Ziang Liu | Engineering | Best Researcher Award

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Mr. Ziang Liu | Engineering | Best Researcher Award

Nanjing University | China

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Early Academic Pursuits

Mr. Ziang Liu began his academic journey with distinction at Tianjin University, where he earned his Bachelor of Science in Electronic Engineering. His strong foundation in engineering and mathematics laid the groundwork for advanced research and innovation. Continuing his academic trajectory, he pursued a Master of Science in Electronic Engineering at the prestigious Nanjing University, where he was recognized as an Outstanding Student and awarded the First-class Academic Scholarship.

Professional Endeavors

Ziang has accumulated valuable industry experience through impactful internships. At Meituan Shanghai, he served as an LLMs Evaluation Algorithm Intern, where he designed evaluation schemes and analyzed instruction-following capabilities across large language models such as Qwen, Doubao, ChatGPT 3.5/4, and Llama2-70B.  In another significant role at Alibaba DingTalk in Hangzhou, he worked on the back-end development of Chatmemo, an enterprise AI assistant. There, he implemented knowledge graph subgraph displays and integrated Retrieval-Augmented Generation (RAG), significantly boosting response speed and system performance.

Contributions and Research Focus

Mr. Liu’s core interests revolve around LLMs (Large Language Models), RAG (Retrieval-Augmented Generation), and knowledge graph technologies. He has contributed to the design and optimization of backend systems for intelligent applications in healthcare and enterprise settings. His work on deploying frameworks like Graph RAG and utilizing tools like Redis, MySQL, and Spring Boot has shown practical outcomes in real-world systems, particularly in performance optimization, load balancing, and cache management. His participation in the Nanjing University Intelligent Hospital Project resulted in a custom online medication purchasing system, complete with AI-powered Q&A capabilities and scalable backend infrastructure.

Accolades and Recognition

Ziang Liu’s academic excellence is evident through a remarkable series of accolades earned during both his undergraduate and postgraduate studies. He was honored as the Outstanding Student of Nanjing University in 2023 and received the First-class Academic Scholarship in 2022, recognizing his superior academic performance. His analytical and technical skills were demonstrated through competition achievements, including the Third Prize in the 19th Chinese Graduate Mathematical Modeling Competition (2022) and the Second Prize in the 18th Chinese Electronic Design Competition (2023). Earlier in his academic journey, he was named a Meritorious Winner in the Mathematical Contest in Modeling (MCM) in 2021 and was recognized as an Outstanding Graduate of Tianjin University in 2022. These accomplishments reflect his consistent dedication, innovation, and leadership in engineering and applied mathematics.

Impact and Influence

Ziang Liu’s work has made a tangible impact in both academia and industry. His efforts in improving instruction-following performance in LLMs and optimizing backend systems for enterprise AI applications have proven valuable for real-world implementation. His innovations in intelligent hospital systems demonstrate a commitment to applying advanced AI technologies to enhance societal well-being and operational efficiency.

Legacy and Future Contributions

Poised at the intersection of AI, backend engineering, and applied innovation, Mr. Ziang Liu is emerging as a key contributor to the next generation of AI infrastructure. His hands-on experience with cutting-edge technologies like gRPC, GraphRAG, JWT, and multi-threaded optimization positions him to drive future advancements in AI systems, enterprise platforms, and digital healthcare. With a strong academic record and robust technical expertise, he is well on his way to becoming a leading voice in intelligent systems development.

 

 

Publications

Channel-Dependent Multilayer EEG Time-Frequency Representations Combined with Transfer Learning-Based Deep CNN Framework for Few-Channel MI EEG Classification

Authors: Ziang Liu, Kang Fan, Qin Gu, Yaduan Ruan
Journal: Bioengineering
Year: 2025

Studying Multi-Frequency Multilayer Brain Network via Deep Learning for EEG-Based Epilepsy Detection

Authors: Weidong Dang, Dongmei Lv, Linge Rui, Ziang Liu, Guanrong Chen, Zhongke Gao
Journal: IEEE Sensors Journal
Year: 2021

Akash Sharma | Engineering | Best Researcher Award

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Mr. Akash Sharma | Engineering | Best Researcher Award

Malaviya National Institute of Technology | India

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Early Academic Pursuits 🎓

Mr. Akash Sharma’s academic journey began with a solid foundation in Electrical Engineering. He earned his Bachelor of Technology (B-Tech) in Electrical Engineering from Arya College of Engineering & IT, RTU Kota in 2016, achieving a commendable 68.5%. He further pursued a Master of Technology (M-Tech) in Power Systems from Malaviya National Institute of Technology (MNIT), Jaipur in 2021, with a CGPA of 7.72. His quest for knowledge continued as he completed his PhD in Power Systems at MNIT, Jaipur in 2022, with a CGPA of 7.6. His doctoral research focused on the performance analysis of smart grids, utilizing data-driven methods and machine learning.

Professional Endeavors 💼

Mr. Sharma's professional experience includes diverse roles. He served as a guest faculty at the College of Dairy Science and Technology, Jobner, from 2021 to 2022, where he contributed to the academic environment. Prior to this, he worked as a Graduate Engineer Trainee (GET) at IRB Infrastructure Ltd., handling electrical aspects of various plants and overseeing staff welfare. Additionally, Mr. Sharma gained valuable experience as a Public Relations Officer (PRO) with Indian Business Pages in 2016.

Contributions and Research Focus 🔍

Mr. Sharma's research is centered on the performance analysis of smart grids, integrating deep learning and machine learning techniques. His PhD work emphasizes cybersecurity in energy consumption, aiming to develop advanced models for detecting and mitigating cyber-attacks on smart grid infrastructures. His work also explores the seamless integration of renewable energy sources and optimization of smart grid performance. He has published a notable research paper on voltage profile enhancement using FACTS devices and has worked on solar tracking systems.

Accolades and Recognition 🏅

While Mr. Sharma has not yet received major awards, his active participation in co-curricular activities and his impactful research reflect his dedication. His work on smart grids and renewable energy has been well-received in academic circles, demonstrating his commitment to advancing the field of electrical engineering.

Impact and Influence 🌟

Mr. Sharma's contributions to smart grid technology and renewable energy integration are shaping the future of power systems. His work in enhancing grid performance and addressing cybersecurity concerns is crucial in the evolving landscape of energy management. His involvement in both academic and professional settings highlights his influence on the next generation of engineers and researchers.

Legacy and Future Contributions 🚀

Looking ahead, Mr. Sharma's ongoing research and professional activities will continue to impact the field of electrical engineering. His focus on smart grids and renewable energy positions him to contribute significantly to advancements in these areas. As he builds on his experiences and research, he is poised to leave a lasting legacy in the realm of power systems and sustainable energy solutions.

 

Publications

  • Title: Anomaly detection in smart grid using optimized extreme gradient boosting with SCADA system
  • Authors: Sharma, A., Tiwari, R.
  • Journal: Electric Power Systems Research
  • Year: 2024

 

  • Title: Load Shedding Technique for Maintaining Voltage Stability
  • Authors: Sharma, P.K., Sharma, A., Tiwari, R.
  • Journal: Lecture Notes in Electrical Engineering
  • Year: 2024

 

 

 

 

Vishnu Dharssini A.C | Engineering | Best Researcher Award

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Ms. Vishnu Dharssini A.C | Engineering | Best Researcher Award

Thiagarajar College of Engineering | India

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Early Academic Pursuits

Ms. Vishnu Dharssini A.C has consistently demonstrated a passion for knowledge and excellence in her academic journey. Her pursuit of higher education in Electrical and Electronics Engineering began at Thiagarajar College of Engineering, Madurai, where she excelled academically. She was awarded a Silver Medal as the Best Outgoing Student of the Year 2021. Her dedication and outstanding performance were further recognized through awards for her achievements in the Anna University semestral examinations for two consecutive years, 2017 and 2018.

Professional Endeavors

Ms. Dharssini's professional endeavors are marked by her dedication to research and development in the field of Electrical and Electronics Engineering. She has engaged in various innovative projects, such as the simulation and analysis of a standalone microgrid for grid stability and modeling energy demand for an educational institution. Her current work focuses on an IoT-based demand side management and control scheme for smart grids. Additionally, she has gained valuable industrial exposure through her involvement in projects and collaborations.

Contributions and Research Focus

Ms. Dharssini has made significant contributions to the field of Electrical and Electronics Engineering, particularly in smart grid and renewable energy technologies. She is also exploring the burgeoning fields of machine learning and deep learning. Her research is supported by her proficiency in tools and software such as MATLAB, ETAP, Power World Simulator, Grafana, HOMER, DIG SILENT Power Factory Software, and PARAMICS. Her dedication to research is evident from her publications, which include two book chapters, seven conference papers, and five journal articles.

Accolades and Recognition

Ms. Dharssini's academic and research excellence have been widely recognized. In June 2023, she was selected for the "International Young Scientist Awards" under the category of "Best Researcher Award." Her commitment to continuous learning and skill enhancement is evident from her participation in numerous courses during the COVID-19 lockdown, including over five IEEE courses and five Coursera courses. Her efforts were further acknowledged when she received the "Savitha" scheme fellowship from Thiagarajar Research Fellowship in June 2022.

Impact and Influence

Ms. Dharssini's impact extends beyond her research contributions. She has actively participated in international conferences, where she has presented her work and engaged with the global academic community. Her involvement in initiatives such as the "Science and Technology Capacity Building for Industrial Needs" by the Tamil Nadu Council for Science and Technology in Chennai in 2019 highlights her commitment to applying her knowledge for industrial and societal benefits.

Legacy and Future Contributions

Ms. Vishnu Dharssini A.C's legacy in Electrical and Electronics Engineering is marked by her rigorous research, academic excellence, and dedication to continuous learning. As she continues her career, her contributions to smart grid technology, renewable energy systems, and the integration of machine learning in engineering are anticipated to advance the field significantly. Her ongoing research and professional endeavors promise to leave a lasting impact on the scientific community and pave the way for future innovations.

 

Notable Publications

Three-tier integrated demand-supply energy management for optimized energy usage in institutional building 2024

Smart Energy Source Management in a Commercial Building Microgrid 2024

An Investigation on Static Reconfiguration of Solar Photovoltaic Panels by Adopting Arithmetic Array Modelling 2023 (1)

Deployment of IoT-Based Smart Demand-Side Management System with an Enhanced Degree of User Comfort at an Educational Institution 2023 (4)

Energy Pattern Classification and Prediction in an Educational Institution using Deep Learning Framework 2022 (5)

 

 

Saida Bedoui | Engineering | Best Researcher Award

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Dr. Saida Bedoui | Engineering | Best Researcher Award

Gabes University | Tunisia

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Early Academic Pursuits

Dr. Saida Bedoui’s academic journey is marked by an exceptional pursuit of knowledge and excellence in electrical engineering and related fields. She began her educational journey at Lycée République in Gabès, Tunisia, where she earned her Bachelor of Mathematics in June 2003. Following this, she attended the Higher Institute of Applied Sciences and Technology of Gabes, where she completed her preparatory classes for the National Engineering School with a focus on Physics and Mathematics in July 2005, securing admission to the engineering school. Her higher education was pursued at the National Engineering School of Gabes, where she obtained her degree in Electric-Automatic Engineering in July 2008, graduating with a “Very Good” rating. She further specialized by obtaining a Master's in Automatic and Intelligent Techniques in June 2009, also with a “Very Good” rating. Dr. Bedoui then achieved her PhD in Electrical Engineering in March 2013 with the highest honors, and later completed her Habilitation Thesis in Electrical Engineering at Gabes University in February 2023.

Professional Endeavors

Dr. Bedoui’s professional career spans several prestigious roles in academia. She started as a contractual lecturer at the National Engineering School of Gabes from 2008 to 2012. She then served as a lecturer at the Higher Institute of Applied Sciences and Technology of Gafsa from 2012 to 2013. Since September 2013, she has been an Assistant Professor at the Higher Institute of Industrial Systems of Gabes, where she has been involved in teaching a variety of subjects, including Automatic, Electronics, and Industrial Computing, at all levels of higher education.

Contributions and Research Focus

Dr. Bedoui’s research interests primarily focus on the identification and control of time-delay systems. Her PhD thesis contributed significantly to this field by proposing methods to identify time-delay systems, addressing the simultaneous identification of time delay and dynamic parameters of both mono-variable and multi-variable time-delay systems. Her work includes the development of new approaches for generating libraries of local models for nonlinear time-delay systems. Her contributions extend to supervising numerous graduate projects and theses. She has guided students in projects ranging from the design and implementation of road junction prototypes to the modernization of control systems for industrial applications.

Accolades and Recognition

Dr. Bedoui has been recognized for her work with various scholarships and research stays at esteemed institutions. Notably, she received a CSC scholarship for a research stay at Jiangnan University, PR China, in 2023. She has also undertaken research stays at the Laboratory of Engineering Systems in Caen, France, and the Research Center for Automatic Control of Nancy, France.

Impact and Influence

Dr. Bedoui has played a pivotal role in several significant projects and associations. She served as the project manager for the initiative "Strengthening the Capacity of the 4C Center in Training and Support for Students and Young Graduates of ISSI-Gabes" from January 2020 to February 2022. Additionally, she has been the Director of the Career Center and Skills Certification and has been actively involved with the Tunisian Association of Automatic and Digitizing in various capacities since 2010.

Legacy and Future Contributions

Dr. Bedoui’s legacy is characterized by her dedication to advancing the field of electrical engineering through both education and research. Her extensive teaching experience, coupled with her innovative research, has made significant contributions to the academic community. Her work continues to influence the development of automatic and intelligent systems.

 

Notable Publications

Iterative parameter identification for Hammerstein systems with ARMA noises by using the filtering identification idea 2024

On the combined estimation of the parameters and the states of fractional-order systems 2023 (2)

Diagnosis and fault tolerant control against actuator fault for a class of hybrid Dynamic systems 2023 (3)

Convergence Analysis of Forgetting Factor Least Squares Algorithm for ARMAX Time-Delay Models 2022 (1)

Parameter and State Estimation of Nonlinear Fractional-Order Model Using Luenberger Observer 2022 (6)