Hussain Ahmad | Software Engineering | Best Researcher Award

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Mr. Hussain Ahmad | Software Engineering | Best Researcher Award

PhD Student at The University of Adelaide, Australia

🛡️ Hussain Ahmad is a cybersecurity and software engineering expert with a strong background in cloud computing, machine learning, robotics, and autonomous systems. Currently pursuing a PhD at the University of Adelaide (2021-2025), his research focuses on self-adaptive cybersecurity and software scalability. He has led 15+ R&DI projects, published 10 high-impact papers with 500+ citations, and secured AUD 200k+ in funding from Google, Amazon, and Cyber Security CRC. A Professional Electronics Engineer (Engineers Australia), he has supervised 12+ students and received the Outstanding International Student Award. His industry roles include Cyber Security Engineer, Chief Project Officer (Migrova), and Software Engineer (Kindship). 🌍🔐🤖

 

Publication Profile

Scopus

 

🎓 Education

Hussain Ahmad is currently pursuing a Doctor of Philosophy (PhD) in Cybersecurity and Software Engineering at The University of Adelaide, Australia (2021-2025). His research focuses on self-adaptive cybersecurity and software scalability, under the supervision of Claudia Szabo, Christoph Treude, and Markus Wagner. Prior to this, he earned a Bachelor of Science in Electronic Engineering (2013-2017) from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan, achieving a High Distinction. His bachelor’s degree is accredited by Engineers Australia, reflecting his strong foundation in electronic engineering and advanced computing systems. 📡🔐📊

 

💼 Work Experience

Hussain Ahmad is an R&D Scholar in Software Security & Scalability at The University of Adelaide (2021-2025), leading 15+ R&DI projects at the intersection of Cybersecurity, Software Engineering, and Machine Learning, with high-impact findings published in leading journals. As a Research Supervisor (2022-2025), he mentors students on industry-focused R&DI projects in collaboration with CSIRO’s Data61, Migrova, and Schlumberger. He also serves as Chief Project Officer at Migrova (2023-2024), securing AUD 100k for AI-driven cybersecurity solutions. Additionally, he developed an ML-enabled therapist recommendation engine as a Software Engineer at Kindship (2022-2023). 🔐💻🚀

 

🏆 Awards & Achievements

Hussain Ahmad has received numerous prestigious accolades for his contributions to R&DI, cybersecurity, and academic excellence. He was featured in a leading newspaper and honored with the Outstanding International Student Award at The University of Adelaide. He won the Exceptional HDR Representative Award and secured People’s Choice & Second Place in the 2024 Visualise Your Thesis Competition. His achievements include a Google Cloud Grant, AUD 100k Seed-Start grant, and three RTP Scholarships. Additionally, he is an accredited Professional Electronics Engineer, a recipient of six Dean’s Excellence Awards, and was awarded a GIKI Fully Funded Financial Assistance Award. 🏅🔬🚀

 

🔍 Research Focus

 

Hussain Ahmad’s research primarily focuses on cybersecurity, software engineering, and microservice architectures. His work on Microservice Vulnerability Analysis in IEEE Access (2024) highlights security risks, threat modeling, and empirical insights into software vulnerabilities. His expertise extends to self-adaptive cybersecurity, cloud computing, machine learning, and autonomous systems. With multiple high-impact publications and industry collaborations, he contributes to secure software scalability, cyber defense mechanisms, and AI-driven security solutions. His interdisciplinary approach bridges software security, electronic engineering, and automation, making him a key researcher in next-generation secure computing systems. 🔐💻📡

 

Publication Top Notes

1️⃣ A Review on C3I Systems’ Security: Vulnerabilities, Attacks, and Countermeasures – ACM Computing Surveys, 2023 🏆 
2️⃣ Smart HPA: A Resource-Efficient Horizontal Pod Auto-scaler for Microservice Architectures – ICSA, 2024 🏆 
3️⃣ Towards Resource-Efficient Reactive and Proactive Auto-scaling for Microservice Architectures – Journal of Systems and Software, 2024 🏆 
4️⃣ Microservice Vulnerability Analysis: A Literature Review with Empirical Insights – IEEE Access, 2024 🏆 
5️⃣ Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures – Cluster Computing, 2024 🏆
6️⃣ A Survey on Immersive Cyber Situational Awareness Systems – Submitted to IEEE Access, 2024 🏆 🛡️
7️⃣ ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large Language Models – 2024 🏆
8️⃣ Machine Learning Driven Smishing Detection Framework for Mobile Security – Submitted to Cluster Computing, 2024 🏆 
9️⃣ What Skills Do Cyber Security Professionals Need? – Submitted to Neurocomputing, 2025 🏆 
🔟 Exploring Sentiments of ChatGPT Early Adopters using Twitter Data – 2023 🏆

 

 

 

Debajyoti Dhar | Computer Science | Best Researcher Award

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Mr. Debajyoti Dhar | Computer Science | Best Researcher Award

Mr. Debajyoti Dhar, Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior, India

Debajyoti Dhar is an ambitious B.Tech student with a CGPA of 7.67/10, specializing in Computer Science. He has honed his skills through impactful internships, including as a Software Development Engineer at Defence Research and Development Establishment and a Full Stack Developer at Edilitics Private Limited. Debajyoti has contributed to projects like a Decentralized FPS Game with NFT Marketplace and a Ticket Management Platform, showcasing his expertise in blockchain, cloud systems, and machine learning. He has co-authored IEEE conference papers and a journal paper, demonstrating his strong research capabilities. 💻📊🔗

 

Publication Profile

Orcid

Education Background

Debajyoti Dhar is currently pursuing a Bachelor of Technology in Computer Science at the Indian Institute of Information Technology and Management Gwalior. He started his academic journey in December 2021 and is expected to graduate in July 2025. With a CGPA of 7.67/10.00, Debajyoti has demonstrated a strong academic performance, excelling in his coursework. His education has equipped him with a solid foundation in computer science, preparing him for advanced projects and research in areas such as software development, machine learning, and blockchain technology. 📚💻🚀

 

Professional Experience

Debajyoti Dhar has gained valuable experience through multiple internships, showcasing his expertise in software development. At Defence Research and Development Establishment (Dec 2022–Oct 2023), he developed a heavy gas detection model in Java and created a 2D plotter in Python for data visualization. During his time at Edilitics Private Limited (Apr–Jun 2023), he built a robust backend using FastAPI and enhanced development efficiency with CI/CD pipelines and Docker. At Mak Design Private Limited (May–Jul 2024), he created a real-time chat module with Django and ReactJS, ensuring end-to-end encryption. 💻🔧🚀

 

Achievements

Debajyoti Dhar has demonstrated exceptional skills through various achievements. As a freelance developer for Metarootz, he built a full-stack blockchain social media project using NodeJS, ExpressJS, and MongoDB for the backend, and NextJS with TailwindCSS for the frontend. He delivered a comprehensive 5-day training bootcamp on web app deployment automation with Docker, Kubernetes, and Github Actions for industry professionals. Debajyoti has also co-authored two IEEE conference papers on computer vision and deep learning and contributed to a machine learning paper in MDPI Sensors journal. Additionally, he solved 300+ DSA questions on GFG and LeetCode. 📈💻📚

 

Research Focus

Mr. Debajyoti Dhar has contributed significantly to machine learning and optimization techniques, particularly in the context of environmental prediction. His recent work, “Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale”, published in Sensors, demonstrates his expertise in applying advanced algorithms to solve agricultural and environmental challenges. The research focuses on soil organic carbon prediction using machine learning models, emphasizing scalability and efficiency. This aligns with his broader focus on data science, AI-driven predictions, and sustainable technologies to address complex real-world problems in various domains. 🌍🤖📊

 

Publication Top Notes  

  • Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale (2024) 📚

Yunge Zou | Computer Science | Best Scholar Award

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Dr. Yunge Zou | Computer Science | Best Scholar Award

Dr. Yunge Zou, Chongqing University, China

Dr. Yunge Zou is a Ph.D. scholar at Chongqing University, specializing in hybrid powertrain design and battery degradation in the Department of Automotive Engineering. He is a talent under the Chongqing Excellence Program and a Shapingba Elite Talent (2023–2025). Dr. Zou has led key projects, including the National Key R&D Program, focusing on high-efficiency powertrain technologies. His contributions include innovative methods like Hyper-Rapid Dynamic Programming, which optimizes multi-mode hybrid powertrains. With multiple patents and high-impact publications, he collaborates with leading automotive firms like Chang’an New Energy, advancing sustainable transportation. 🚗🔋📚

 

Publication Profile

Orcid

Google Scholar

Academic and Professional Background 🔋

Dr. Yunge Zou earned his B.E. degree in Automotive Engineering from Chongqing University, China, in 2018. Currently, he is pursuing his Ph.D. in hybrid powertrain design and optimization at the Vehicle Power System Lab, Department of Automotive Engineering, Chongqing University. Recognized for his exceptional talent, Dr. Zou is part of the prestigious Chongqing Excellence Program and was honored as a Shapingba Elite Talent for 2023–2025. His research focuses on hybrid powertrain topology design, battery degradation, energy management systems (EMS), and enhancing battery life, contributing to sustainable transportation innovation. 📚🔧🌱

 

Research and Innovations 🚗

Dr. Yunge Zou is leading several groundbreaking research projects in the field of hybrid powertrain design and optimization. His work includes the National Key Research and Development Program of China on high-efficiency range extender assembly and electric vehicle integration (2022-2024), with a funding of 2.5 million yuan. He is also working on optimizing hybrid electric vehicle design through the National Science Fund for Excellent Young Scholars (2023-2025). Additionally, he contributes to various projects focusing on hybrid vehicle dynamics, energy efficiency, and low-emission technologies, backed by substantial funding from multiple prestigious organizations. 🛠️⚡

 

🛠️ Research Focus

Dr. Yunge Zou’s research primarily focuses on hybrid powertrain design and optimization for electric and range-extended vehicles. His work includes the development of control strategies and topology design for hybrid systems, aiming to improve fuel economy, efficiency, and reduce emissions. Dr. Zou has made significant advancements in aging-aware optimization and mode-switching mechanisms for multi-mode hybrid vehicles. His contributions also extend to battery degradation, energy management, and the computational efficiency of fuel economy assessment using innovative algorithms like Hyper Rapid Dynamic Programming (HR-DP). His work is instrumental in the evolution of transportation electrification. 🚗⚡

 

Publication Top Notes

  • “Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory” – Energy 242, 122944 (Cited by 14, 2022) 🔋
  • “Aging-aware co-optimization of topology, parameter and control for multi-mode input-and output-split hybrid electric powertrains” – Journal of Power Sources 624, 235564 (Cited by 1, 2024) ⚙️
  • “Design of optimal control strategy for range extended electric vehicles considering additional noise, vibration and harshness constraints” – Energy 310, 133287 (Cited by 1, 2024) 🚗
  • “Computationally efficient assessment of fuel economy of multi-modes and multi-gears hybrid electric vehicles: A Hyper Rapid Dynamic Programming Approach” – Energy, 133811 (Cited by 0, 2024) 🔧

Suganya. R | Engineering | Best Researcher Award

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Dr. R. Suganya| Engineering | Best Researcher Award

Associate Professor,  Dr.  N.G.P Institute of Technology,  India.

Dr. R. Suganya, an Associate Professor at Dr. N.G.P Institute of Technology, has nearly 20 years of experience in engineering education. Her research focuses on mobile networks, IoT, and machine learning, resulting in 21 publications in Scopus-indexed journals. Notable achievements include the Academic Excellence Award from Novel Research Academy and multiple NPTEL accolades. As a mentor for the IITB-AICTE Mapathon, she has demonstrated her commitment to student engagement and collaborative learning. Dr. Suganya’s impressive contributions to academia and research make her a deserving candidate for the Research for Best Researcher Award.

Publication Profile

Google Scholar

Educational Background 

Dr. R. Suganya holds a commendable academic record, beginning with her Bachelor of Engineering (B.E.) in Electronics and Communication from V.L.B Janakiammal College of Engineering and Technology, where she graduated with First Class honors. She continued her education at Kumaraguru College of Technology, earning a Master of Engineering (M.E.) in Computer Science and Engineering with Distinction. Her commitment to academic excellence culminated in a Ph.D. from Anna University, Chennai, where she conducted advanced research, further solidifying her expertise in her field. This solid educational foundation underpins her effective teaching and innovative research contributions in engineering.

Professional Experiences

Dr. R. Suganya has a robust academic background, currently serving as an Associate Professor at Dr. N.G.P Institute of Technology since May 2023, following an extensive tenure of nearly 17 years at Sri Krishna College of Technology. Her teaching experience spans across various levels of engineering education, showcasing her dedication to nurturing the next generation of engineers. Additionally, her role as a lecturer at Nanjiah Lingammal Polytechnic College provided her with foundational teaching experience that further solidified her pedagogical skills.

Research Interests and Contributions

Dr. Suganya’s research interests are primarily in the domains of mobile networks, IoT, and machine learning, evidenced by her impressive publication record. She has authored 21 articles in Scopus-indexed journals, covering innovative topics such as channel allocation methods, secure voting systems, and cancer recognition frameworks. Her recent work involves the application of advanced algorithms and machine learning techniques, demonstrating her commitment to leveraging technology for real-world applications.

Awards and Achievements  

Dr. Suganya’s achievements have not gone unnoticed. She has received several accolades, including the Academic Excellence Award from Novel Research Academy and the NPTEL Discipline Star Award on two occasions. Her recognition as a mentor for the IITB-AICTE Mapathon further underscores her ability to guide students and foster collaborative learning environments. Such acknowledgments illustrate her impact within the academic community and her dedication to excellence in research and teaching.

Conclusion

In conclusion, Dr. R. Suganya’s extensive experience, notable research contributions, and numerous accolades make her an exceptional candidate for the Research for Best Researcher Award. Her commitment to academic excellence, coupled with her innovative research in technology, positions her as a leading figure in her field. Recognizing her contributions through this award would not only honor her achievements but also inspire others in the academic community to pursue excellence in research and education.

Publication Top Notes

  • Automated smart trolley with smart billing using Arduino 📝 (22) – 2016
  • Classification of DDoS attacks–A survey 📊 (13) – 2020
  • Simulation and Analysis of SVHM Technique for DCMLI under Transient Conditions with Non-Linear Loads 🔬 (8) – 2017
  • Blockchain based secure voting system using IoT 🔒 (6) – 2020
  • Reduction of THD in Single Phase AC to DC Boost Converter using PID controller ⚡ (6) – 2014
  • Fuzzy rough set inspired rate adaptation and resource allocation using Hidden Markov Model (FRSIRA-HMM) in mobile ad hoc networks 🧠 (5) – 2019
  • Automated Toll Plaza System Using RFID and GSM Technology 🚦 (5) – 2018
  • Tamper detection using watermarking scheme and k-mean clustering for bio-medical images 🖼️ (5) – 2016
  • Voltage control of AC-DC converter using sliding mode control ⚙️ (5) – 2013
  • Air Quality Monitoring System with Emergency Alerts Using IoT 🌍 (4) – 2021
  • Detect fake identities using improved Machine Learning Algorithm 🔍 (4) – 2021
  • Smart sentimental analysis of the impact of social media on COVID-19 📱 (4) – 2021
  • Pathogenesis of oral squamous cell carcinoma—an update 🦷 (4) – 2019
  • Identifying and Ranking Product Aspects based on Consumer reviews 🛍️ (4) – 2015
  • An Iterative Image Restoration Scheme for Degraded Face Images 🖥️ (4) – 2013
  • Product review analysis by web scraping using NLP 📝 (3) – 2022
  • An Erlang Factor integrated channel allocation method for boosting quality of services in mobile ad hoc networks 📶 (3) – 2018
  • Denial-of-Service Attack Detection Using Anomaly with Misuse Based Method 🚫 (3) – 2016
  • Development and Proposal System for the Formulation of Solar paint 🌞 (2) – 2021
  • Immunohistochemical expression of Bcl‑2 in oral squamous cell carcinoma 🩺 (2) – 2009

 

Sheng Ye | Computer Science | Best Researcher Award

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Sheng Ye | Computer Science | Best Researcher Award

Mr Sheng Ye, Tsinghua University, China

Mr. Sheng Ye 🎓 is a talented researcher in advanced computer science, specializing in deep learning and computer vision. Graduating in the top 15% from Tsinghua University with a GPA of 3.89/4.0, under the guidance of Prof. Liu Yongjin, he quickly established himself as a promising talent. His award-winning project on real-time video stylization 🏅 received the “Best Practice Award” from Kuaishou and Tsinghua University, and he has been honored with multiple scholarships, including the prestigious “Jiukun Scholarship.” Known for his impactful publications 📑 and contributions to academic conferences, Mr. Sheng Ye is well-positioned to excel in research.

Publication Profile

Scopus

Education Background 🎓

The candidate holds a strong academic record in advanced computer science, focusing on deep learning and computer vision. Graduating among the top 15% from Tsinghua University with a GPA of 3.89/4.0, they were supervised by Prof. Liu Yongjin. Recognized as an exemplary graduate, their academic achievements reflect a dedication to excellence. Early accolades include ranking within the top 10 of their grade and excelling in the national entrance exam with a score of 703. This foundation underlines their exceptional knowledge base and capability in scientific research.

Research Focus and Achievements 🔬

The candidate’s research spans innovative deep learning techniques and computer vision applications. A notable project on real-time video stylization was awarded the “Best Practice Award” by Kuaishou and Tsinghua University. Additional distinctions include winning first prize at the 16th Image and Graphics Technology and Applications Conference (IGTA). Their publication record is further strengthened by multiple scholarship awards and recognitions, including the prestigious “Tsinghua Friends – Jiukun Scholarship” in 2022–2023. This research-oriented focus positions the candidate as a strong contender for the Best Researcher Award.

Professional Experience and Contributions 💼

Through internships and student roles, the candidate has significantly impacted Tsinghua’s computing community. Leading publicity efforts in the computer science department, they manage the “JiXiaoYan” public account, curating content across various academic themes. Their professional involvement also extends to reviewing for prominent conferences and journals like CVPR, AAAI, NeurIPS, and ECCV. This experience illustrates their commitment to academic development and a thriving research community.

Key Publications 📑

  • 2024: DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation – ACM Transactions on Graphics, 43(4) 📊
  • 2024: O2-Recon: 3D Reconstruction of Occluded Objects – AAAI Conference on AI, 38(3) 🖼️
  • 2024: Online Exhibition Halls with Virtual Agents – Journal of Software, 35(3) 🌐
  • 2024: Fine-Grained Indoor Scene Reconstruction – IEEE Transactions on Visualization 📐
  • 2023: Virtual Digital Human for Customer Service – Computers and Graphics, 115 🎭
  • 2022: Audio-Driven Gesture Generation – Lecture Notes in Computer Science, 13665 🎶

Publication Top Notes

DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation and Head Pose Generation via Diffusion Models

O2-Recon: Completing 3D Reconstruction of Occluded Objects in the Scene with a Pre-trained 2D Diffusion Model

Indoor Scene Reconstruction with Fine-Grained Details Using Hybrid Representation and Normal Prior Enhancement

Generation of virtual digital human for customer service industry

Audio-Driven Stylized Gesture Generation with Flow-Based Model

Conclusion 🏆

The candidate’s robust educational background, innovative research, and active participation in academic communities distinguish them as a prime candidate for the Best Researcher Award. With numerous accolades, impactful publications, and a track record of community engagement, they are set to make meaningful contributions to the fields of deep learning and computer vision.

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.

Jingwei Zhou | Engineering | Best Researcher Award

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Jingwei Zhou | Engineering | Best Researcher Award

Dr Jingwei Zhou, Tsinghua University, China

Dr. Jingwei Zhou’s impressive academic background, research contributions, and professional experience, he appears to be a strong candidate for the Best Researcher Award. Here’s an overview of his qualifications that support this opinion:

Publication profile

Scopus

Education

  • Postdoctoral Researcher in Mechanical Engineering at Tsinghua University (2021-2024)
  • Ph.D. in Mechanics from Beijing University of Technology (2015-2020)
  • Master’s in Mechanical Engineering from Inner Mongolia University of Science & Technology (2009-2012)
  • Bachelor’s in Mechanical Engineering from Beijing Information Science and Technology University (2005-2009)

Professional Experience

  • Senior Researcher at Central Research Institute Goldwind Science & Technology Co., Ltd (2020-Present)
  • Visiting Ph.D. Student at Duke University (2018-2019)
  • Blade Design Engineer at Goldwind Science & Technology Co., Ltd (2012-2015)

Key Projects

  1. Adaptive Control: Developed a controller for a 6.25 MW wind turbine, significantly enhancing project value by $50 million.
  2. Aero-elasticity: Led the development of software for long slender blade design and validation.
  3. Floating Wind Turbine Control: Involved in modeling and experimental design for floating wind turbines.
  4. Stability Analysis: Worked on mitigating self-excited vibrations in wind turbines.

Honors and Awards

  • Second Prize for Scientific and Technological Progress from China Machinery Industry Association for his work on bend-twist adaptive control for flexible wind turbine blades, showcasing significant innovation and impact in renewable energy technology.

Publications

Dr. Zhou has multiple publications in respected journals related to wind turbine dynamics, such as:

  • Bend-twist adaptive control for flexible wind turbine blades in Mechanical Systems and Signal Processing.
  • Nonlinear vortex-induced vibration and its mitigation of wind turbines in parked conditions in Applied Mathematical Modelling.
  • Research on modeling and vortex-induced vibrations of semi-submersible floating offshore wind turbines.

Publication top notes

Bend-twist adaptive control for flexible wind turbine blades: Principles and experimental validation

Nonlinear vortex-induced vibration and its mitigation of wind turbines in parked conditions

Modeling and vortex-induced vibrations of semi-submersible floating offshore wind turbines

Dynamic deformation monitoring of cantilever beams using piezoelectric sensors: Theory and experiment

Nonlinear vortex-induced vibration of wind turbine towers: Theory and experimental validation

Aeroelastic deformation and load reduction of bending-torsion coupled wind turbine blades

Investigation on dynamics of rotating wind turbine blade using transferred differential transformation method

 

Conclusion

Dr. Zhou’s blend of advanced education, extensive research experience in mechanical engineering with a focus on wind energy, notable project outcomes, and recognition in the form of awards and publications make him an excellent candidate for the Best Researcher Award. His work not only advances the field of renewable energy but also demonstrates a strong commitment to innovation and practical application in real-world scenarios.

Guglielmo Vaccaro | Engineering | Best Researcher Award

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Mr. Guglielmo Vaccaro | Engineering | Best Researcher Award

Mr. Guglielmo Vaccaro, Università degli studi di Firenze, Italy

Guglielmo Vaccaro (born June 18, 1997, in Florence) is a dedicated researcher in mechanical and energy engineering. He holds a Bachelor’s in Mechanical Engineering and a Master’s in Energy Engineering from the University of Florence, both achieved with honors. Currently pursuing a Ph.D. in Industrial Engineering, his research focuses on eco-friendly refrigeration systems and CO2-based mixtures. He has presented at multiple international conferences and published in peer-reviewed journals. Guglielmo has also collaborated with CNAM in Paris on chiller systems. He is proficient in several software tools, including Matlab and Python. Fluent in Italian and English. 🇮🇹🔬💡

 

Publication profile

Google Scholar

Education

Bachelor’s Degree in Mechanical Engineering from the University of Florence, graduated with honors (110/110 cum laude). His thesis focused on optimizing a convergent-divergent nozzle, showcasing his attention to detail in technical design.

Master’s Degree in Energy Engineering (Machines Track) from the University of Florence, also graduated with honors. His thesis was centered on the design of an ejector for recovering lamination losses in a CO2-based plant, which highlights his commitment to sustainable technologies.

Ph.D. in Industrial Engineering, currently ongoing at the University of Florence, focusing on eco-friendly refrigeration systems, particularly on developing refrigeration plants using eco-compatible mixtures, which underlines his dedication to cutting-edge research in environmental sustainability.

Research

Presented research at prominent conferences, such as the International Congress of Refrigeration, covering topics like CO2-based mixtures for refrigeration and ice storage systems.

Published articles in renowned journals, including the International Journal of Refrigeration, where he assessed the thermodynamic performance of trans-critical refrigeration systems utilizing CO2 mixtures. His work extends into sustainable energy communities and low-TEWI refrigerants, indicating his focus on advancing energy-efficient and environmentally safe solutions.

Conclusion

Guglielmo Vaccaro’s combination of academic excellence, innovative research on eco-compatible refrigeration systems, and international collaborations makes him a strong contender for the Best Researcher Award. His focus on environmental sustainability through advanced refrigeration technologies aligns with the goals of pushing the boundaries in energy efficiency and renewable energy systems.

 

Publication Top Notes

  • Thermodynamic assessment of trans-critical refrigeration systems utilizing CO2-based mixtures | Cited by: 23 | Year: 2023 🔬❄️
  • Heat pumps and thermal energy storages centralised management in a Renewable Energy Community | Cited by: 8 | Year: 2023 ♻️🌍
  • A proposal for a non-flammable, fluorine-free, CO2-based mixture as a low TEWI refrigerant | Cited by: 5 | Year: 2024 💧🔋
  • Working Fluid Selection for High-Temperature Heat Pumps: A Comprehensive Evaluation | Cited by: 3 | Year: 2024 🔥🔧
  • Optimal sizing of a distributed energy system with thermal load electrification | Cited by: 2 | Year: 2020 ⚡📏
  • Propylene and DME solubility in PAG oil: Experimental investigations and simplified modeling | Cited by: 1 | Year: 2024 📊🧪
  • Experimental investigations and modeling of Propylene and DME solubility in PAG oil | Cited by: 1 | Year: 2023 🔍📈
  • Numerical assessment of CO2-based mixtures for refrigeration systems: focus on the evaporation process  Year: 2023 🌬️💨
  • Development of a code for the evaluation of air sanitation efficiency of UV-C linear lamps in ventilation systems Year: 2022 💡🌬️
  • Thermodynamic analysis of a steam ejector chiller with ice storage  Year: 2022 ❄️🧊

Dinesh Sharma | Computer Science | Best Researcher Award

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Dr. Dinesh Sharma | Computer Science | Best Researcher Award

Dr. Dinesh Sharma, Manipal University Jaipur, India

Dr. Dinesh Sharma holds a Ph.D. in Computer Science and Engineering from Uttarakhand and an M.E. from C-DAC, Pune. With over 14 years of experience in technical and engineering education, he currently serves as an Associate Professor at Manipal University Jaipur. He has published multiple patents, including innovations in animal wellbeing and waste management. Dr. Sharma is a technical committee member for various international conferences and has acted as a guest editor for respected journals. He is also an AICTE High-Performance Computing Master Trainer, dedicated to advancing technology in education. 🌍✨

 

Publication profile

Scopus

Qualification

Dr. Dinesh Sharma is an accomplished academic in the field of Computer Science and Engineering, holding a Ph.D. from Uttarakhand Technical University. He also earned a Master’s degree in CSE from C-DAC, Pune, and a Bachelor’s degree from R.G.P.V., Bhopal. With over 14 years of experience in technical education, he currently serves as an Associate Professor at Manipal University Jaipur. Dr. Sharma has a strong research background, with multiple patents and publications focusing on innovative technologies. His contributions to academia include serving as a reviewer for numerous journals and as a technical committee member for various international conferences. 🌍✨

 

Professional Achievements 🏆

Dr. Dinesh Sharma has made significant contributions to academia and industry, serving as a Guest Editor for a special issue on “Industrial System Pioneering in Industry 4.0” in the Journal of New Materials and Electrochemical Systems. He is an AICTE High-Performance Computing Master Trainer and has been invited as a session chair at numerous international conferences, including IEEE CSNT and CICN. Dr. Sharma coordinated a five-day Faculty Development Program on IoT at Amity University and served as an Associate Editor for Pragyan Journal of Information Technology. Additionally, he reviews for various SCI, IEEE, and Scopus-indexed journals. 🌐✨

 

Awards & Guided Projects 🏅

Dr. Dinesh Sharma has successfully mentored CSE students who achieved remarkable milestones, including securing international funding of $1,000 and $250 from Latrobe University Technology Grand Challenge, where one project also won the 1st runner-up prize. Under his guidance, Mr. Ashish Kumar Mishra developed a “Smart Attendance System,” earning 1st position in a national challenge organized by Amazon and receiving ₹35,000. Additionally, Ms. Priyanshi Gupta won ₹30,000 and the runner-up prize at the “Gwalior Smart City Tech Challenge 2020.” Dr. Sharma also led the development of the web conferencing platform “Bharat Live” for online activities. 🌍🎉

 

Professional Experience 📚

Dr. Dinesh Sharma brings over 14 years of expertise in technical and engineering education, specializing in software development with 8 years of freelance experience in C#, ASP.Net, PHP, Java, and Android app development. Currently, he serves as an Associate Professor in Data Science and Engineering at Manipal University Jaipur since August 2023, where he is also a software developer, KPI coordinator, and E-cell coordinator. Previously, he worked as an Assistant Professor at Amity University Madhya Pradesh and IMS Unison University, contributing significantly as a software developer and coordinator for various academic initiatives. His journey began as the Head of the Computer Science & Engineering Department at Amardeep College of Engineering and Management. 🎓💻

 

Conclusion

Dr. Dinesh Sharma’s qualifications, innovative research contributions, professional achievements, and mentorship make him an exemplary candidate for the Best Researcher Award. His commitment to advancing technology and educating future generations in the field of computer science is commendable, and he is well-deserving of this recognition.

 

Publication Top Notes

  • Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network – Cited by: 0 (2024) 🐾
  • Automatic detection and classification of plant leaf diseases using image processing: A survey – Cited by: 1 (2023) 🌱
  • Enhancing Feature Extraction in Plant Image Analysis through a Multilayer Hybrid DCNN – Cited by: 0 (2023) 🖼️
  • Comparative Analysis of Skin Cancer Detection Using Classification Algorithms – Cited by: 1 (2023) 🎗️
  • Face Mask Detection Analysis for Covid19 Using CNN and Deep Learning – Cited by: 3 (2022) 😷
  • Energy Efficient Multitier Random DEC Routing Protocols for WSN: In Agricultural – Cited by: 18 (2021) 🌾
  • A new energy efficient multitier deterministic energy-efficient clustering routing protocol for wireless sensor networks – Cited by: 34 (2020) 💡
  • Comparative energy evaluation of lEACH protocol for monitoring soil parameter in wireless sensors network – Cited by: 7 (2018) 🌍
  • Enhance PeGASIS algorithm for increasing the life time of wireless sensor network – Cited by: 6 (2018) ⚡

Noor .A. Rashed | Computer Science Award | Women Researcher Award

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Dr . Noor .A. Rashed | Computer Science Award | Women Researcher Award

Dr. Noor Rashid, Iraq

Dr. Noor Rashid is a Ph.D. candidate at the University of Technology, Baghdad, specializing in Computer Science. She earned her master’s degree from the University of al-Anbar in 2018. Her research covers areas such as Artificial Intelligence, secure data systems, machine learning, data mining, image processing, and project management automation. Her current focus is on optimization algorithms, particularly multi-objective optimization (2022-2023). Dr. Rashid has contributed significantly to the field, including her recent publication on evolutionary and swarm-based algorithms. She continues to advance AI and optimization research in her academic journey.

 

Publication profile

Google Scholar

Orcid

Employment

Dr. Noor Rashid is currently employed at the University of Technology, Baghdad, Iraq, in the Department of Computer Science. As a dedicated researcher and educator, she contributes to the university’s mission by advancing studies in Artificial Intelligence, secure data systems, and optimization algorithms. Her role involves teaching and mentoring students while conducting innovative research in multi-objective optimization and machine learning. Dr. Rashid’s work continues to impact both the academic community and the broader technological landscape through her involvement in cutting-edge computer science projects.

 

Education and Qualifications 🎓📜

Dr. Noor Rashid is currently pursuing her Ph.D. in Computer Science at the University of Technology, Baghdad, Iraq, from November 2021 to November 2024. Her doctoral research focuses on advanced areas such as optimization algorithms and Artificial Intelligence, contributing to cutting-edge technological advancements. Prior to this, Dr. Rashid earned her master’s degree from the College of Computer Science and Information Technology at the University of al-Anbar in 2018. Her academic background equips her with a strong foundation in secure data, machine learning, and project management systems, preparing her for continued success in the field.

 

Research Focus 🎯🔬

Dr. Noor Rashid’s research primarily focuses on Artificial Intelligence (AI), particularly in machine learning, optimization algorithms, and data mining. Her studies delve into complex areas such as multi-objective optimization and evolutionary algorithms, aiming to solve real-world computational problems. Additionally, Dr. Rashid has worked extensively on medical image processing, applying AI techniques like ANN and SVM to detect and classify diseases like diabetic retinopathy. Her research bridges the gap between AI and healthcare, making significant contributions to secure data, networks, and advanced algorithmic developments. 🚀🧠

 

Publication Top Notes

  • Diagnosis retinopathy disease using GLCM and ANN – N. Rashed, S. Ali, A. Dawood – J. Theor. Appl. Inf. Technol 96, 6028-6040, 2018 (Cited by: 4) 📖
  • Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems – N.A. Rashed, Y.H. Ali, T.A. Rashid, A. Salih – arXiv preprint, 2024 (Cited by: 2) 🌐
  • Advancements in Optimization: Critical Analysis of Evolutionary, Swarm, and Behavior-Based Algorithms –  Rashed, Y.H. Ali, T.A. Rashid – Algorithms 17(9), 416, 2024 📑
  • ANN and SVM to recognize Texture features for spontaneous Detection and Rating of Diabetic Retinopathy –  Rashed (Upcoming) 🔍