Image Fusion using the Dual Tree Complex Wavelet Transform,” in IEEE 4th International Conference on Control, Automation and Information Sciences (ICCAIS-2015), Changshu, China, 29-31 October 2015. IEEE
  • Manish Khare, Om Prakash, Rajneesh Kumar Srivastava, Ashish Khare, “Contourlet Transform based Human Object Tracking,” Proceedings of 27th SPIE Electronic Imaging, Vol. 9410 (Visual Information Processing and Communication VI), 08-12 February 2015, San Francisco, USA. SPIE
  • Om Prakash, Manish Khare, Ashish Khare, “Biorthogonal Wavelet Transform Based Classification of Human Object Using Adaboost Classifier,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, pp. 194-199, 02-05 December 2014. IEEE
  • Manish Khare, Om Prakash, Rajneesh Kumar Srivastava, Ashish Khare, “Daubechies Complex Wavelet Transform Based Approach for Multiclass Object Classification,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, 206-211, 02-05 December 2014. IEEE
  • Prashant Srivastava, Om Prakash, Ashish Khare, “Content-Based Image Retrieval Using Moments of Wavelet Transform,” Proceedings of IEEE 3rd International Conference on Control, Automation and Information Sciences (ICCAIS-2014), Gwangju Institute of Science and Technology (GIST), South Korea, pp. 159-164, 02-05 December 2014. IEEE
  • Om Prakash, Arvind Kumar, Ashish Khare, “Pixel-level Image Fusion Scheme based on Steerable Pyramid Wavelet Transform using absolute Maximum fusion rule,” Proceedings of IEEE International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT-2014), Ghaziabad, India, pp. 770-775, 07-08 February 2014. IEEE

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📝🔬

Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

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Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

Mr. Nagesh Dewangan distinguished academic and researcher in the field Interpretation Analysis of Deep Learning Models. As a dedicated researcher in the field of machinery condition monitoring, his work has focused on advancing knowledge in activity monitoring and fault diagnosis for heavy machinery using deep learning models. His research has led to several key advancements, particularly in the areas of machinery activity recognition and motor fault diagnosis. He has worked on projects focusing on the cycle time of dumper activities and real-time fault diagnosis of motors using acceleration signals. The studies were conducted in both laboratory and real environments, providing comprehensive data for robust analyses. His work has resulted in the development of innovative methodologies and technologies. He has contributed to the creation of new algorithms for activity recognition using convolutional neural networks (CNNs) and developed approaches to enhance the generalizability of models across different environments. Collaborations with institutions like CSIR-Central Institute of Mining and Fuel Research Dhanbad, India, and industry partners like Coal India Limited, India, have enriched his research.

 

🌐 Professional Profile

Educations📚📚📚

He is currently a Ph.D. research scholar in the Acoustics and Condition Monitoring Laboratory, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India. He received his B.E. degree in Mechanical Engineering from the Bhilai Institute of Technology Durg, India, in 2016, and his M.Tech. degree in Maintenance Engineering & Tribology from the Indian Institute of Technology Dhanbad, India, in 2019. His research interests are in the areas of Mining Machinery, Condition Monitoring, Signal Processing, Fault Diagnosis, Real-time Application, Internet of Things, Machine Learning, and Deep Learning for industry-oriented Product Design and Development. Throughout his academic career, he has been involved in numerous research projects focused on improving machinery efficiency and safety, particularly in the mining industry. His recent work includes analyzing the cycle time of dump truck activities, fuel consumption, and implementing Convolutional Neural Networks for activity recognition.

Experience

He has published a paper in the reputed journal Automation in Construction, where he critically evaluates existing methods and proposes innovative solutions. Additionally, he has co-authored two papers in reputed journals, such as Engineering Transactions and the International Journal of Chemical Engineering. He has also presented his work at various prestigious conferences, such as the International Conference on Mechanical Power Transmission 2019 (IIT Madras), 17th International Conference on Vibration Engineering and Technology of Machinery 2022 (Institute of Engineering, Nepal), National Conference on Condition Monitoring 2023 (NSTL, Visakhapatnam), and World Congress on Engineering Asset Management (RMIT University, Vietnam), sharing his findings and insights with the academic and professional community. For his research work, he predominantly uses MATLAB, Python, LabVIEW, and NI Multisim.

 

📝🔬Publications📝🔬

Hedieh Sajedi – Machine learning – Best Researcher Award

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Hedieh Sajedi – Machine learning – Best Researcher Award

Dr. Hedieh Sajedi  distinguished academic and researcher in the field Machine learning.  Her research interests encompass a wide range of advanced topics, including deep learning and machine learning, where she delves into the development and refinement of algorithms that enable computers to learn from and make decisions based on data. She is also deeply involved in multimedia processing, exploring techniques to enhance and manipulate various forms of media, such as images, videos, and audio. Additionally, her work in data mining and information retrieval focuses on extracting meaningful patterns and insights from large datasets, improving the efficiency and accuracy of information retrieval systems. Furthermore, she investigates bio-inspired algorithms, drawing inspiration from natural processes to create innovative computational methods that solve complex problems.

🌐 Professional Profile

Educations📚📚📚

She completed her Ph.D. in Artificial Intelligence and Robotics at Sharif University of Technology in May 2010, following her M.Sc. in the same field from the same institution, which she earned in August 2005. Prior to her postgraduate studies, she obtained her B.Sc. in Computer Software Engineering from Amir Kabir University of Technology in September 2002.

Work Experience:

She has delivered several invited talks on various topics, including “Computer vision and machine learning for medical image analysis” at the Children’s International Research Center in Washington DC, USA, in July 2022, and “Age Prediction based on brain MRI images” at Pompeu Fabra University in Barcelona, Spain, in June 2022. Additionally, she discussed a “Blind Spot Warning System based on Vehicle Analysis in Stream Images” at the same university and “Brain Age Estimation based on Brain MRI Images” at Sehir University of Istanbul, Turkey, in March 2018. Earlier, in March 2014, she presented on the “Application of Steganography and Steganalysis Methods in Medical and Healthcare Systems” at the University of Pavia, Italy. Her executive activities include serving as the Scientific Chair of the International Conference on Pattern Recognition and Image Analysis (IPRIA) in 2023, head of the Computer Science Department from 2018 to 2022, and Scientific Chair of the 6th International Conference on Pattern Recognition and Image Analysis at the University of Tehran in 2022. She also held the position of Head of Computer Services and Information Technology in the College of Science from 2018 to 2020 and served as Inspector of the Image Processing and Machine Vision Society in Tehran, Iran, in 2015 and 2017. Her funded projects include research on the “Detection and Classification of Circular Objects on the Basis of Convolutional Neural Network (CNN)” funded by the Iran National Science Foundation (INSF) from 2021 to the present, “Investigating Brain Health from Brain MRI Images Using Machine Learning Methods,” partially funded by the Institute for Research in Fundamental Sciences (IPM) from 2018 to 2019, “Brain Age Estimation with Mathematical Modeling” funded by INSF from 2017 to 2018, and the development of “A High-Security and High-Capacity Steganography System” funded by INSF from 2011 to 2014.

Honors & Awards

She was recognized as a member of the University of Tehran Top Researchers Club in 2022 and received the Erasmus Mobility Award from the European Union in the same year. Additionally, she was honored with the Honors Program Graduate Award from Sharif University of Technology for the period from 2006 to 2010. Since 2009, she has been an active member of the Scientific Society for Image Processing and Machine Vision.

She has been an instructor at the University of Tehran since 2013, teaching courses such as “Machine Learning,” “Artificial Intelligence,” “Data Mining,” and “Digital Image Processing” in the Department of Computer Science. She has also instructed “Advanced Topics in Artificial Intelligence” since 2020 and “Advanced Information Retrieval” from 2017 to 2020. Additionally, she taught “Advances in AI” from 2013 to 2020 and “Machine Learning in Physics” from 2018 to 2019. Her teaching portfolio includes courses for Ph.D. students at the Institute of Biochemistry and Biophysics, such as “Advanced Data Structure” in 2018-2019. At AmirKabir University of Technology, she instructed “Machine Learning” from 2010 to 2011 and “Artificial Intelligence” in 2010-2011. She also co-instructed “Machine Vision” at Pompeu Fabra University in Barcelona, Spain, in May 2022. Her experience in bio-inspired computing includes teaching “Evolutionary Computing” at the University of Tehran from 2013 to 2016.

Furthermore, she has taught “Distributed Systems” at Azad University, Qazvin, from 2011 to 2013, and courses such as “Computer Networks,” “Compiler Design and Principles,” and “Introduction to Programming” at the University of Tehran. She also taught “Operating Systems,” “Introduction to Programming,” and other foundational courses at Tarbiat Moallem University from 2006 to 2008. Her early teaching roles include instructing “Introduction to Programming” at Sharif University of Technology in 2006-2007 and several technical and scientific presentation courses at AmirKabir University of Technology from 2009 to 2011.

📝🔬Publications📝🔬

Asif Hamid- Deep learning – Best Researcher Award

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Asif Hamid- Deep learning – Best Researcher Award

Mr. Asif Hamid  distinguished academic and researcher in the field  Deep learning. He has accumulated over four years of experience in writing and publishing research articles for journals and conferences. This experience has provided him with a deep understanding of various writing styles, from scholarly articles to book chapters and industry-focused documentation. His role as a reviewer for many prestigious conferences has also sharpened his critical thinking and editorial abilities.

His expertise is not limited to writing; he is skilled in Python and MATLAB programming, which are crucial for his research projects. He possesses basic skills in HTML and is proficient with MS Office tools—Word, Excel, and PowerPoint—as well as LaTeX software, all vital for creating research papers and presentations. Additionally, his ability to utilize internet applications and implement deep learning techniques demonstrates his aptitude for integrating cutting-edge technology into his research activities.

🌐 Professional Profiles

Educations📚📚📚

He is currently pursuing a Ph.D. at the Islamic University of Science and Technology (IUST) in Awantipora, Jammu & Kashmir, India, a program he began in 2020. Prior to this, he earned his Master of Technology degree in Control and Instrumentation Systems from Jamia Milia Islamia (JMI) in India, where he distinguished himself by securing a CGPA of 9.3 out of 10, placing him in the top 1% of his class. His foundational education was completed at Baba Ghulam Shah Badshah University in Rajouri, Jammu & Kashmir, where he received his Bachelor of Technology degree in Electronics and Communication Engineering, achieving a percentile score of 75.6, which also placed him in the top 1% of his peers.

Conference Papers

• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, May). Discovering low-rank
representations of large-scale power-grid models using Koopman theory. In 2022 Trends in
Electrical, Electronics, Computer Engineering Conference (TEECCON). IEEE.. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, July). Power Grid parameter
estimation using Sparse Identification of Nonlinear Dynamics. In 2022 International
Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) (pp. 1-6).
IEEE. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, Neural network-based time stepping

Awards and Achievements

He has received numerous accolades and support for his academic pursuits. Since 2020, he has been a recipient of the MHRD (Ministry of Human Resource Development, Government of India) fellowship for his Ph.D. studies in the Department of Electrical Engineering at the Islamic University of Science and Technology in Awantipora, Jammu & Kashmir, India, supported by grant number IUST0119013135. In 2019, he successfully qualified the GATE (Graduate Aptitude Test in Engineering) for Electronics and Communication Engineering, scoring 31.67 out of 100. Furthermore, in 2017, he qualified for the M.Tech. program at Jamia Milia Islamia, Delhi, by passing the entrance examination, demonstrating his consistent excellence and competence in his field.

WORKSHOP / SEMINAR / TRAINING / STC attended

1. Presented Discovering low-rank representations of large scale power-grid models using Koopman
theory paper in Electrical, Electronics, Computer Engineering Conference IEEE held on 26-27
may 2022 at Reva University.
2. Presented Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics
paper in the INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROLLER AND
COMPUTING FOR SMART POWER, IEEE 2022 organized by the Department of Electrical
and Electronics Engineering, Sreenidhi Institute of Science And Technology, Hyderabad,
India during 21–23 July 2022.
3. Reviewer for IEEE international conference on applied intelligence and sustainable
computing 2023.
4. Attend in faculty development program entitled “Research Methodology + Publication Ethics”
organised by Department of computer science and engineering IUST, Awantipora form 7-11
Feb 2022.

📝🔬Publications📝🔬

  • Hierarchical deep learning-based adaptive time stepping scheme for multiscale simulations

    Engineering Applications of Artificial Intelligence
    2024-07 | Journal article
    DOI: 10.1016/j.engappai.2024.108430
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Neural network-based time stepping scheme for multiscale partial differential equations

    2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA)
    2023-10-27 | Conference paper
    DOI: 10.1109/cera59325.2023.10455439
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Deep learning assisted surrogate modeling of large-scale power grids

    Sustainable Energy, Grids and Networks
    2023-06 | Journal article
    DOI: 10.1016/j.segan.2023.101031
    Part ofISSN: 2352-4677
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics

    2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)
    2022-07-21 | Conference paper
    DOI: 10.1109/iciccsp53532.2022.9862464
    CONTRIBUTORS: ASIF HAMID BHAT

Wei Zhang – Digital algorithms – Best Researcher Award

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Wei Zhang – Digital algorithms – Best Researcher Award

Dr. Wei Zhang distinguished academic and researcher in the field Digital algorithms. Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement.

🌐 Professional Profiles

Educations📚📚📚

From September 2016 to June 2019, he pursued his Bachelor of Marketing at Hefei University of Technology. He continued his studies at Hunan Agricultural University, where he earned a Master of Agricultural and Forestry Economics and Management, completing the program in June 2021. Building on his academic achievements, he began his PhD in Capability Economic Management at the same university in September 2021, with an expected completion date of June 2025.

Research Experience

Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement. Following this, in 2022, they published an article in “Price Theory and Practice,” where they analyzed the effectiveness of reforms in the rural collective property rights system from the perspective of farmer participation. This research, featured in the March 2022 issue on pages 169-172 and 205, was underpinned by a survey of 315 farmer households across Hunan and Jiangxi provinces, offering valuable insights into the impact of these reforms on rural communities.

Project experience

He hosted the 2023 Hunan Provincial Postgraduate Research Innovation Project Key Project, CX20230730, which focused on the Research on the Contract and Performance of Farmland Infrastructure Governance under Endowment Heterogeneity. He also played a significant role in contributing to several major research projects. He participated in writing a major project for the Hunan Provincial Social Science Fund, numbered 23ZWA14, which involved researching the Current Situation and Countermeasures of Rural Collective Economic Development in Hunan Province. Additionally, he contributed to the general project of the Hunan Provincial Social Science Fund, 21YBA079, which examined the governance mechanism and performance of high-standard farmland in the context of food and ecological security. His research contributions extended to the Hunan Provincial Natural Science Foundation’s general project, 2023JJ30312, focusing on the mechanism and performance of digital technology in empowering farmland water conservancy facilities. Moreover, he was involved in writing for a project under the Hunan Provincial Development and Reform Commission that researched coordinated food and ecological security in the middle and lower reaches of the Yangtze River plain, considering “resources-factors-policies.”

Personal honor

He achieved notable recognition in various academic competitions and forums. At the 2021 Modern Agricultural Development Forum and the First “World Agriculture” Workshop in the context of “Dual Cycles,” he won the second prize in the paper competition. His research excellence continued into the following year when he won the first prize for outstanding paper at the 2022 Hunan Rural Economics Association Annual Meeting. Additionally, he received the award for the second “Economic Management Quantitative Research Methods” Excellent Paper at the School of Economics, Hunan Agricultural University. He also actively participated in advanced training sessions, including the “Jiangsu Province Applied Economic Research Methodology” workshop organized by the Economics Graduate Education Steering Committee of Jiangsu Province and the School of Economics and Management of Nanjing Agricultural University, where he earned the title of qualified student. Furthermore, he attended the “2021 Summer Econometrics and Scientific Research Methods Lecture Series” at the School of Statistics and Mathematics of Zhongnan University of Economics and Law, also achieving the status of qualified student.

 

📝🔬Publications📝🔬

Jianxiao Wang – Data Science – Best Researcher Award

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 Dr. Jianxiao Wang  distinguished academic and researcher in the Data Science and Smart Grid. He is currently an Assistant Professor at the National Engineering Laboratory For Big Data Analysis and Applications, Peking University, and a Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. He obtained Bachelor’s degrees in Engineering and Economics from Tsinghua University in 2014, and completed his Ph.D. in Electrical Engineering from Tsinghua University in 2019. From 2016 to 2017, he served as a visiting researcher at Stanford University and the University of California, Berkeley. From 2019 to 2020, he worked as a project leader at the Ministry of Science and Technology of the People’s Republic of China, contributing to the 14th Five-Year Plan for High Tech Development in the field of energy and transportation, and conducting research on the 2035 National Science and Technology Development Strategy in China.

His research interests revolve around data-driven decision making for energy storage and renewable power systems, focusing on evaluating the levelized cost and designing national low-carbon pathways for emerging technologies such as AIGC, roadside photovoltaics, electric and fuel cell vehicles, power-to-hydrogen, green ammonia chemical industry, and carbon capture and storage utilization. As the first or corresponding author, he has published 1 paper in Nature Sustainability, 2 papers in Nature Communications, 1 paper in Cell The Innovation, 1 paper in Cell Patterns, and 2 papers in Cell iScience. Additionally, he has authored 99 papers published in top journals and conferences, including two 0.1% ESI Hot Paper, two 1% ESI Highly Cited Paper, and four IEEE Conference Best Paper Awards. He has applied for 35 China Invention Patents and 2 US Patents. Furthermore, he has published one Springer monograph as the first author, one IEEE Press monograph as a contributing author, and coauthored three Chinese monographs. The research article in Nature Sustainability was selected as a cover paper candidate and received an official report from Johns Hopkins University. As of August 2023, the research article in Nature Communications has been accessed over 10,000 times and cited 147 times, selected as a 0.1% ESI Hot Paper and officially reported by People’s Daily.

🌐 Professional Profiles

Educations📚📚📚

He pursued his academic journey at Tsinghua University, where he completed his Bachelor’s degrees in Electrical Engineering from the Department of Electrical Engineering and Economics from the School of Economics and Management from August 2010 to July 2014. Subsequently, he continued his academic pursuit at Tsinghua University, specializing in Electrical Engineering, where he earned his Ph.D. from the Department of Electrical Engineering from August 2014 to January 2019. During his Ph.D., he achieved a GPA of 92.8, ranking 2nd out of 55 students. His outstanding performance led to his recognition as an Outstanding Doctoral Graduate and his dissertation being acknowledged as one of the top 2% at Tsinghua University. Additionally, he was awarded the Tsinghua University President Jiang Nanxiang Scholarship, a prestigious honor bestowed upon 10 Ph.D. students annually.

As part of his academic journey, he expanded his horizons through visiting researcher positions at renowned institutions. From April 2017 to December 2017, he conducted research as a visiting researcher at the University of California, Berkeley. Prior to this, from November 2016 to December 2017, he engaged in research activities as a visiting researcher at Stanford University. Furthermore, he broadened his research experience with a visiting researcher position at Texas A&M University from July 2013 to September 2013.

Research Experience

He has been serving as an Assistant Professor at the National Engineering Laboratory for Big Data Analysis and Applications at Peking University since June 2022. Concurrently, he holds the position of Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. Prior to his current roles, from October 2019 to September 2020, he worked as a Project Manager at the Ministry of Science and Technology of the People’s Republic of China. Additionally, he gained valuable experience as a Lecturer at North China Electric Power University from June 2019 to May 2022.

He has received numerous accolades and awards for his outstanding contributions to science, technology, and innovation. In 2023, he was honored with the Second Prize of the Science and Technology Progress Award from the China Electrotechnical Society for his work on “Transmission and Distribution Network Coordinated Control Technology and Applications Under High Distributed Energy Penetration.” Additionally, he received the Second Prize of the Power Innovation Award from the China Electric Power Union for his achievements in “Technology and Application for Data Value-driven Hierarchical Scheduling of Renewable Power Systems.” He was also recognized with the Wu Wen-Jun Artificial Intelligence Outstanding Youth Award by the Chinese Association for Artificial Intelligence for his research on “Physics-informed Data Driven Theory for Smart Grid Operation.” Furthermore, he was selected for the Wiley Open Science Excellent Author Program.

In 2022, he was honored with the Young Scientist Award by the Ministry of Science and Technology of China. He has also been recognized under the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology for his work on “Smart City Energy System Operation Considering Adaptive Consistency Control of Water Electrolysis.” He received a Gold Medal at the Geneva International Exhibition of Inventions for his contribution to “Edge-intelligence Control Technology and System of Solar+Storage Powered Microgrid.” Additionally, his paper titled “Defending Against Adversarial Attacks by Energy Storage Facility” earned the IEEE PES General Meeting Best Paper Award.

He has been recognized for his exceptional service and expertise, receiving the IEEE Transactions on Sustainable Energy Excellent Reviewer Award multiple times. He was also listed in the Forbes China 30 Under 30 Elite List and acknowledged as one of the Outstanding Young Science and Technology Talents by the China Renewable Energy Society. In 2020, he was honored as one of the Beijing Outstanding Young Talents and recognized for his contributions to energy science and technology by the China Energy Research Association. Furthermore, his innovative work on “Renewable Energy-Dominated Virtual Power Plant” secured a place in the top 10 of the Elsevier Renewable Transformation Challenge. He has also been acknowledged with various awards for his inventions and innovations, including the Silver Award at the Beijing Invention and Innovation Competition and the Gold Award at the China Invention Exhibition. Additionally, he has been recognized as a Youth Of China’s High-End Technology Innovation Think Tank for his contributions to the technological development and environmental governance benefits of China’s photovoltaic and energy storage industry.

Monograph

He has authored several publications across various domains, showcasing his expertise and contributions to the field. As the first author, he collaborated with colleagues on the book “Sharing Economy in Energy Markets: Modeling, Analysis and Mechanism Design,” published by Springer in 2022. Additionally, he authored chapters 28-30 in the book “Microgrids: Theory and Practice,” published by IEEE Press in 2023.

Furthermore, he has contributed to monographs in different capacities. In the book “Introduction to the Electricity Spot Market: Trading Strategy and Profit Model for Information Driven Growth,” published by Mechanical Industry Press in 2021, he co-authored chapters 2, 4, and 6. Additionally, he was part of the team contributing to chapter 7 in “2060 China Carbon Neutrality,” published by Chemical Industry Press in 2022. He also co-authored chapters 1 and 2 in “Introduction to New-type Power Systems,” published by the China Association for Science and Technology Carbon Peak and Carbon Neutrality Series in 2022.

Representative Academic Service

He has been recognized for his exemplary contributions and leadership in various professional capacities. In 2023, he served as the Youth Editor for Cell The Innovation, a prestigious role reflecting his expertise in the field, with the journal boasting an Impact Factor of 32.1. He was also appointed as a National Graduate Education Evaluation and Monitoring Expert by the Ministry of Education, showcasing his commitment to education excellence.

In 2022, he was honored as a Distinguished Researcher under the Beijing “Thousands of People Entering Thousands of Enterprises” program, highlighting his significant contributions to research and innovation. He was also recognized as a National Excellent Educator in the National Simulation Innovation Application Competition and appointed as an Instructor by the IEEE Industry Applications Society (IAS) at Peking University. Additionally, he received accolades as an Excellent Editor from the IET Energy Conversion and Economics.

In 2021, he was appointed as an Executive Member of the IEEE Power and Energy Society (PES) China, underscoring his leadership and expertise in the field. He also served as a Youth Working Committee Member of the 9th Council of the Chinese Electrotechnical Society, demonstrating his active involvement in professional organizations.

In 2020, he was recognized as an expert in the 6th National Technology Prediction by the Ministry of Science and Technology of China, further acknowledging his expertise and contributions to technology development. Additionally, he joined the Editorial Board of IET Renewable Power Generation, contributing his insights to the publication.

From 2019 to 2022, he chaired panel sessions at the IEEE PES General Meeting, showcasing his leadership and expertise in the field. Through these diverse roles and responsibilities, he has demonstrated his commitment to advancing research, education, and innovation in his field.

Representative Research Project

He has undertaken numerous significant research projects as the primary investigator, showcasing his leadership and expertise in the field. From November 2022 to October 2025, he leads the National Key R&D Plan project titled “Resilience Enhancement Technology for Large Urban Power Grids Amidst Extreme Events,” with a funding of 4.5 million Chinese yuan. Similarly, from January 2023 to December 2026, he is leading a project funded by the National Natural Science Foundation of China titled “Renewable-dominated Power System Flexible Ramping Operation Considering Consistency Control of Water Electrolysis Multiphysics,” with a grant of 540 thousand Chinese yuan.

In previous years, he has led various other research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the State Grid Corporation of China. These projects cover a wide range of topics including virtual power plant market operation, energy systems integration, self-sustained energy systems for highways, and collaborative regulation technology for large-scale energy storage clusters. Through his involvement in these projects, he has made significant contributions to advancing research and innovation in the energy sector.

📝🔬Publications📝🔬

1 Jianxiao Wang#, Liudong Chen#, Zhenfei Tan, Ershun Du, Nian Liu, Jing Ma, Mingyang Sun, Canbing Li, Jie Song,
Xi Lu*, Chin-Woo Tan*, Guannan He*. Inherent spatiotemporal uncertainty of renewable power in China. Nature
Communications, 2023, 14: 5379.
2 Yang Yu#, Jianxiao Wang#, Qixin Chen, Johannes Urpelainen, Qingguo Ding, Shuo Liu, Bing Zhang*.
Decarbonization efforts hindered by China’s slow progress on electricity market reforms. Nature Sustainability.
2023, 6, 1006-1015.
Special Comments from Johns Hopkins University:

China’s Sluggish Electricity Market Reforms Impede Decarbonization Efforts


Representative Publications
3 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Mu Wang, Daniel M Kammen*, Zhu Liu, Ziming Ma, Qing Xia
and Chongqing Kang. Exploring the trade-offs between electric heating policy and carbon mitigation in China,
Nature Communications, 2020, 11: 6054. (0.1% ESI Hot Paper) https://doi.org/10.1038/s41467-020-19854-y
Special Comments from People’s Daily and Tsinghua University News:
https://www.tsinghua.edu.cn/info/1175/21483.ht

4 Jianxiao Wang#, Feng Gao#, Yangze Zhou, Qinglai Guo, Chin-Woo Tan, Jie Song, Yi Wang*. Data sharing in energy
systems. Advances in Applied Energy, 2023, 10: 100132.
AEii International Applied Energy and EnergyVision Youth Scientists Forum Report:
https://mp.weixin.qq.com/s/9FyaH55gpaKFirXhlrboGg
5 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Xiaowen Lai, Qing Xia, Chongqing Kang. Incentive mechanism
for clearing energy and reserve markets in multi-area power systems. IEEE Transactions on Sustainable Energy, 2020,
11(4): 2470 – 2482.
6 Jianxiao Wang#, Junjie Qin, Haiwang Zhong*, Ram Rajagopal, Qing Xia, Chongqing Kang. Reliability value of
distributed solar+storage systems amidst rare weather events. IEEE Transactions on Smart Grid, 2019, 10(4): 4476 –
4486.
7 Jianxiao Wang#, Haiwang Zhong*, Xiaowen Lai, Qing Xia, Yang Wang, Chongqing Kang. Exploring key weather
factors from analytical modeling toward improved solar power forecasting. IEEE Transactions on Smart Grid, 2019,
10(2): 1417-1427.
8 Jianxiao Wang#, Haiwang Zhong, Qing Xia*, Chongqing Kang. Optimal planning strategy for distributed energy
resources considering structural transmission cost allocation. IEEE Transactions on Smart Grid, 2018, 9(5):
5236-5248.
9 Jianxiao Wang#, Haiwang Zhong, Chin-Woo Tan, Xiao Chen, Ram Rajagopal, Qing Xia*, Chongqing Kang.
Economic benefits of integrating solar-powered heat pumps in a CHP system. IEEE Transactions on Sustainable
Energy, 2018, 9(4): 1702-1712.
10 Jianxiao Wang#, Haiwang Zhong, Ziming Ma, Qing Xia*, Chongqing Kang. Review and prospect of integrated.

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

 

Zubaida Rehman- IoT security – Best Researcher Award

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Zubaida Rehman- IoT security

Dr.   Zubaida  Rehman distinguished academic and researcher in the field IoT security. The focal point of her research was to enhance energy production while minimizing wake effects, a challenge that she addressed effectively through the application of Genetic Algorithms. This comprehensive study not only deepened her understanding of cutting-edge technologies in the field but also contributed to the ongoing discourse surrounding sustainable energy solutions.

Education

From 2012 to 2015, she pursued her Master of Computer Science at the National University of Computer and Emerging Sciences in Islamabad, Pakistan. Throughout this academic journey, she specialized in various domains such as Computational Intelligence, Advanced Databases, Cloud Computing, and Evolutionary Computation. The culmination of her academic endeavors was manifested in her research thesis, where she delved into the intricate realm of the Wind Turbine Layout Optimization Problem. Employing the innovative approach of Genetic Algorithms, she endeavored to optimize the layout design by incorporating diverse turbine sizes.

Professional Profiles:

Research Interest
With a diverse set of technical skills and a keen interest in cutting-edge research, she has a strong foundation in data science, encompassing data analysis and business analytics. Her expertise extends to areas such as cybersecurity, Internet of Things (IoT), and machine learning. Adept in computational intelligence, she excels in addressing real-world optimization problems with a focus on cost-effective and efficient analyses. Her proficiency in big data management within cloud environments is demonstrated through her work on effective scheduling for incoming data stream processing.
Work Experience
Her professional journey includes roles as a Software Engineer at KN Technologies Islamabad (Part Time) from January 2016 to December 2016, where she contributed to projects developed in C, C#, and PHP, demonstrating her skills in project planning and execution. As a Software Developer at Technology Architect Islamabad from January 2014 to December 2015, she engaged in the design and testing of ongoing projects, particularly focusing on Infinite-Space Shortest Path Problems and Semicontractive Dynamic Programming.
In the academic realm, she has made notable contributions with research papers published in renowned conferences such as IEEE Conference on Cloud Computing and Big Data Analysis 2016. Her survey paper on “Survey on Branch Prediction Techniques” was published in RJIIT 2017. She has further showcased her research acumen through term papers and reviews, including topics like the automatic design of multi-objective ant colony optimization algorithms, emerging trends in cloud computing, imperfect distributed learning in traffic light control, and a survey paper on the Rapid Multi-Agent Development Toolkit. Through her extensive academic and professional background, she continues to be a valuable asset in the intersection of technology, research, and software development.
Publication