Aleeza Adeel | Computer Science | Research Excellence Award

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Mrs. Aleeza Adeel | Computer Science | Research Excellence Award

The University of Waikato | New Zealand

Mrs. Aleeza Adeel is a Ph.D. student at the School of Computing and Mathematical Sciences, University of Waikato, New Zealand, specializing in digital twin frameworks, sustainable energy systems, and user-centered computing solutions. Her research focuses on developing interoperable and scalable digital twin technologies to optimize energy system management, enhance operational efficiency, and support sustainable resource utilization. She has contributed to peer-reviewed publications, including a recent article in Energies on an interoperable user-centered digital twin framework, demonstrating her commitment to integrating advanced computational models with real-world energy systems. Aleeza collaborates with interdisciplinary researchers, including experts in energy management and computational modeling, to ensure her work addresses both technical rigor and societal relevance. Her research contributes to sustainable energy transitions by providing data-driven, user-centric solutions that improve system performance, reduce environmental impact, and support informed decision-making in complex energy infrastructures.

Profile: View ORCID Profile 

Featured Publication


An Interoperable User‑Centred Digital Twin Framework for Sustainable Energy System Management

– Adeel, A., Apperley, M., & Walmsley, T. G., Energies, 2026, 19(2), Article 333

Miroslaw Kozielski | Computer Science | Best Researcher Award

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Mr. Miroslaw Kozielski | Computer Science | Best Researcher Award

Kazimierz Wielki University | Poland

Mr. Mirosław Kozielski is a researcher at Kazimierz Wielki University in Bydgoszcz, Poland, specializing in computer science, with a strong focus on natural language processing (NLP), industrial informatics, and Industry 4.0/5.0 technologies. His research addresses the use of intelligent language-based systems for automated industrial documentation, knowledge representation, and digital transformation in modern manufacturing environments. He has authored 7 peer-reviewed publications, which have accumulated 35 citations, and holds an h-index of 3, reflecting a focused and emerging academic impact. Dr. Kozielski collaborates with interdisciplinary teams, contributing to the integration of artificial intelligence with industrial and organizational processes. His work supports the development of efficient, human-centric, and sustainable industrial systems, with societal impact through improved documentation quality, enhanced knowledge accessibility, and the practical adoption of advanced AI-driven solutions in contemporary industrial ecosystems.

Citation Metrics (Scopus)

35
25
15
5
0

Citations

35

Documents

7

h-index

3

Citations

Documents

h-index

View Scopus Profile
 View ORCID Profile

Featured Publications

Zeba Shamsi | Computer Science | Research Excellence Award

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Assoc. Prof. Dr. Zeba Shamsi | Computer Science | Research Excellence Award

Associate Professor | Lendi Institute of Engineering and Technology | India

Dr. Zeba Shamsi is a researcher at the National Institute of Technology Silchar, India, with expertise in computer science and engineering, particularly in cybersecurity, machine learning, and intelligent data-driven systems. Her research focuses on advanced threat detection, deep learning architectures, and generative models for secure and resilient computing. She has authored 7 peer-reviewed research publications, receiving 104 citations, with an h-index of 5, reflecting steady academic impact. Her recent work on zero-day attack detection using dynamic-weighted contractive autoencoders and GAN-based evaluation highlights her contribution to next-generation cyber defense mechanisms. Dr. Shamsi actively collaborates with national and international researchers, fostering interdisciplinary research and knowledge exchange. Her work contributes to improving digital security, protecting critical infrastructure, and supporting safer adoption of emerging technologies, demonstrating meaningful societal and technological impact at both academic and applied levels.

Citation Metrics (Scopus)

104
80
60
40
0

Citations

104

Documents

7

h-index

5

Citations

Documents

h-index

View Google Scholar Profile
 View Scopus Profile
 View ORCID Profile

Featured Publications


An Encryption Scheme for Securing Multiple Medical Images


– Journal of Information Security and Applications, 2019

Visually Meaningful Cipher Data Concealment


– Digital Signal Processing, 2024

Visually Meaningful Cipher Data Concealment


– Digital Signal Processing, 2024

Securing Encrypted Image Information in Audio Data


– Multimedia Tools and Applications, 2023

Takeshi Nikawa | Biochemistry | Research Excellence Award

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Prof. Dr. Takeshi Nikawa | Biochemistry | Research Excellence Award

Tokushima University Graduate School | Japan

Prof. Dr. Takeshi Nikawa is a distinguished researcher at Tokushima University, Japan, with expertise in skeletal muscle physiology, molecular biology, and nutritional interventions. His research explores the mechanisms underlying muscle atrophy, mitochondrial function, and gene regulation during myogenesis, aiming to understand how these processes impact aging, metabolism, and overall health. Nikawa’s work integrates experimental studies with translational approaches to develop strategies for maintaining muscle mass and function, particularly in aging populations or individuals at risk of muscle degeneration. He actively collaborates with international scientists across multiple disciplines, fostering knowledge exchange and advancing global research initiatives. Through his publications and applied studies, Nikawa contributes to both fundamental scientific understanding and practical interventions, supporting the development of therapeutic, nutritional, and lifestyle strategies that enhance quality of life and address key societal challenges related to health and aging.

Citation Metrics (Scopus)

4787
3500

2500
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0

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4,787

Documents

157

h-index

39

Citations

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View Scopus Profile

Featured Publications

Jian Liu | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Jian Liu | Engineering | Best Researcher Award

Deputy Director of the Department at Tiangong University, China

Assoc. Prof. Dr. Jian Liu is a senior experimentalist and Master’s Supervisor at Tiangong University, specializing in ultra-fine fiber preparation, textile machinery design, and automation. With a PhD in Mechanical Design and Theory, he has led and contributed to six major research projects, including those funded by the National Natural Science Foundation of China and the National Development and Reform Commission. Dr. Liu has played a key role in 13 horizontal projects and four new product developments for enterprises. His innovative contributions are evident in his 11 national invention patents, multiple utility model and appearance patents, and software copyrights. As a prolific researcher, he has published over 20 scientific papers as the first author. Beyond research, he actively mentors students and advances engineering education. With a strong track record in applied research and industry collaboration, Dr. Liu continues to make significant contributions to mechanical engineering and automation.

Professional Profile 

Education

Assoc. Prof. Dr. Jian Liu has a strong academic background in mechanical engineering. He earned his Bachelor of Engineering degree in Mechanical Design, Manufacturing, and Automation from the School of Mechanical Engineering at Shandong University of Technology in 2007. Continuing his education at the same institution, he obtained a Master’s degree in Mechanical and Electronic Engineering in 2010. Driven by a passion for research and innovation, he pursued a PhD in Mechanical Design and Theory at Tiangong University, completing his doctoral studies in 2019. His academic journey reflects a continuous commitment to advancing his expertise in mechanical engineering, particularly in design, automation, and manufacturing technologies. Through his higher education and research, Dr. Liu has developed a strong foundation that supports his contributions to both academia and industry, playing a crucial role in advancing new technologies and mentoring the next generation of engineers.

Professional Experience

Assoc. Prof. Dr. Jian Liu has extensive professional experience in mechanical engineering education and research. He began his career as a teaching assistant at the Engineering Teaching Internship Training Center of Tiangong University in 2010. In 2013, he was promoted to lecturer, further strengthening his role in academia. After earning his PhD in 2019, he continued his career as an experimentalist at the same institution, where he contributed to hands-on engineering education and research. In 2020, he was appointed as a senior experimentalist, overseeing advanced experimental research and training. With over a decade of experience, Dr. Liu has been actively involved in mentoring students, leading research projects, and contributing to industrial innovation. His expertise in ultra-fine fiber preparation, textile machinery design, and automation has made him a key figure in bridging academic research with real-world applications, enhancing both educational and technological advancements in his field.

Research Interest

Assoc. Prof. Dr. Jian Liu’s research interests lie in the fields of ultra-fine fiber preparation technology, textile machinery design, and automation. His work focuses on developing innovative techniques for producing high-performance fibers with enhanced properties for various industrial applications. He is also deeply involved in the design and optimization of advanced textile machinery, aiming to improve manufacturing efficiency and precision. Additionally, Dr. Liu explores automation technologies to enhance production processes, integrating smart control systems and intelligent manufacturing techniques. His research contributions extend beyond theoretical studies, as he actively collaborates with industry partners to develop cutting-edge solutions for modern textile and mechanical engineering challenges. With numerous patents and publications, Dr. Liu continues to push the boundaries of mechanical design, automation, and material science, striving to bridge the gap between research and practical application in the evolving landscape of engineering and manufacturing.

Award and Honor

You haven’t mentioned specific awards and honors in your resume. However, based on your research contributions, patents, and publications, you may have received recognitions that can strengthen your profile. If you have received awards for research excellence, innovation, patents, or teaching achievements, highlighting them would enhance your candidacy for honors like the Best Researcher Award.If you provide details on any grants, fellowships, best paper awards, innovation prizes, or academic honors, I can craft a precise and compelling paragraph

Research Skill

Assoc. Prof. Dr. Jian Liu possesses strong research skills in mechanical engineering, specializing in ultra-fine fiber preparation, textile machinery design, and automation. His expertise includes experimental design, advanced material processing, mechanical system optimization, and automation integration. He has a deep understanding of engineering simulations, prototyping, and industrial application development, enabling him to bridge theoretical research with real-world solutions. Dr. Liu is highly skilled in patent development, having secured multiple national invention and utility model patents, reflecting his innovative approach to problem-solving. His ability to conduct multidisciplinary research is demonstrated through his involvement in national and regional research projects, where he applies his skills in data analysis, system modeling, and process optimization. Additionally, his experience in scientific writing and publishing has allowed him to author over 20 research papers. With a strong foundation in mechanical design and automation, Dr. Liu continues to drive innovation in engineering research.

Conclusion

Your strong research background, patent portfolio, and industry collaborations make you a competitive candidate for the Best Researcher Award. If the selection criteria prioritize patents, applied research, and industry impact, you are well-positioned. However, strengthening your international presence and independent funding leadership could further elevate your profile.

Publications Top Noted

  • Author(s): P. Wang, B. Wang, L. Zhao, L. Nie, J. Liu
  • Year: 2025
  • Title: Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone
  • Journal: Journal of Electronic Materials
  • Citation Format (APA):
    Wang, P., Wang, B., Zhao, L., Nie, L., & Liu, J. (2025). Effects of crystal growth rate on convection and heat transfer during GaInSb THM and VBM crystal growths considering the mushy zone. Journal of Electronic Materials.
  • Citation Format (IEEE):
    P. Wang, B. Wang, L. Zhao, L. Nie, and J. Liu, “Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone,” J. Electron. Mater., 2025.
  • Citation Format (Harvard):
    Wang, P., Wang, B., Zhao, L., Nie, L. and Liu, J. (2025) ‘Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone’, Journal of Electronic Materials.

 

Anuj Kumar | Engineering | Best Researcher Award

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Mr. Anuj Kumar | Engineering | Best Researcher Award

Assistant Professor at Management Education & Research Institute, Janakpuri, India

Anuj Kumar is an accomplished academic and researcher in Computer Science & Engineering, currently pursuing a Ph.D. in Image Processing at AKTU, Lucknow. With over a decade of teaching experience at institutions like Guru Gobind Singh Indraprastha University and IIMT College of Engineering, he has significantly contributed to education and research. His expertise spans artificial intelligence, computer graphics, and data structures, complemented by proficiency in programming languages such as Python, C++, and MATLAB. He has published research papers in Scopus-indexed journals, IEEE Explorer, and Elsevier, along with a book chapter on distributed artificial intelligence. Recognized for his contributions, he was awarded at the Smart India Hackathon 2018 and qualified GATE 2012 with an 85.04 percentile. Anuj is actively involved in academic leadership, faculty development, and university assessments. With a commitment to innovation and interdisciplinary research, he aspires to advance computational methodologies and industrial applications in artificial intelligence and image processing.

Professional Profile 

Education

Anuj Kumar has a strong academic background in Computer Science & Engineering. He is currently pursuing a Ph.D. in Image Processing from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, Uttar Pradesh, demonstrating his commitment to advanced research. He earned his M.Tech in Computer Science & Engineering from Guru Gobind Singh Indraprastha University, Delhi, in 2014, securing a first division. His undergraduate studies include a B.Tech in Computer Science & Engineering from the Institution of Electronics & Telecommunication Engineers (IETE), Delhi, in 2011, also with first-division honors. Additionally, he holds a Three-Year Diploma in Computer Science & Engineering from IETE, Delhi (2006). His early education was completed under the U.P. Board, where he finished 10th grade (2000) and 12th grade (2003) in the second division. His educational journey, enriched with technical certifications like MCAD (Microsoft Certified Application Developer) in 2006, has laid a strong foundation for his expertise in computing and research.

Professional Experience

Anuj Kumar has extensive academic experience as an Assistant Professor in Computer Science & Engineering, with a teaching career spanning over a decade across prestigious institutions. Since July 2023, he has been serving at MERI College of Engineering and Technology, Haryana. Prior to this, he worked at IIMT College of Engineering, Greater Noida (2022–2023) and Greater Noida Institute of Technology, GGSIPU (2018–2022), where he contributed to curriculum development and research initiatives. He also held academic positions at USIC&T, Guru Gobind Singh Indraprastha University (2017–2018) and Ram-Eesh Institute of Engineering & Technology (2017). Earlier in his career, he served at Baba Saheb Ambedkar Institute of Technology & Management (2014–2016) and The Institution of Electronics & Telecommunication Engineers, Delhi (2011–2012). His vast experience includes mentoring students, conducting faculty development programs, and leading academic audits, showcasing his commitment to education, research, and institutional development.

Research Interest

Anuj Kumar’s research interests lie at the intersection of computer vision, image processing, artificial intelligence, and computational methods. Currently pursuing a Ph.D. in Image Processing, he focuses on developing advanced techniques for image enhancement, noise removal, and forgery detection using deep learning algorithms. His expertise extends to computer graphics, formal language automata, database management systems (DBMS), data structures, and discrete mathematics, which serve as the foundation for his research innovations. He has actively contributed to AI-driven industrial systems, biodiversity assessment using hyperspectral imaging, and disruptive innovations in tech-business analytics. His work has been published in Scopus-indexed journals, IEEE conference proceedings, and reputed international journals, reflecting the impact of his research. Additionally, he explores the applications of distributed artificial intelligence (DAI) for document retrieval, emphasizing intelligent data processing techniques. His dedication to cutting-edge research strengthens his role as a mentor and academician in the field of computer science and engineering.

Award and Honor

Anuj Kumar has been recognized for his academic excellence and research contributions through various awards and honors. He was awarded in the Smart India Hackathon 2018, a prestigious national-level competition promoting innovation and problem-solving skills. Demonstrating strong technical acumen, he qualified GATE 2012 with an impressive 85.04 percentile and a score of 302, showcasing his expertise in computer science and engineering. His achievements extend beyond academics, as he was the runner-up in the 100m race at IETE, New Delhi, in 2005, highlighting his diverse talents. Additionally, he has played a significant role in academia as a convener of the Joint Assessment Committee (JAC) for academic audits, deputy center superintendent for examinations, and university representative in various assessment programs. His dedication to research and education is further reflected in his memberships on editorial boards and professional organizations, solidifying his reputation as a distinguished academic and researcher.

Research Skill

Anuj Kumar possesses a strong research skillset that spans multiple domains within computer science and engineering, particularly in image processing, artificial intelligence, and computational methods. His expertise in deep learning, fuzzy techniques, and hyperspectral imaging enables him to develop innovative solutions for image enhancement, noise removal, and forgery detection. He is proficient in Python, MATLAB, C++, and various database management systems (DBMS), which support his research in data analysis, automation, and intelligent computing. His ability to critically analyze complex problems, design experiments, and implement advanced algorithms has led to multiple Scopus-indexed publications, IEEE conference presentations, and book chapters. Additionally, his role in academic audits, faculty development programs, and technical training workshops demonstrates his leadership in research and education. His strong analytical thinking, problem-solving capabilities, and hands-on approach to emerging technologies make him a highly skilled researcher in the field of computer vision and artificial intelligence.

Conclusion

Anuj Kumar has a strong academic foundation, technical expertise, and a growing research portfolio in computer science and engineering. His contributions to image processing, artificial intelligence, and industrial automation position him as a promising candidate for the Best Researcher Award. However, enhancing high-impact publications, research collaborations, and funding contributions would further strengthen his profile for this recognition.

Publications Top Noted

  • P., Jaidka, Preeti, P., Upadhyay, Prashant, A., Kumar, Aman, A.S., Kumar, Anuj Shiva, S.P., Yadav, Satya Prakash (2024). Transforming Coconut Farming with Deep Learning Disease Detection. Evergreen. Citations: 0

  • D., Sharma, Deepak, A.S., Kumar, Anuj Shiva, N., Tyagi, Nitin, S.S., Chavan, Sunil S., S.M.P., Gangadharan, Syam Machinathu Parambil (2024). Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT. Measurement: Sensors. Citations: 3

  • S., Singh, Sandeep, B.K., Singh, B. K., A.S., Kumar, Anuj Shiva (2024). Multi-organ segmentation of organ-at-risk (OAR’s) of head and neck site using ensemble learning technique. Radiography. Citations: 3

  • R., Naz, Rahat, A.S., Kumar, Anuj Shiva (2024). Surveying Quantum-Proof Blockchain Security: The Era of Exotic Signatures. Conference Paper. Citations: 1

 

Arash Yazdanpanah Goharrizi | Engineering | Best Innovation Award

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Prof. Arash Yazdanpanah Goharrizi | Engineering | Best Innovation Award

Shahid Beheshti University, Iran

Dr. Arash Yazdanpanah Goharrizi is a distinguished professor in electrical engineering at Shahid Beheshti University, Tehran, Iran. His research focuses on nanotechnology, semiconductor devices, and electronic transport properties, with contributions to optimizing transistor performance, nanoribbon-based sensors, and first-principles calculations of novel materials. He has published extensively in high-impact journals, collaborating with international researchers to advance the field of microelectronics and nanostructures. In addition to research, Dr. Goharrizi actively reviews scientific manuscripts and contributes to academic peer-review processes.

Professional Profile

Education

Dr. Arash Yazdanpanah Goharrizi earned his academic qualifications from Shahid Beheshti University, Tehran, Iran. He initially served as an assistant professor in electrical engineering at the same institution, where he developed expertise in semiconductor physics, nanomaterials, and device modeling. His academic training provided him with a strong foundation in theoretical and applied aspects of electronic devices, paving the way for his contributions to advanced semiconductor research.

Professional Experience

Dr. Goharrizi currently serves as a professor at Shahid Beheshti University, where he leads research in electrical engineering, with a focus on micro- and nanostructures. Over the years, he has conducted groundbreaking studies on electronic and transport properties of advanced materials like phosphorene, antimonene, and germanene. His work has led to numerous publications in esteemed journals such as ACS Applied Electronic Materials, IEEE Transactions on Electron Devices, and Physica E. Beyond research, he contributes to academia through peer reviewing and mentoring graduate students in semiconductor device physics and nanoelectronics.

Research Interests

Dr. Arash Yazdanpanah Goharrizi’s research interests lie in the fields of nanoelectronics, semiconductor devices, and computational materials science. He focuses on the electronic, optical, and transport properties of low-dimensional materials such as phosphorene, antimonene, graphene, and germanene nanoribbons, utilizing first-principles calculations and device modeling to optimize their performance. His studies contribute to advancements in transistor design, Bragg grating-based sensors, and tunneling field-effect transistors (TFETs). Additionally, he explores strain engineering and doping control to enhance device efficiency and scalability. His interdisciplinary research integrates physics, electrical engineering, and material science, aiming to develop next-generation electronic and optoelectronic devices for high-performance computing and sensing applications.

Awards and Honors

Dr. Goharrizi has been recognized for his contributions to semiconductor research and nanoelectronics through various academic and professional honors. His high-impact publications in prestigious journals and collaborations with international researchers reflect his standing in the scientific community. As a peer reviewer for leading journals, he has contributed to the advancement of materials science and electrical engineering. He has also received recognition for his mentorship and guidance of graduate students in advanced semiconductor device research. His work on nanostructured materials and electronic transport properties continues to earn him accolades within the academic and research communities, further establishing his reputation as a leading expert in the field.

Publications Top Noted

  1. Modeling of lightly doped drain and source graphene nanoribbon field effect transistors
    • Authors: M Saremi, M Saremi, H Niazi, AY Goharrizi
    • Journal: Superlattices and Microstructures
    • Year: 2013
    • Citations: 94
  2. Armchair graphene nanoribbon resonant tunneling diodes using antidote and BN doping
    • Authors: AY Goharrizi, M Zoghi, M Saremi
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2016
    • Citations: 93
  3. Band gap tuning of armchair graphene nanoribbons by using antidotes
    • Authors: M Zoghi, AY Goharrizi, M Saremi
    • Journal: Journal of Electronic Materials
    • Year: 2017
    • Citations: 77
  4. A numerical study of line-edge roughness scattering in graphene nanoribbons
    • Authors: A Yazdanpanah, M Pourfath, M Fathipour, H Kosina, S Selberherr
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2011
    • Citations: 71
  5. Device performance of graphene nanoribbon field-effect transistors in the presence of line-edge roughness
    • Authors: AY Goharrizi, M Pourfath, M Fathipour, H Kosina
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2012
    • Citations: 67
  6. Tuning electronic, magnetic, and transport properties of blue phosphorene by substitutional doping: a first-principles study
    • Authors: F Safari, M Fathipour, A Yazdanpanah Goharrizi
    • Journal: Journal of Computational Electronics
    • Year: 2018
    • Citations: 44
  7. An analytical model for line-edge roughness limited mobility of graphene nanoribbons
    • Authors: AY Goharrizi, M Pourfath, M Fathipour, H Kosina, S Selberherr
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2011
    • Citations: 41
  8. SOI LDMOSFET with up and down extended stepped drift region
    • Authors: M Saremi, M Saremi, H Niazi, M Saremi, AY Goharrizi
    • Journal: Journal of Electronic Materials
    • Year: 2017
    • Citations: 40
  9. A new method for classification and identification of complex fiber Bragg grating using the genetic algorithm
    • Authors: A Rostami, A Yazdanpanah-Goharriz
    • Journal: Progress In Electromagnetics Research
    • Year: 2007
    • Citations: 31
  10. Strain-induced armchair graphene nanoribbon resonant-tunneling diodes
  • Authors: M Zoghi, AY Goharrizi
  • Journal: IEEE Transactions on Electron Devices
  • Year: 2017
  • Citations: 30