Ms. Lingxiao Qu – kernel method – Best Researcher Award

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Ms. Lingxiao Qu - kernel method - Best Researcher Award

The University of Aizu - China

Author Profile 

ORCID 

🎓 Early academic pursuits

Lingxiao Qu began her academic journey with a strong foundation in computer science and technology, earning her bachelor’s degree from north china electric power university in china between october 2013 and september 2017. during this time, she developed a deep interest in embedded systems and power electronics, which laid the groundwork for her future academic and research pursuits. her academic dedication and performance paved the way for graduate-level opportunities and advanced research training.

👩‍💻 Professional endeavors

Following her undergraduate studies, lingxiao pursued a master’s degree in software engineering at guangxi normal university, china, from october 2018 to september 2021 under the guidance of professor jiang jing. currently, she is completing her ph.d. at the university of aizu, japan, in the graduate school of computer science and engineering, where she has been working under the supervision of professor pei yan since october 2021. throughout her academic trajectory, she has actively contributed to software development projects and collaborative research in power electronics and intelligent systems.

🔬 Contributions and research focus

Lingxiao’s research primarily centers on integrating software engineering with power electronics applications, aiming to enhance the intelligence and efficiency of electronic systems. she has explored machine learning algorithms, optimization techniques, and real-time control strategies to advance the design and deployment of smart power electronic devices. her work demonstrates a profound understanding of cross-disciplinary systems, particularly in how computational methods can elevate power electronics design and operation.

🌍 Impact and influence

Lingxiao Qu’s research contributions have had a growing influence in the field of embedded systems and intelligent control, particularly in applying advanced software engineering approaches to power electronics. her innovative thinking has inspired her peers and collaborators, fostering academic discussions and new explorations within her research group and beyond. her ability to merge theoretical knowledge with practical implementation makes her a valuable contributor to modern electronic system advancements.

📚 Academic cites

Although in the early stages of her research career, lingxiao qu’s scholarly work is gaining academic recognition, especially within the circles of computer science and power electronics. she has been actively engaged in publishing her research findings in international journals and conferences. her work has contributed to evolving academic conversations and citations in areas intersecting computer engineering and smart electrical systems.

🌱 Legacy and future contributions

Lingxiao Qu is poised to become a prominent researcher at the intersection of software engineering and power electronics. her future endeavors are expected to explore green energy applications, smart grids, and ai-powered control systems. with a robust academic foundation and a commitment to innovation, her ongoing and future contributions will likely shape the next generation of intelligent electronic systems. she aims to mentor future researchers and collaborate globally to advance sustainable and efficient electronic technologies.

Notable Publications 

  • Title: A Comprehensive Review on Discriminant Analysis for Addressing Challenges of Class-Level Limitations, Small Sample Size, and Robustness
    Author(s): Lingxiao Qu, Yan Pei
    Journal: Processes

  • Title: A Data Analysis Method Using Orthogonal Transformation in a Reproducing Kernel Hilbert Space
    Author(s): Lingxiao Qu, Yan Pei, Jianqiang Li
    Conference: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

  • Title: Coded Distributed Computing Schemes via Grouping Method
    Author(s): Jing Jiang, Lingling Zhou, Lingxiao Qu
    Conference: Proceedings of the 8th International Conference on Computing and Artificial Intelligence

  • Title: An Approach to Improve Distributed Computing
    Author(s): Jing Jiang, Yiyun Zhong, Lingxiao Qu
    Conference: 2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT)

  • Title: Cascaded Coded Distributed Computing Schemes Based on Placement Delivery Arrays
    Author(s): Jing Jiang, Lingxiao Qu
    Journal: IEEE Access

Dr. Mohsin Masood – Data Scientist – Best Researcher Award 

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Dr. Mohsin Masood - Data Scientist - Best Researcher Award 

Imperial College London - United Kingdom

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Mohsin Masood began his academic journey with a strong foundation in computer science, securing a merit-based msc funding grant from the university of east london (2011–2012). his early academic achievements laid the groundwork for advanced training in health data science, culminating in a phd in statistical modelling from the university of strathclyde, funded by a competitive grant (2014–2017). his scholarly curiosity extended internationally through the erasmus exchange research grant at vsb-technical university of ostrava (2015–2018), where he deepened his expertise in predictive modelling and bioinformatics. during this phase, his interest in power electronics and algorithmic optimization in medical diagnostics emerged as an interdisciplinary focus.

💼 Professional endeavors

With over a decade of experience, mohsin has held impactful roles across academia and research institutions. as an assistant professor in computer science at abasyn university (2018–2022), he designed and taught advanced courses in ai, ml, and data science, incorporating real-world applications in epidemiology and digital health. later, as a senior research fellow at the university of leeds (2022–2023), he led data engineering for a large-scale 2.9 million patient cohort, employing advanced machine learning and nlp tools to analyze multimorbidity and Data Scientist cardiovascular risks. currently, he serves as a research associate at imperial college london (2023–present), where he leads predictive modelling projects on population health, integrating datasets like uk biobank, sail databank, and triphic. he also fosters collaborations with institutions such as sheffield university and a* university of singapore.

🧠 Contributions and research focus

Mohsin’s core research focus lies in multimorbidity, disease progression modelling, and epidemiological risk assessment, particularly within cardiovascular and pulmonary health Data Scientist domains. he applies deep learning, survival analysis, and multistate modelling to interpret complex patient trajectories and disease clustering. his work with electronic health records (ehrs) like hospital episode statistics (hes) reflects a commitment to improving precision medicine. integrating technologies from power electronics into patient monitoring systems has been a unique dimension of his research, promoting real-time diagnostics and health alerts. he has also contributed to educational leadership by mentoring bsc and msc students in ai-based health science projects.

🌍 Impact and influence

Mohsin’s influence extends beyond academia through his involvement in cross-institutional research, digital outreach, and public health strategy. at imperial’s national heart and lung institute (nhli), he manages social media communications to boost public engagement with medical data science. his high-impact publications have contributed to the growing intersection of Data Scientist computational modelling and health outcomes, often cited in cardiovascular and cancer research communities. he is recognized for bridging the gap between statistical modelling and power electronics, showing how smart analytics can optimize hardware for healthcare delivery.

📚 Academic cites

His academic influence is reflected in high citation counts across journals focusing on biostatistics, machine learning in medicine, and epidemiology. notable contributions include projects funded by imperial nhli’s pilot project award (2023–2024) and royan pharmaceutical’s breast cancer research grant (2020–2021). his statistical toolkits and predictive algorithms are widely referenced in studies involving survival analysis, deep learning applications in ehrs, and risk prediction modelling.

🧬 Legacy and future contributions

Mohsin’s legacy lies in fostering a data-driven healthcare ecosystem where interdisciplinary tools empower clinicians and researchers alike. he aims to develop scalable, explainable ai systems for public health, enabling real-time decision-making in hospitals and remote settings. leveraging power electronics, he envisions the integration of wearable technologies with ai for early disease detection and patient monitoring. his commitment to mentoring the next generation of health data scientists ensures a lasting academic and societal impact.

Notable Publications 

  • Title: Emotion classification and crowd source sensing; a lexicon based approach
    Authors: R. Kamal, M.A. Shah, C. Maple, M. Masood, A. Wahid, A. Mehmood
    Journal: IEEE Access

  • Title: An improved particle swarm algorithm for multi-objectives based optimization in MPLS/GMPLS networks
    Authors: M. Masood, M.M. Fouad, R. Kamal, I. Glesk, I.U. Khan
    Journal: IEEE Access

  • Title: Energy efficient software defined networking algorithm for wireless sensor networks
    Authors: M. Masood, M.M. Fouad, S. Seyedzadeh, I. Glesk
    Journal: Transportation Research Procedia

  • Title: Proposing bat inspired heuristic algorithm for the optimization of GMPLS networks
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2017 25th Telecommunication Forum (TELFOR)

  • Title: Analysis of artificial intelligence-based metaheuristic algorithm for MPLS network optimization
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2018 20th International Conference on Transparent Optical Networks (ICTON)

Dr. Lamine Mbarki – Stochastic and probability – Best Researcher Award

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Dr. Lamine Mbarki - Stochastic and probability - Best Researcher Award

University of Tunis El Manar - Tunisia

Author Profile 

SCOPUS 

Early academic pursuits 🎓

Lamine Mbarki's academic journey began with a strong foundation in mathematics, earning his baccalaureate diploma in 2006. his passion for the subject led him to pursue a diplomate in mathematics and computer sciences from the faculty of sciences of monastir, tunisia, in 2008. he furthered his expertise with a master's degree in mathematics in 2010, followed by a master's of research in harmonic analysis in 2012. his research, supervised by mohamed sifi and dominique bakry, explored markovian operators and hypergroup properties, setting the stage for his ph.d. work. he completed his ph.d. at the faculty of sciences of tunis, focusing on the p(x)-laplacian operator and its associated operators, a significant contribution to the field of differential equations.

Professional endeavors 👨‍🏫

Currently an assistant professor in the mathematics department at the faculty of sciences of tunis, lamine mbarki has been dedicated to academia, imparting knowledge and advancing mathematical research. his teaching and mentorship have influenced many students, particularly in areas such as partial differential equations, fractional calculus, and stochastic analysis. his institutional affiliation with the university of tunis el manar reflects his commitment to academic excellence and research development.

Contributions and research focus 🔬

Dr. Mbarki's research focuses on the mathematical study of partial differential equations, fractional calculus, probability, and dynamical systems. his significant contributions include his work on the hypergroup property and the study of the p(x)-laplacian operator. this research has advanced the understanding of complex mathematical structures and their applications in various scientific fields. his interdisciplinary approach bridges theoretical mathematics with practical applications,  Stochastic and probability particularly in stochastic processes and dynamic systems.

Accolades and recognition 🏅

Throughout his academic career, dr. mbarki has received recognition for his pioneering research in mathematics. his collaborations with esteemed supervisors such as dominique bakry and mounir bezzarga have cemented his reputation as a notable researcher in harmonic analysis and operator theory. his work continues to be  Stochastic and probability cited and utilized by researchers across the globe, particularly in the areas of partial differential equations and probability theory.

Impact and influence 🌍

Dr. Mbarki’s research has had a wide-reaching impact, particularly in advancing the understanding of complex mathematical systems. his work on fractional calculus and stochastic analysis has applications in physics, engineering, and economics, influencing how mathematical models are employed in real-world scenarios. as a  Stochastic and probability teacher and researcher, his contributions have shaped the careers of many students and young researchers, fostering a new generation of mathematical minds.

Legacy and future contributions 🔮

As a dedicated mathematician, dr. mbarki's legacy will be defined by his innovative work in partial differential equations and stochastic processes. his research continues to evolve, and he is expected to contribute further to the fields of fractional calculus and dynamical systems. his future work will likely continue to impact both theoretical mathematics and its applied fields, ensuring that his contributions remain influential for years to come.

Notable Publications 

  1. Title: "A degenerate Kirchhoff-type problem involving variable s(·)-order fractional p(·)-Laplacian with weights"
    Authors: Allaoui, M., Hamdani, M.K., Mbarki, L.
    Journal: Periodica Mathematica Hungarica, 2024, 88(2), pp. 396–411
  2. Title: "Existence and Multiplicity of Solutions for a Class of Kirchhoff–Boussinesq-Type Problems with Logarithmic Growth"
    Authors: Carlos, R.D., Mbarki, L., Yang, S.
    Journal: Mediterranean Journal of Mathematics, 2024, 21(3), 108
  3. Title: "Existence of Multiple Solution for a Singular p(x)-Laplacian Problem"
    Authors: Ghanmi, A., Mbarki, L., Choudhuri, D.
    Journal: Complex Analysis and Operator Theory, 2024, 18(2), 26
  4. Title: "Unified approach to nonlinear Caputo fractional derivative boundary value problems: extending the upper and lower solutions method"
    Authors: Talib, I., Batool, A., Sousa, J.V.D.C., Lamine, M.
    Journal: Journal of Mathematics and Computer Science, 2024, 37(1), pp. 20–31
  5. Title: "Solutions for a Nonlocal Elliptic System with General Growth"
    Authors: Mbarki, L., Tavares, L.S., Sousa, J.V.C.
    Journal: Complex Analysis and Operator Theory, 2023, 17(8), 134