VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

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Mr. VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM, DTU DELHI, India.

Vikram Singh Kardam is a dedicated researcher and academician specializing in signal processing, currently pursuing his Ph.D. at Delhi Technological University (DTU). With a strong educational foundation, including an M.Tech in Signal Processing and Digital Design, and a B.Tech in Electronics and Communication Engineering, he has consistently demonstrated academic excellence. Vikram has diverse professional experience, having worked both in industry and academia, including roles as a Project Engineer and Assistant Professor. His innovative M.Tech thesis on real-time iris recognition highlights his ability to apply advanced concepts to practical challenges in biometric security. Proficient in multiple programming languages and known for his problem-solving attitude, he blends technical skill with teaching acumen, influencing students and peers alike. His GATE rank and contributions to student development further underscore his commitment to excellence in engineering and education.

Profile

Scopus

 

🎓 Early Academic Pursuits

Vikram Singh Kardam’s academic journey began with a solid foundation in science and technology. He completed his 10th and 12th education from Government Inter College, Agra, achieving commendable marks that laid the groundwork for his future in engineering. His higher education commenced at the University Institute of Engineering and Technology, CSJM University, Kanpur, where he earned his Bachelor of Technology in Electronics and Communication Engineering in 2007 with a respectable score of 73.2%. Driven by a passion for advanced studies, he pursued a Master of Technology in Signal Processing and Digital Design from Delhi Technological University (DTU), securing a CGPA of 8.06 in 2017. His academic path reflects not only consistent effort but also a dedication to the field of signal processing.

🧑‍🏫 Professional Endeavors

Vikram embarked on his professional career with diverse roles that bridged academia and industry. He served as a Project Engineer at ITI Limited, Delhi, and as a Lab Engineer at Dayalbagh Engineering College, Agra, gaining hands-on experience in real-world engineering environments. His passion for teaching led him to academia, where he worked as an Assistant Professor in reputed institutions such as Galgotias College of Engineering and Technology, Greater Noida, and HMR Institute of Technology and Management, Delhi. With around three years of cumulative teaching experience, he has imparted theoretical knowledge and practical insights in Electronics and Communication Engineering, contributing to the academic development of numerous students.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardam’s research delves into the intricacies of digital signal processing with real-world applications. His M.Tech thesis, titled “Real Time Iris Recognition”, showcases his innovation in biometric security systems. By integrating iris recognition with eye-blinking detection using a basic webcam, he proposed a novel, low-cost, and more secure method for identity verification. The system’s robustness and its resistance to hacking highlight his ability to merge theoretical concepts with practical utility. His fluency in programming languages such as MATLAB, C, C++, and Python3 supports his technical versatility in algorithm development and simulation.

🏅 Accolades and Recognition

A noteworthy milestone in Vikram’s academic journey is securing an All India Rank of 5334 in the GATE 2021 examination in Electronics and Communication Engineering. This national-level achievement is a testament to his strong grasp of core concepts and problem-solving acumen. Additionally, his academic performances during B.Tech and M.Tech reflect sustained excellence. His thesis project, recognized for its practical application and innovative approach, further enhances his academic reputation.

📚 Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his students’ academic and professional growth. His commitment to regularly conducting lectures, his focus on ensuring student understanding, and his hands-on approach to lab sessions highlight his dedication to holistic teaching. Beyond knowledge delivery, his empathetic and analytical mindset enables him to mentor students, offer academic guidance, and solve problems effectively. His ability to integrate teaching with research creates an inspiring learning environment.

🌐 Legacy and Future Contributions

Looking forward, Vikram aspires to contribute to both academia and industry through innovative research in signal processing, embedded systems, and biometric technology. His current Ph.D. pursuits are expected to yield impactful contributions to the scientific community, particularly in the areas of real-time data analysis and secure identification systems. With a forward-thinking vision, he aims to blend educational excellence with technological advancement, fostering a new generation of engineers equipped with both critical thinking and creative problem-solving skills.

🧠 Vision and Intellect

At the core of Vikram Singh Kardam’s career is a mindset defined by curiosity, dedication, and the pursuit of knowledge. A quick learner and an effective communicator, he embodies the spirit of modern engineering – adaptive, analytical, and collaborative. His ability to learn and implement complex systems, along with his respect for students and colleagues, reflects not just technical competence but also emotional intelligence. As a lifelong learner and educator, he is poised to make enduring contributions in signal processing and beyond.

Publication

  • Title: BSPKTM-SIFE-WST: Bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification

  • Authors: V.S. Kardam, S. Taran, A. Pandey

  • Year: 2025

 

 

✅ Conclusion

Vikram Singh Kardam stands out as a promising scholar and educator in the field of signal processing. His journey reflects a balance of theoretical rigor, practical implementation, and a passion for continuous learning. With a future-oriented mindset, he is poised to make meaningful contributions to biometric systems, digital design, and the broader engineering community. As he advances through his doctoral research and professional engagements, Vikram’s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Haosen Yang | Energy data analytics | Best Researcher Award

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Dr. Haosen Yang | Energy data analytics | Best Researcher Award

Dr. Haosen Yang,  Hong Kong Polytechnic University, Hong Kong.

Haosen Yang is a dedicated researcher specializing in smart grids, renewable energy, and machine learning. Born in 1996 in Shandong, China, he has developed expertise in high-dimensional statistics, energy systems modeling, and fault detection. Currently working on enhancing the resilience of power grids, Haosen’s research focuses on integrating transportation systems and battery fault detection using advanced data-driven methods. He has published multiple journal articles and served as an editor for Power System Protection and Control, contributing significantly to the field. His interdisciplinary approach combines energy systems with cutting-edge machine learning techniques to improve energy forecasting and system operation.

Profile

Google Scholar

 

Early Academic Pursuits 🎓

Haosen Yang, born in 1996 in Shandong, China, has demonstrated a passion for research and learning from a young age. His academic journey began at Shanghai Jiao Tong University, where he honed his skills and knowledge in the fields of smart grids, renewable energy, and machine learning. His dedication to his studies allowed him to develop a deep understanding of high-dimensional statistics, power grid resilience, and fault detection in various energy systems. Throughout his academic years, Haosen exhibited a strong aptitude for interdisciplinary research, combining technical expertise in energy systems with cutting-edge statistical methods. His commitment to academic excellence set the foundation for his future contributions to the field of energy systems.

Professional Endeavors 💼

Currently, Haosen Yang is focused on high-dimensional statistics-based modeling for the resilience of power grids, specifically integrating transportation systems, battery fault detection, and related technologies. His professional work extends into the areas of data-driven energy system modeling and operation, where he employs innovative methods to analyze and improve energy forecasting techniques. As an active researcher, he continues to contribute to the development of smarter, more efficient energy systems. In addition to his technical work, Haosen has taken on an editorial role for the SCI journal Power System Protection and Control, where he actively contributes to the advancement of knowledge in the field.

Contributions and Research Focus 🔬

Haosen’s research interests revolve around the intersection of smart grids, renewable energy, and machine learning. His primary focus is on improving the resilience and efficiency of power grids through the application of high-dimensional statistics and machine learning techniques. His contributions span several areas, including fault detection in energy devices, data-driven modeling of energy systems, and predictive energy forecasting. By incorporating machine learning algorithms into energy systems, Haosen is helping to create smarter and more reliable grids that are better equipped to handle fluctuations in energy demand and supply. His interdisciplinary approach has allowed him to explore innovative solutions for complex problems in energy systems.

Accolades and Recognition 🏆

Haosen Yang has gained recognition for his exceptional contributions to energy systems and machine learning. With 11 journal papers and 1 conference paper published as the first author, his research has garnered significant attention in the academic community. His expertise has led to invitations to serve as an editor for the Power System Protection and Control journal, where he plays a vital role in shaping the direction of research in the field. His work has been praised for its practical applications and theoretical rigor, earning him respect among his peers and colleagues.

Impact and Influence 🌍

The impact of Haosen Yang’s work extends beyond the academic sphere, influencing real-world applications in energy systems. His focus on the resilience of power grids and fault detection systems has the potential to improve the reliability and sustainability of energy infrastructure, particularly in the face of growing demands for renewable energy. His research into smart grid technologies and machine learning is helping to shape the future of energy systems by making them more adaptive, efficient, and secure. Haosen’s contributions to the field of renewable energy and power grid resilience are making a lasting impact on both academic research and industry practices.

Legacy and Future Contributions 🚀

Haosen Yang’s work is poised to leave a lasting legacy in the field of energy systems and renewable energy. His interdisciplinary approach and innovative use of machine learning techniques are laying the groundwork for future advancements in smart grids, energy forecasting, and fault detection. Looking ahead, Haosen is committed to continuing his research and contributing to the development of sustainable and resilient energy systems. His dedication to improving the efficiency and reliability of energy infrastructure will undoubtedly lead to new breakthroughs that will have a positive impact on the global energy landscape for years to come.

Research Philosophy and Vision 🔭

Haosen Yang’s research philosophy is centered around using advanced statistical methods and machine learning techniques to solve complex challenges in energy systems. His vision for the future of energy is one where smart grids and renewable energy sources work seamlessly together, offering more resilient, efficient, and sustainable solutions. Haosen believes that interdisciplinary collaboration is key to unlocking new potential in energy systems and is dedicated to continuing his work in this area. Through his research, he aims to push the boundaries of what is possible, shaping the future of energy systems and ensuring their long-term sustainability.

Publication

  1. Title: Detection and classification of transmission line transient faults based on graph convolutional neural network
    Authors: H Tong, RC Qiu, D Zhang, H Yang, Q Ding, X Shi
    Year: 2021

 

  1. Title: Spatio-temporal correlation analysis of online monitoring data for anomaly detection and location in distribution networks
    Authors: X Shi, R Qiu, Z Ling, F Yang, H Yang, X He
    Year: 2019

 

  1. Title: A deep learning approach for fault type identification of transmission line
    Authors: X Shuwei, Q Caiming, Z Dongxia, HE Xing, CHU Lei, Y Haosen
    Year: 2019

 

  1. Title: Blind false data injection attacks against state estimation based on matrix reconstruction
    Authors: H Yang, X He, Z Wang, RC Qiu, Q Ai
    Year: 2022

 

  1. Title: Distributed event-triggered fixed-time fault-tolerant secondary control of islanded AC microgrid
    Authors: Z Wang, J Wang, M Ma, H Yang*, D Chen, L Wang, P Li
    Year: 2022

 

  1. Title: Unsupervised feature learning for online voltage stability evaluation and monitoring based on variational autoencoder
    Authors: H Yang, RC Qiu, X Shi, X He
    Year: 2020

 

  1. Title: Improving power system state estimation based on matrix-level cleaning
    Authors: H Yang, RC Qiu, L Chu, T Mi, X Shi, CM Liu
    Year: 2020

 

  1. Title: A Distributed Event-Triggered Fixed-Time Fault-Tolerant Secondary Control Framework of Islanded AC Microgrid Against Faults and Communication Constraints
    Authors: Z Wang, W Jie, M Ma, H Yang*, D Chen, L Xiong, P Li
    Year: 2022

 

Conclusion 🌟

Haosen Yang’s work stands at the forefront of the intersection between renewable energy, smart grid technology, and machine learning. His innovative contributions to power grid resilience and fault detection promise to shape the future of energy systems, making them more efficient, reliable, and adaptable. With a commitment to both academic excellence and practical applications, Haosen is set to leave a lasting legacy in the field. As he continues to explore and develop new solutions for complex energy challenges, his work will undoubtedly influence the development of more sustainable energy infrastructures globally.

Sunday Aboyeji | Feature selection | Best Researcher Award

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Mr. Sunday Aboyeji | Feature selection | Best Researcher Award

Mr. Sunday Aboyeji, Shenzhen Institutes of Advanced Technology, China.

Sunday Timothy Aboyeji is an accomplished researcher in computational science and biomedical signal processing. With an impressive academic foundation in physics and communication science, he has pursued groundbreaking research in patient-independent seizure classification using EEG data. His work combines advanced algorithms, deep learning, and explainable AI to enhance the accuracy and interpretability of diagnostic tools for epilepsy and other neurological disorders. His dedication to interdisciplinary collaboration and his contributions to high-impact publications reflect his influence in the field.

 

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Orcid

Scholar

📚 Early academic pursuits

Sunday Timothy Aboyeji began his academic journey with an unwavering passion for physical and computational sciences. Earning his Bachelor of Technology in Physics/Electronics from the Federal University of Technology, Minna, Nigeria, he graduated with first-class honors and a stellar GPA of 4.61/5.00. His undergraduate thesis, which explored the simulation of radiofrequency radiation effects on the brain, laid the foundation for his future endeavors in biomedical signal processing. He further honed his expertise by completing a Master’s degree in Communication Physics at the Federal University of Technology, Akure, Nigeria, achieving an outstanding GPA of 4.86/5.00. His master’s research on radioclimatic variables and refractivity modeling highlighted his ability to blend theoretical knowledge with practical applications.

🔬 Professional endeavors

Sunday is currently pursuing a Ph.D. in Pattern Recognition and Intelligent Systems at the University of Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, China. His doctoral dissertation focuses on developing patient-independent EEG-based seizure classification algorithms. Over the course of his research, he has designed cutting-edge solutions integrating signal processing, feature engineering, and deep learning. His projects include unsupervised seizure detection, feature fusion of Gramian angular fields, and domain adaptation frameworks, all aimed at revolutionizing epilepsy diagnosis. Beyond his academic achievements, he is an active member of IEEE and serves as a certified first-aider in Shenzhen, demonstrating his dedication to community service and professional growth.

🧠 Contributions and research focus

Sunday’s research has profoundly impacted computational science and biomedical signal processing. He specializes in the analysis of EEG, EMG, and other complex biomedical signals using advanced algorithms and explainable AI techniques. His groundbreaking work emphasizes the interpretability of deep learning models, enabling better diagnostic tools for epilepsy and other neurological disorders. By transforming biomedical signals into visual spectrograms and leveraging hybrid feature selection frameworks, he has created highly accurate and reliable classification models that support patient care and advance brain-computer interface technology.

🏆 Accolades and recognition

Sunday’s academic excellence has been recognized through multiple awards, including the prestigious Chinese Government Scholarship for his Ph.D. studies. His undergraduate achievements earned him commendations from his university dean. These accolades reflect his dedication to academic rigor and his ability to excel in highly competitive environments. He has also been invited to serve as a peer reviewer for leading journals, further solidifying his reputation as a rising star in his field.

🌍 Impact and influence

Through collaborative efforts with international scholars and researchers, Sunday has contributed to several high-impact publications in journals such as Computers in Biology and Medicine and the IEEE Journal of Biomedical and Health Informatics. His work on robust seizure detection and interpretable machine learning models has set a benchmark for researchers in biomedical signal processing. These contributions not only enhance patient diagnostics but also pave the way for more accessible healthcare technologies.

🌟 Legacy and future contributions

Sunday aspires to leave a legacy as a trailblazer in biomedical signal processing and computational sciences. His ongoing research on domain adaptation frameworks promises to address patient-specific challenges, making diagnostic systems more generalized and inclusive. He envisions leveraging his expertise to develop innovative solutions that enhance the quality of life for individuals with neurological disorders, ensuring his work continues to inspire and benefit the global scientific community.

💡 Dedication to innovation

Sunday’s career exemplifies a commitment to innovation, interdisciplinary collaboration, and societal impact. With his technical skills in Python, TensorFlow, and Pytorch, coupled with a deep understanding of signal processing and pattern recognition, he remains at the forefront of research in his field. His dedication to integrating advanced technology with real-world applications underscores his role as a visionary researcher and advocate for progress in medical diagnostics.

📚 Publications

  • Title: Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach
    Authors: Ijaz Ahmad, Zhenzhen Liu, Lin Li, Inam Ullah, Sunday Timothy Aboyeji, Xin Wang, Oluwarotimi Williams Samuel, Guanglin Li, Yuan Tao, Yan Chen, et al.
    Year: 2024

 

  • Title: Automatic Detection of Epileptic Seizure Based on One Dimensional Cascaded Convolutional Autoencoder with Adaptive Window-Thresholding
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Guoru Zhao, Yu Zhang, Guanglin Li, et al.
    Year: 2024

 

  • Title: Feature Fusion of Gramian Angular Field Deep Learning EEG-Based Epileptic Seizure Classification
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Yu Zhang, Guoru Zhao, Guanglin Li, et al.
    Year: 2024

 

  • Title: Modeling of Atmospheric Primary Radioclimatic Variables in Nigeria for Microwave Radio Propagation Applications
    Authors: Falodun, S.E., Ojo, J.S., Aboyeji, S.T.
    Year: 2021

 

Conclusion

Sunday’s journey exemplifies a relentless pursuit of knowledge and innovation. From his academic excellence in Nigeria to his impactful research at the Shenzhen Institute of Advanced Technology, he has made meaningful strides in advancing patient care through computational science. With a clear vision for the future, his contributions promise to continue shaping the landscape of biomedical signal processing and inspire further advancements in medical diagnostics.

 

Chen Wang | neural network application | Best Researcher Award

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Prof Dr.Chen Wang | neural network application | Best Researcher Award

Prof Dr Chen Wang School of Mining, Guizhou University China

Wang Chen is a distinguished professor at Guizhou University, specializing in mining engineering and resources and environment. He holds a PhD from the China University of Mining and Technology and has significant expertise in mining methods, rock mechanics, mining system engineering, and the kinematic behavior of rock layers in karst regions.

profile

scopus

📚 Recruitment Discipline Direction

Mining Engineering, Resources and Environment

🔬 Main Research Fields and Directions

Mining Methods,Rock Mechanics,Mining System Engineering,Roadway Support,Kinematic Mechanisms of Rock Layers in Karst Mountainous Areas.

💼 Key Research Projects (2018 – Present)

National Natural Science Foundation General Project (52174072)“Study on the Mechanisms of Rock Layer Movement under Repeated Mining in Karst Mountainous Areas,” 2022.01-2025.12, 580,000 RMB, Principal Investigator, ongoing. 💰National Natural Science Foundation Youth Science Fund Project (51904081)“Study on the Mechanisms of Instability Induced by Mining in Shallowly Buried Coal Layers in Karst Terrain,” 2020.01-2022.12, 240,000 RMB, Principal Investigator, ongoing. 🔍

✍️ Journal Articles:

Wang Chen et al. “An Expert System for Equipment Selection of Thin Coal Seam Mining.” (2019) .Wang Chen et al. “Optimal Selection of a Longwall Mining Method for a Thin Coal Seam Working Face.” (2016) .Wang Chen, Zhou Jie. “New Advances in Automatic Shearer Cutting Technology.” (2021) ⚙️

🥇 Achievements

Patents: 5 granted invention patents related to coal mining technology. Awards: Multiple research awards for contributions to mining technology. 🏆

📚 Publications

  1. Title: Study on strength prediction and strength change of Phosphogypsum-based composite cementitious backfill based on BP neural network
    Authors: Wu, M., Wang, C., Zuo, Y., Zhang, J., Luo, Y.
    Year: 2024
    Journal: Materials Today Communications
    Volume: 41
    Article Number: 110331

 

  1. Title: Correction: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 14

 

  1. Title: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 1

 

  1. Title: Evolution of Broken Coal’s Permeability Characteristics under Cyclic Loading–Unloading Conditions
    Authors: Luo, L., Zhang, L., Pan, J., Wang, C., Li, S.
    Year: 2024
    Journal: Natural Resources Research
    Volume: 33
    Issue: 5
    Pages: 2279–2297

 

  1. Title: Preparation and characterization of green lignin modified mineral cementitious firefighting materials based on uncalcined coal gangue and coal fly ash
    Authors: Dou, G., Wang, C., Zhong, X., Qin, B.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 435
    Article Number: 136799

 

  1. Title: Mining Technology Evaluation for Steep Coal Seams Based on a GA-BP Neural Network
    Authors: Li, X., Wang, C., Li, C., Luo, Y., Jiang, S.
    Year: 2024
    Journal: ACS Omega
    Volume: 9
    Issue: 23
    Pages: 25309–25321

 

  1. Title: Capturing rate- and temperature-dependent behavior of concrete using a thermodynamically consistent viscoplastic-damage model
    Authors: Tao, J., Yang, X.-G., Lei, Y., Wang, C.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 422
    Article Number: 135791

Conclusion

Wang Chen’s extensive research and numerous publications significantly contribute to the field of mining engineering. His focus on the complexities of karst geology and the development of intelligent mining technologies positions him as a leader in advancing mining safety and efficiency. His ongoing projects reflect a commitment to addressing contemporary challenges in the mining sector, particularly in relation to environmental sustainability and resource management.