Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

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Dr. Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

Dr. Chaima Aouiche is a dedicated academic and researcher in computer science with expertise in artificial intelligence, machine learning, cybersecurity, and bioinformatics. Born on October 24, 1990, in Tebessa, Algeria, she began her academic journey at Larbi Tebessi University and pursued her Ph.D. at Northwestern Polytechnical University (NPU), China. With international exposure, Dr. Aouiche has authored impactful publications on cancer gene prediction, data integration, and AI-based energy systems. She has collaborated across disciplines and countries, contributing to international conferences and peer-reviewed journals. Currently serving as a university teacher in Algeria, she is also a multilingual educator with teaching experience in China and Algeria. Dr. Aouiche combines technical knowledge with strong interpersonal skills and a passion for teaching, traveling, and community service, making her a well-rounded and globally competent scholar committed to innovation and education.

Profile

🎓 Education

Dr. Chaima Aouiche holds a strong academic foundation in computer science. She earned her Bachelor’s degree (2008–2011) and Master’s degree (2011–2013) in Computer Science from Larbi Tebessi University, Algeria, where she was recognized with the “Outstanding Student Award” in 2013. She expanded her horizons by studying the Chinese language for a year (2013–2014) at Northwestern Polytechnical University (NPU) in Xi’an, China. She then pursued a Ph.D. in Computer Science and Technology at NPU (2014–2021), focusing on stage-specific gene prediction, big data integration, and artificial intelligence. Throughout her academic journey, she acquired various global certifications, including Artificial Intelligence Foundations, Advanced Machine Learning, and Deep Learning, further enriching her qualifications. With multilingual skills in Arabic, French, English, and Chinese, she integrates global perspectives into her research and teaching. Her academic path reflects both depth and international breadth.

🧪 Experience

Dr. Chaima Aouiche has a diverse background in academia, industry, and cross-cultural teaching. She began her professional career in project management at MPE-MPI Investments, Tebessa (2011–2013), where she gained hands-on technical and administrative skills. In 2017, she taught English and Arabic in Xi’an, China, enhancing her intercultural communication and educational outreach. Currently, she works as a university teacher in Algeria, engaging in teaching, research supervision, and publication. Her training includes courses in project management, AI, and big data, complemented by technical expertise in programming (Python, Java, R), MATLAB, web technologies, and networking. Her ability to communicate in four languages (Arabic, French, English, Chinese) and her volunteering and mentoring activities reflect her commitment to holistic professional development. Dr. Aouiche’s career is defined by interdisciplinary collaboration, international exposure, and a passion for applied technological solutions, making her an asset in both academia and industry.

🏅 Awards and Honors

Dr. Aouiche’s academic and professional excellence has been recognized through multiple awards and certificates. She was awarded the Outstanding Student Award by Larbi Tebessi University in 2013. Her further accolades include numerous international certifications, such as the HSK 4 Chinese Proficiency Certificate, Artificial Intelligence and Big Data Training (Xi’an Jiaotong University), AI Foundations Masterclass (2023), and Advanced Machine Learning and Deep Learning Certificates (2024). She has also been recognized for her participation in global academic initiatives, such as the International Winter Camp (2017) and the Silk Road Engineering Science Program (2020). In addition to formal honors, her significant co-authorship on high-impact publications in BMC Bioinformatics, Frontiers in Genetics, and IEEE conferences speaks to her professional standing. These accolades collectively highlight her dedication to academic distinction, global engagement, and technological innovation.

🔬 Research Focus

Dr. Aouiche’s research intersects bioinformatics, artificial intelligence, machine learning, and cybersecurity. Her work has emphasized integrating multiple datasets to predict stage-specific cancer-related genes, mapping copy number variations, and modeling aberrant genomic events. She co-authored key studies published in BMC Bioinformatics, Frontiers in Genetics, and Quantitative Biology, which propose dynamic gene modules and data-driven cancer diagnostics. Recent work explores ensemble learning and AI approaches to detect cyberattacks using integrated datasets, showing a pivot toward cybersecurity and smart systems. Additionally, her research extends into renewable energy, specifically applying AI models to optimize photovoltaic systems and MPPT (Maximum Power Point Tracking) control. Her interdisciplinary approach bridges computational biology and engineering, reflecting her adaptability and innovative vision. Dr. Aouiche is particularly interested in applied AI that addresses real-world challenges in medicine, energy, and security, with a growing focus on industry 4.0 applications.

âś… Conclusion

Dr. Chaima Aouiche is an innovative computer scientist and academic whose international education, multidisciplinary research in AI and bioinformatics, commitment to teaching, and dynamic professional experiences make her a valuable contributor to global science and technology.

Publications

Quanying Lu | Forecasting | Best Researcher Award

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Dr. Quanying Lu | Forecasting | Best Researcher Award

Dr. Quanying Lu is an Associate Professor at Beijing University of Technology, specializing in energy economics, forecasting, and systems engineering. 🎓 She completed her Ph.D. at the University of Chinese Academy of Sciences and has published 30+ papers in top journals, including Nature Communications and Energy Economics. 📚 She has held postdoctoral and research positions in prestigious institutions and actively contributes to policy research. 🌍

Profile

Education 🎓

  • Ph.D. (2017-2020): University of Chinese Academy of Sciences, School of Economics and Management, supervised by Prof. Shouyang Wang.
  • M.Sc. (2014-2017): International Business School, Shaanxi Normal University, supervised by Prof. Jian Chai.
  • B.Sc. (2010-2014): International Business School, Shaanxi Normal University, Department of Economics and Statistics.

Experience 👨‍🏫

  • Associate Professor (06/2022–Present), Beijing University of Technology, supervising Ph.D. students.
  • Postdoctoral Fellow (07/2020–05/2022), Academy of Mathematics and Systems Science, Chinese Academy of Sciences.
  • Research Assistant (08/2018–10/2018), Department of Management Sciences, City University of Hong Kong.

Awards & Recognitions 🏅

  • Outstanding Young Talent, Phoenix Plan, Chaoyang District, Beijing (2024).
  • Young Scholar of Social Computing, CAAI-BDSC (2024).
  • Young Scholar of Forecasting Science, Frontier Forum on Forecasting Science (2024).
  • Young Elite Scientists Sponsorship, BAST (2023).
  • Excellent Mentor, China International “Internet Plus” Innovation Competition (2023).

Research Interests 🔬

Dr. Lu specializes in energy economics, environmental policy analysis, economic forecasting, and systems engineering. 📊 Her research addresses crude oil price dynamics, carbon reduction strategies, and financial market interactions. 💡 She integrates machine learning with forecasting models, contributing to sustainable energy and environmental policies. 🌍

Publications 

[1] Liang, Q., Lin, Q., Guo, M., Lu, Q., Zhang, D. Forecasting crude oil prices: A
Gated Recurrent Unit-based nonlinear Granger Causality model. International
Review of Financial Analysis, 2025, 104124.
[2] Wang, S., Li, J., Lu, Q. (2024) Optimization of carbon peaking achieving paths in
Chinas transportation sector under digital feature clustering. Energy, 313,133887
[3] Yang, B., Lu, Q.*, Sun, Y., Wang, S., & Lai, K. K. Quantitative evaluation of oil
price fluctuation events based on interval counterfactual model (in Chinese).
Systems Engineering-Theory & Practice, 2023, 43(1):191-205.
[4] Lu, Q.*, Shi, H., & Wang, S. Estimating the shock effect of “Black Swan” and
“Gray Rhino” events on the crude oil market: the GSI-BN research framework (in
Chinese). China Journal of Econometrics, 2022, 1(2): 194-208.
[5] Lu, Q., Duan, H.*, Shi, H., Peng, B., Liu, Y., Wu, T., Du, H., & Wang, S*. (2022).
Decarbonization scenarios and carbon reduction potential for China’s road
transportation by 2060. npj Urban Sustainability, 2: 34. DOI:
https://www.nature.com/articles/s42949-022-000.
[6] Lu, Q., Sun, Y.*, Hong, Y., Wang, S. (2022). Forecasting interval-valued crude
oil prices via threshold autoregressive interval models. Quantitative Finance,
DOI: 10.1080/14697688.2022.2112065
Page 3 / 6
[7] Guo, Y., Lu, Q.*, Wang, S., Wang, Q. (2022). Analysis of air quality spatial
spillover effect caused by transportation infrastructure. Transportation Research
Part D: Transport & Environment, 108, 103325.
[8] Wei, Z., Chai, J., Dong, J., Lu, Q. (2022). Understanding the linkage-dependence
structure between oil and gas markets: A new perspective. Energy, 257, 124755.
[9] Chai, J., Zhang, X.*, Lu, Q., Zhang, X., & Wang, Y. (2021). Research on
imbalance between supply and demand in China’s natural gas market under the
double -track price system. Energy Policy, 155, 112380.
[10]Lu, Q., Sun, S., Duan, H.*, & Wang, S. (2021). Analysis and forecasting of crude
oil price based on the variable selection-LSTM integrated model. Energy
Informatics, 4 (Suppl 2):47.
[11]Shi, H., Chai, J.*, Lu, Q., Zheng, J., & Wang, S. (2021). The impact of China’s
low-carbon transition on economy, society and energy in 2030 based on CO2
emissions drivers. Energy, 239(1):122336, DOI: 10.1016/j.energy.2021.122336.
[12]Jiang, S., Li, Y., Lu, Q., Hong, Y., Guan, D.*, Xiong, Y., & Wang, S.* (2021).
Policy assessments for the carbon emission flows and sustainability of Bitcoin
blockchain operation in China. Nature Communications, 12(1), 1-10.
[13]Jiang, S., Li Y., Lu, Q., Wang, S., & Wei, Y*. (2021). Volatility communicator or
receiver? Investigating volatility spillover mechanisms among Bitcoin and other
financial markets. Research in International Business and Finance,
59(4):101543.
[14]Lu, Q., Li, Y., Chai, J., & Wang, S.* (2020). Crude oil price analysis and
forecasting ：A perspective of “new triangle”. Energy Economics, 87, 104721.
DOI: 10.1016/j.eneco.2020.104721.
[15]Chai, J., Shi, H.*, Lu, Q., & Hu, Y. (2020). Quantifying and predicting the
Water-Energy-Food-Economy-Society-Environment Nexus based on Bayesian
networks – a case study of China. Journal of Cleaner Production, 256, 120266.
DOI: 10.1016/j.jclepro.2020.120266.
[16]Lu, Q., Chai, J., Wang, S.*, Zhang, Z. G., & Sun, X. C. (2020). Potential energy
conservation and CO2 emission reduction related to China’s road transportation.
Journal of Cleaner Production, 245, 118892. DOI:
10.1016/j.jclepro.2019.118892.
[17]Chai, J., Lu, Q.*, Hu, Y., Wang, S., Lai, K. K., & Liu, H. (2018). Analysis and
Bayes statistical probability inference of crude oil price change point.
Technological Forecasting & Social Change, 126, 271-283.
[18]Chai, J., Lu, Q.*, Wang, S., & Lai, K. K. (2016). Analysis of road transportation
consumption demand in China. Transportation Research Part D: Transport &
Environment, 2016, 48:112-124.

 

Rakesh Meena | Applied Mathematics | Best Researcher Award

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Mr. Rakesh Meena | Applied Mathematics | Best Researcher Award

Research Scholar at Sardar Vallabhbhai National Institute of Technology, India

Mr. Rakesh Meena is a promising researcher and Ph.D. candidate at the Department of Mathematics, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India. His academic journey is characterized by a focus on advanced mathematical modeling, fractional calculus, and differential equations. With a blend of theoretical and computational expertise, Mr. Meena is dedicated to contributing to innovative solutions in applied mathematics, particularly in areas like epidemic modeling and dynamic systems. He is driven by the desire to combine research with teaching to foster academic growth and knowledge sharing. Throughout his career, he has earned recognition through prestigious scholarships and fellowships, such as the Junior Research Fellowship (JRF) and Senior Research Fellowship (SRF) from CSIR-UGC. His research contributions, including numerous journal publications and conference presentations, reflect his deep commitment to advancing mathematical sciences. Mr. Meena’s aspirations align with the goal of bringing meaningful change to both the academic community and society through his research and teaching.

Profile

Scopus

Google Scholar

Orcid

 

Education 🎓

Mr. Rakesh Meena’s educational background forms a solid foundation for his research career. He began his academic journey at Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, where he completed his Five-Year Integrated M.Sc. in Mathematics with first division in 2020. Following this, he embarked on his Ph.D. in Mathematics, with a focus on linear and nonlinear fractional differential equations. Under the guidance of Dr. Sushil Kumar, he has made notable progress in mathematical modeling, particularly through the semi-analytical approach. His cumulative performance during his Ph.D. coursework reflects dedication, maintaining a CGPA of 7.25. Throughout his education, Mr. Meena has demonstrated a continuous pursuit of knowledge, aiming to contribute to the vast field of mathematical sciences. His educational path has not only provided him with strong analytical skills but also a deep understanding of both theoretical and computational methods. This educational experience, combined with his passion for research, serves as a solid launchpad for his future contributions to the scientific community.

Work Experience đź’Ľ

Mr. Rakesh Meena’s professional experience includes extensive academic research at the Department of Mathematics, SVNIT, Surat. Currently pursuing his Ph.D., Mr. Meena has contributed to a range of mathematical research, particularly in fractional calculus, epidemic modeling, and nonlinear differential equations. His expertise in using semi-analytical methods, such as the Residual Power Series (RPS) method and Homotopy Analysis Method, allows him to solve complex mathematical equations, which are pivotal in the fields of mathematical modeling and computational mathematics. As a junior and senior research fellow (JRF/SRF), he has been involved in multiple research projects that align with his goal of applying mathematical theory to real-world problems. Additionally, Mr. Meena has shared his research findings through several journal articles and conference papers, expanding his influence in academic circles. Beyond research, his role in mentoring and teaching aligns with his long-term goal of working in an institution where teaching and research go hand-in-hand. His participation in both national and international conferences further strengthens his professional experience, offering him a platform to engage with global research communities.

Awards and Honors

Mr. Rakesh Meena has been the recipient of several prestigious awards and fellowships, recognizing his academic excellence and research potential. In 2020, he was awarded the Junior Research Fellowship (JRF) by CSIR-UGC, which was followed by the Senior Research Fellowship (SRF) in 2022. These fellowships are granted to outstanding researchers in the field of mathematical sciences and are a testament to his proficiency and dedication to research. Additionally, Mr. Meena qualified for GATE (Graduate Aptitude Test in Engineering) in both 2022 and 2023, further cementing his academic credentials. His work, particularly in mathematical modeling and fractional calculus, has earned him recognition in the academic community. His achievements also include being a recipient of certification from CSIR-HRDG, highlighting his commitment to continuous learning and development. These awards and honors reflect Mr. Meena’s dedication to pushing the boundaries of mathematical research, and they serve as a foundation for his continued contributions to the scientific community.

Research Interests

Mr. Rakesh Meena’s primary research interests lie in mathematical modeling, fractional differential equations, and dynamic systems. His doctoral research specifically focuses on linear and nonlinear fractional differential equations, employing semi-analytical methods for their solutions. He aims to explore these equations’ applications in real-world phenomena, such as epidemic modeling, fluid dynamics, and wave propagation. His work in fractional calculus offers new insights into the mathematical descriptions of complex systems, which are often difficult to model using traditional integer-order differential equations. Through his research, Mr. Meena is particularly interested in understanding the behavior of systems with memory and hereditary properties, common in biological and physical systems. In addition to his work on differential equations, he is exploring the application of the Residual Power Series (RPS) method and other numerical techniques, such as the Euler and Runge-Kutta methods, to obtain approximate solutions to these complex models. His interdisciplinary approach to mathematical modeling promises to contribute to both the advancement of mathematical theory and its practical applications in fields like epidemiology, physics, and engineering.

Research Skills

Mr. Rakesh Meena’s research skills are diverse, encompassing both theoretical and computational techniques. His proficiency in mathematical modeling, especially in the context of fractional differential equations, stands out as a major strength. He is well-versed in various semi-analytical methods, notably the Residual Power Series (RPS) and Homotopy Analysis Method, to solve complex differential equations. These techniques are especially useful in capturing the dynamics of systems governed by fractional order equations, which are prevalent in many natural and social systems. Mr. Meena also possesses strong numerical skills, applying methods like the Euler method, Runge-Kutta method, and finite difference methods for computational analysis. He is skilled in using computational tools, including MATLAB, Maple, Mathematica, and LaTeX, to model, analyze, and visualize mathematical problems. His ability to integrate both analytical and numerical methods enables him to approach research challenges from a comprehensive perspective. Moreover, his academic rigor and attention to detail contribute to his systematic approach to research, making his work both reliable and impactful.

đź“š Publications

Conclusion 

Mr. Rakesh Meena is a strong contender for the Best Researcher Award due to his excellent academic record, innovative research in fractional differential equations, and contribution to mathematical modeling. His expertise in semi-analytical and numerical methods provides significant value to his field. With a broader impact focus and increased public engagement, he has the potential to make transformative contributions to both academia and society. This will further cement his position as a leader in his field. 🌟