Naga Nithin Katta | Image Processing | Best Researcher Award

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Mr. Naga Nithin Katta | Image Processing | Best Researcher Award

Employee at Oppo | India

Naga Nithin Katta is a highly motivated computer science and engineering professional with a strong focus on innovation, research, and problem-solving. His expertise spans artificial intelligence, machine learning, computer vision, and full stack development, areas in which he has applied his skills to impactful projects. He has gained industrial exposure as a software engineer at OPPO, where he contributed to projects involving video stream analysis, automation of testing frameworks, and mobile AI deployment. Alongside his industry experience, he has been an active mentor in data structures and algorithms, helping students strengthen their problem-solving abilities. His leadership has been recognized through international competitions, including selection among the Top 100 teams globally in the Google Solution Challenge and multiple hackathon victories. With a balance of technical knowledge, practical implementation, and a passion for community contribution, he is steadily building a strong foundation as an emerging researcher with promising leadership potential.

Professional Profile

Scopus Profile

Education

Naga Nithin Katta is pursuing a Bachelor of Technology in Computer Science and Engineering at VNR Vignana Jyothi Institute of Engineering and Technology, where he has been developing a strong academic background in computing principles, software engineering, and applied technologies. Prior to this, he successfully completed a diploma in computer science from the Government Institute of Electronics, which provided him with a solid technical base in programming, database management, and system design. His educational journey has been complemented by active participation in research-oriented projects, hackathons, and collaborative learning platforms that encouraged innovation and problem-solving. He has consistently demonstrated academic excellence by integrating classroom knowledge with practical applications, which is evident in his project work and international recognition through competitive platforms. This strong educational foundation has equipped him with both theoretical and applied perspectives, allowing him to bridge the gap between academia and industry while nurturing his passion for research and development.

Professional Experience

Naga Nithin Katta has gained valuable professional experience as a software engineer at OPPO, where he contributed to significant projects aimed at improving efficiency and automation in mobile technologies. His work involved developing web applications using Vue.js and MySQL for managing project statuses, implementing video stream analysis through OpenCV and Python, and deploying AI models on mobile devices using ONNX and Beeware. He played a key role in creating a UI automation system powered by large language models, reducing manual testing efforts and enhancing accuracy. Additionally, he contributed to building a network operator testing automation tool, streamlining processes and reducing workforce requirements. Alongside his industry work, he served as a student mentor at SmartInterviews, guiding learners in data structures and algorithms and preparing them for technical challenges. This blend of industrial expertise and teaching experience reflects his versatility, ability to collaborate across teams, and passion for applying research in practical contexts.

Research Interest

Naga Nithin Kattaโ€™s research interests lie primarily in the fields of artificial intelligence, computer vision, natural language processing, and software engineering, with a particular focus on developing innovative solutions that bridge academic research and real-world applications. He has worked on projects such as sign language converters that integrate computer vision with generative AI and cloud technologies, reflecting his interest in human-computer interaction and accessibility-focused applications. His engagement with large language models and UI automation tools demonstrates his curiosity in advancing human-machine interaction and automated testing frameworks. Additionally, his focus on video stream analysis and frame detection highlights his inclination towards multimedia research and visual computing. He is also keen on exploring areas such as deep learning optimization, mobile AI deployment, and cloud-integrated intelligent systems. His vision is to contribute to impactful solutions that enhance everyday technologies while simultaneously pursuing scholarly outputs that advance scientific knowledge.

Research Skill

Naga Nithin Katta has developed strong research skills that enable him to design, implement, and evaluate innovative solutions across different domains of computer science. He is proficient in programming languages such as C, C++, Python, and Java, and demonstrates advanced knowledge in full stack development with tools like ReactJs, Vue.js, and MySQL. His expertise in AI and machine learning is reflected in projects involving computer vision, natural language processing, and model deployment on mobile devices. He has practical experience in research-driven software development, having implemented algorithms for video frame detection, gesture recognition, and UI automation powered by large language models. His familiarity with tools like OpenCV, ONNX, Flask, and cloud-based APIs allows him to conduct applied research efficiently. He also possesses strong problem-solving abilities, demonstrated by his role as a mentor in data structures and algorithms. His skills in bridging theoretical concepts with industrial applications showcase his potential as a future research leader.

Publications Top Notes

Title: Optical Motion Detection Language Generator: A Survey

Year: 2025

Conclusion

Naga Nithin Katta is a deserving candidate for the Best Researcher Award as he has consistently demonstrated innovation, technical expertise, and leadership in both academic and industrial settings. His impactful projects, including advancements in computer vision, automation, and AI-driven solutions, showcase contributions that address real-world challenges and benefit society. With proven recognition in global competitions, mentorship roles, and industry research experience, he has already made meaningful strides as an emerging researcher. With a continued focus on publishing in reputed venues and building stronger international collaborations, he holds significant potential to become a future leader in the research and technology community.

Marco Corrias | Automated Microscopy Image Analysis | Best Researcher Award

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Mr. Marco Corrias | Automated Microscopy Image Analysis | Best Researcher Award

PhD Candidate at University of Vienna, Austria

Marco Corrias is a dedicated Computational Materials Physicist with a strong foundation in physics, data analysis, and machine learning. Currently pursuing his PhD at the University of Vienna, his research focuses on the automated analysis of microscopy images, combining advanced signal processing with computer vision and pattern recognition. Marco is the founding member and primary developer of AiSurf, a robust open-source software that leverages AI for scientific image analysis. His academic path reflects consistent excellence, with both his BSc and MSc degrees completed with top honors. He is recognized for his interdisciplinary mindset, leadership in collaborative research, and commitment to scientific integrity. Marco has also made notable contributions through student mentorship, international conference participation, and high-impact publications. With a strong analytical skillset and a passion for innovation, he is emerging as a promising researcher at the intersection of physics and machine intelligence.

Professional Profileย 

Education๐ŸŽ“

Marco Corrias has pursued a distinguished academic path in physics and materials science. He earned his Bachelor of Science in Physics from the University of Cagliari in 2019, graduating cum laude with a thesis on thermoelectricity in complex materials. He then completed his Master of Science in Materials Physics and Nanoscience at the University of Bologna in 2021, again with cum laude distinction. His Master’s thesis explored the formation and dynamics of polarons in SrTiO3, demonstrating his deep understanding of condensed matter physics. Currently, Marco is undertaking a PhD in Computational Materials Physics at the University of Vienna, where he is engaged in interdisciplinary research that blends physics, computer vision, and artificial intelligence. Throughout his academic journey, Marco has consistently demonstrated excellence, curiosity, and a drive to innovate in both theoretical and applied aspects of physical science.

Professional Experience๐Ÿ“

Marco Corrias has amassed impactful professional experience during his ongoing PhD at the University of Vienna, where he plays a pivotal role in advancing automated image analysis techniques in materials science. As a founding member and main developer of AiSurf, he has designed and implemented a comprehensive open-source tool that uses machine learning and computer vision for microscopy image processing. His professional activities include scientific collaboration across disciplines, presenting research findings at international conferences, and mentoring graduate students. Marco has contributed to academic publications, including a high-impact paper recognized by IOP Publishing, and has played a leadership role in academic software development. Additionally, he co-supervised a master’s thesis, showcasing his capability in academic guidance and research communication. His role involves not only conducting simulations and data analysis but also managing software documentation and interdisciplinary project planning, underscoring his multifaceted professional engagement in computational research.

Research Interest๐Ÿ”Ž

Marco Corrias’ research interests lie at the interface of computational physics, materials science, and artificial intelligence. His primary focus is on the automated analysis of microscopy images, aiming to enhance pattern recognition and feature extraction using computer vision and machine learning techniques. He is particularly interested in applying these tools to understand physical phenomena in materials at the nanoscale. Marcoโ€™s work explores novel methodologies for signal processing and statistical modeling to improve the reproducibility and accuracy of scientific image interpretation. He is also deeply engaged in the development of open-source research tools that democratize access to advanced image analysis technologies. Other areas of interest include thermoelectric materials, polaron dynamics, and the application of high-performance computing in condensed matter systems. Marco is committed to interdisciplinary research that fosters innovation through the integration of physics-based modeling with data-driven techniques, contributing to both scientific discovery and technological advancement.

Award and Honor๐Ÿ†

Marco Corrias has received several academic awards and honors that reflect his dedication and excellence in research. He was the recipient of the Best Poster Award at the prestigious IUVSTA-ZCAM conference, highlighting the quality and originality of his scientific presentation. His research article was selected for inclusion in a celebratory collection of high-impact papers by IOP Publishing, underscoring the scientific value and recognition of his work in the international research community. Marco also successfully completed the Path of Excellence program at the University of Cagliari, an honor awarded to top-performing undergraduate students. These accolades showcase his strong research potential and his ability to effectively communicate complex scientific ideas. In addition to formal recognitions, Marco has actively participated in international academic events, further building his reputation as a rising researcher in computational materials physics. His consistent achievements set a solid foundation for future contributions to his field.

Research Skill๐Ÿ”ฌ

Marco Corrias possesses a strong set of research skills that span computational, analytical, and technical domains. He is highly proficient in programming languages such as Python, C++, R, and Unix, which he applies extensively in data analysis, scientific computing, and software development. His expertise includes machine learning, computer vision, and signal processing, particularly for the analysis of microscopy images in materials science. Marco is the key developer of AiSurf, an open-source software that integrates advanced algorithms for image recognition and pattern extraction. His skillset also includes statistical modeling, numerical simulation, and interdisciplinary collaboration. Marco is adept at documenting and maintaining research codebases and ensuring software usability within academic research contexts. He complements his technical proficiency with soft skills such as teamwork, analytical thinking, problem-solving, and project planning. Together, these skills position him as a highly capable and versatile researcher, well-equipped to address complex scientific challenges with innovative computational approaches.

Conclusion๐Ÿ’ก

Marco Corrias is a strong candidate for the Best Researcher Award, especially considering his innovative contributions to the fusion of computer vision and physics, open-source development, and award-winning research presentations. His work is highly interdisciplinary, bridging the gap between physics, machine learning, and microscopyโ€”an area of growing scientific importance.

With continued publication and greater international engagement, Marco has the potential to emerge as a leading figure in computational materials science and AI-based image analysis. He is suitable for the award, and his profile reflects both current excellence and promising future impact.

Publications Top Notedโœ

  • Title:
    Automated real-space lattice extraction for atomic force microscopy images

  • Authors:
    Marco Corrias, Lorenzo Papa, Igor Sokoloviฤ‡, Viktor Birschitzky, Alexander Gorfer, Martin Setvin, Michael Schmid, Ulrike Diebold, Michele Reticcioli, Cesare Franchini

  • Year of Publication:
    2023

  • Journal:
    Machine Learning: Science and Technology

  • DOI:
    10.1088/2632-2153/acb5e0

  • Source:
    Crossref

  • Citation (as of now):
    (Please note: live citation counts change over time. For the most accurate and current citation count, you should check Google Scholar or Scopus directly.)

Bharati Chaudhari | Edge Detection | Best Researcher Award

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Ms . Bharati Chaudhari | Edge Detection | Best Researcher Award

Assitstant Professor at Maharashtra Institute of Technology, Chh. Sambhajinagar, India

Ms. Bharati Prakash Chaudhari is an experienced academician and researcher with over 18 years of teaching experience in computer science and engineering. Currently serving as an Assistant Professor at MIT, Aurangabad, she has consistently demonstrated a strong commitment to research and education. Her expertise spans image processing, machine learning, and digital system development, with active contributions to both academic research and industry-oriented projects. She has authored multiple research papers in international journals and conferences, including Scopus-indexed publications and IEEE proceedings. Additionally, her involvement in intellectual property development through several copyrights underscores her original contributions to technical education. Ms. Chaudhari continues to pursue her Ph.D. in Computer Science and Engineering at Dr. Babasaheb Ambedkar Marathwada University, reflecting her dedication to academic growth. Her work bridges theoretical knowledge with practical application, particularly through collaborations with industry for digital tool development. She is a proactive, skilled, and forward-looking researcher shaping the field of computer engineering.

Professional Profileย 

Education๐ŸŽ“

Ms. Bharati Prakash Chaudhari holds a Master of Engineering degree in Computer Science and Engineering from Government College of Engineering, Aurangabad, affiliated with Dr. Babasaheb Ambedkar Marathwada University (Dr. B.A.M.U.), where she graduated in 2010 with distinction, scoring 81.25%. She earned her Bachelor of Engineering in Computer Engineering from K.K. Wagh College of Engineering, Nashik under Pune University in 2003, securing first-class marks with 62.2%. Currently, she is pursuing her Ph.D. in Computer Science and Engineering from Dr. B.A.M.U., Aurangabad. Her academic background showcases a steady progression through well-regarded institutions and reflects a continuous pursuit of advanced knowledge in her domain. Her postgraduate studies have equipped her with a solid foundation in algorithm development, computational models, and system-level design. The ongoing doctoral research further strengthens her analytical and research capabilities, positioning her to contribute meaningfully to emerging trends in machine learning and image processing.

Professional Experience๐Ÿ“

Ms. Bharati Prakash Chaudhari has over 18 years of professional academic experience in engineering education. She began her teaching career in February 2003 at MIT IT College, Cidco, Aurangabad, serving as a Lecturer for over three years. Since July 2006, she has been affiliated with MIT, Aurangabad, initially as a Lecturer and later redesignated as an Assistant Professor. Throughout her tenure, she has taught various core subjects in computer science and engineering and actively engaged in curriculum development and mentoring students. Her long-standing commitment to teaching is complemented by her involvement in research, project guidance, and departmental responsibilities. She has also contributed to industry-academic collaboration through participation in projects like digital tool development for transformer design, under GIZโ€“MASSIA initiatives. Ms. Chaudhariโ€™s experience demonstrates not only her academic dedication but also her ability to integrate applied engineering practices into her educational approach, enhancing student learning and research culture.

Research Interest๐Ÿ”Ž

Ms. Bharati Prakash Chaudhari’s research interests center around Image Processing, Machine Learning, and Optimization Algorithms, with a keen focus on applying intelligent computing methods to solve practical problems in healthcare and security. Her recent work on edge detection using Ant Colony Optimization for medical images illustrates her interest in bio-medical image analysis. She also explores areas such as reversible data hiding, digital watermarking, and encrypted image processingโ€”topics that are critical to data security and digital forensics. Her Ph.D. research and publications reflect an effort to integrate biologically inspired algorithms into traditional image processing techniques. Moreover, she has shown a consistent interest in enhancing data representation, pattern recognition, and system intelligence. Through hybrid algorithm development and advanced segmentation techniques, Ms. Chaudhari aims to push the boundaries of image understanding and machine learning applications, particularly in domains where accurate visual interpretation is crucial, such as diagnostics, surveillance, and automation.

Award and Honor๐Ÿ†

Ms. Bharati Prakash Chaudhari has been recognized for her scholarly contributions through multiple Intellectual Property Rights (IPRs) registrations, including copyrights on algorithmic learning materials and applied computer science concepts such as Dijkstraโ€™s Algorithm, Histogram Equalization, and Finite Automata Design. These IPRs reflect her dedication to developing high-quality, original educational content and research outputs. While formal academic awards are not explicitly listed, her achievements in publishing papers in Scopus-indexed journals and prestigious conferences like IEEE and Elsevier Procedia signify academic excellence. Her active involvement in applied research projects, such as the Digital Tool Development for Transformer Design under a government-industry partnership (GIZ-MASSIA), further underscores her practical impact. Through these achievements, she has earned peer recognition within academic and industrial circles. Her participation in international events and successful collaborations with senior researchers demonstrate her growing reputation as a capable and emerging researcher in the field of computer engineering.

Research Skill๐Ÿ”ฌ

Ms. Bharati Prakash Chaudhari possesses strong research skills across multiple domains of computer science, particularly in image analysis, optimization algorithms, and machine learning models. She is proficient in applying Ant Colony Optimization, ICA (Independent Component Analysis), and encryption-based data hiding techniques for real-world problems. Her skill set includes the ability to design experimental methodologies, simulate and validate results, and interpret complex datasets for image processing tasks. She is adept at using MATLAB and other relevant software tools for developing and testing algorithms. Additionally, she is capable of translating conceptual ideas into practical implementations, as evident in her industry collaboration for transformer design automation. Her copyright registrations for algorithmic content reflect her strength in educational research and tool development. With a foundation in both academic writing and hands-on experimentation, Ms. Chaudhari’s research competencies bridge theoretical understanding and applied problem-solvingโ€”making her a valuable contributor to innovation-driven computing research.

Conclusion๐Ÿ’ก

Ms. Bharati Prakash Chaudhari is a strong candidate for the Best Researcher Award, especially given her longevity in academia, publication record, IPRs, and participation in reputed conferences. However, to be a top-tier awardee, finalizing her Ph.D. and enhancing her presence in globally ranked journals, along with measurable citation metrics, would make her profile even more competitive.

Publications Top Notedโœ

  • Title: Hepatoprotective activity of Hydroalcoholic extract of Momordica charantia Linn. leaves against Carbon tetrachloride induced Hepatopathy in Rats
    Authors: KRB, Chaudhari BP, VJ Chaware, YR Joshi
    Year: 2009
    Citations: 45

  • Title: Protective effect of the aqueous extract of Momordica charantia leaves on gentamicin induced nephrotoxicity in rats
    Authors: KRB, VJ Chaware, BP Chaudhary, MK Vaishnav
    Year: 2011
    Citations: 20

  • Title: Protective effect of the aqueous extract of Phaseolus radiatus seeds on gentamicin induced nephrotoxicity in rats
    Authors: VJ Chaware
    Year: 2012
    Citations: 16

  • Title: Quality by design (QbD) concept review in pharmaceuticals
    Authors: K Jagtap, B Chaudhari, V Redasani
    Year: 2022
    Citations: 11

  • Title: Development and validation of spectrophotometric method for simultaneous estimation of meclizine hydrochloride and pyridoxine hydrochloride in tablet dosage form
    Authors: SA Shinde, ZM Sayyed, BP Chaudhari, VJ Chaware, KR Biyani
    Year: 2016
    Citations: 10

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of amlodipine besylate and hydrochlorothiazide in combined dosage form
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, K Biyani
    Year: 2015
    Citations: 9

  • Title: A cross-sectional prescription audit database for anti-anginal drugs with impact of essential drug list and standard treatment guidelines on prescription pattern in Nasik city
    Authors: V Chaudhari, B Chaudhari, A Khairnar
    Year: 2011
    Citations: 7

  • Title: Approaches of digital image watermarking using ICA
    Authors: BP Chaudhari, AK Gulve
    Year: 2010
    Citations: 7

  • Title: A Review on in situ Gel of Gastro Retentive Drug Delivery System
    Authors: BV Aiwale, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 6

  • Title: Image segmentation using hybrid ant colony optimization: A review
    Authors: B Chaudhari, P Shetiye, A Gulve
    Year: 2021
    Citations: 6

  • Title: A Review on Diverging approaches to Fabricate Polymeric Nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 5

  • Title: A Validated RP-HPLC Method for Simultaneous Estimation of Tizanidine and Nimesulide in Bulk and Pharmaceutical Formulation
    Authors: KD Bharatee Chaudhari
    Year: 2020
    Citations: 5

  • Title: Pharmacosome as a Vesicular Drug Delivery System
    Authors: RR Shinde, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 4

  • Title: Influence of Newly Synthesized Superdisintegrant on Dissolution Rate Enhancement of Carbamazepine using Liquisolid Compact Technique
    Authors: GV Raut, PB Chaudhari, KV Redasani
    Year: 2022
    Citations: 4

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of spironolactone and hydrochlorothiazide in pharmaceutical formulation
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, M Zuber, M Sayyed
    Year: 2015
    Citations: 4

  • Title: A compendious review on biodegradable polymeric nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 3

  • Title: Cleaning Validation in Pharmaceutical Industry
    Authors: P Khalate, B Chaudhari, V Redasani
    Year: 2022
    Citations: 2

  • Title: A Novel Tool for Controlled Delivery: Transdermal Drug Delivery System
    Authors: AV Panval, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 2

  • Title: A Review on Pharmaceutical Regulatory Authority of India, USA, UK, Australia
    Authors: AA Shinde, AS Gurav, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

  • Title: Review on Colon Targeted Drug Delivery System
    Authors: NB Waghmode, SV Dhanje, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

Prof. Vaclav Skala | Computer Vision | Best Researcher Award

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Prof. Vaclav Skala | Computer Vision | Best Researcher Award

Professor at University of West Bohemia, Czech Republic

๐Ÿ‘จโ€๐ŸŽ“ Publication Profiles

Scopus

Orcid

Publications

A new fully projective O(lg N) line convex polygon intersection algorithm

  • Authors: Vรกclav V. Skala
    Journal: Visual Computer
    Year: 2025

A new fully projective O(log N) point-in-convex polygon algorithm: a new strategy

  • Authors: Vรกclav V. Skala
    Journal: Visual Computer
    Year: 2024

Meshfree Interpolation of Multidimensional Time-Varying Scattered Data

  • Authors: Vรกclav V. Skala, Eliska E. Mourycova
    Journal: Computers
    Year: 2023

Multispectral Image Generation from RGB Based on WSL Color Representation: Wavelength, Saturation, and Lightness

  • Authors: Vรกclav V. Skala
    Journal: Computers
    Year: 2023

Robust Line-Convex Polygon Intersection Computation in E2 using Projective Space Representation

  • Author: Vรกclav V. Skala
    Journal: Machine Graphics and Vision
    Year: 2023

Dr. Zhou Zhang | Computer Vision | Best Researcher Award

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Dr. Zhou Zhang | Computer Vision | Best Researcher Award

Doctorate at SUNY Farmingdale State College, United States

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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Google Scholar

๐ŸŽ“ Early Academic Pursuits

Dr. Zhou (Joe) Zhang embarked on his academic journey with a strong foundation in mechanical and electrical engineering. His early education culminated in a Ph.D. in Mechanical Engineering from Stevens Institute of Technology, where he was awarded the prestigious James Harry Potter Award in 2018 for outstanding doctoral performance. During his doctoral studies, Dr. Zhang explored virtual reality applications in engineering education, including camera pose tracking, data fusion, and the development of virtual laboratoriesโ€”an area that would become a cornerstone of his future research.

๐Ÿซ Professional Endeavors

Dr. Zhangโ€™s academic career is marked by progressive teaching and research roles. He currently serves as an Assistant Professor at SUNY Farmingdale State College, where he teaches Tool Design and Electronics Packaging. Previously, he held key positions including Associate Professor at Middle Tennessee State University and Assistant Professor at CUNYโ€™s New York City College of Technology, where he played a central role in launching and coordinating the Robotics Concentration. His professional journey also includes roles as a Visiting Research Scholar at NYU, a Research Associate at Southeast University, and an Electrical Engineer at CRRC Nanjing Puzhen Co., Ltd, as well as a Mechanical Engineer at CETCโ€™s 14th Research Institute.

๐Ÿ”ฌ Contributions and Research Focus

Dr. Zhangโ€™s research bridges academic theory and practical implementation. His major contributions span virtual reality (VR) and augmented reality (AR) for engineering education, AI and machine learning applications in robotics, force-feedback robotics, and bio-inspired virtual assembly systems. His work has been funded by institutions such as CUNY GRTI and CUNY Research Awards, including notable projects like the AI and Machine Learning in Co-Robotics and the Virtual Assembly Platform for Engineering Education. Earlier in his career, he was also involved in state-funded research in China, including a $5 million smart controller project backed by the State Grid Corporation of China.

๐ŸŒ Impact and Influence

Dr. Zhang has made a tangible impact on student development, workforce readiness, and interdisciplinary education. His initiatives include establishing co-op and internship collaborations with industry, mentoring undergraduate research, and leading programs like the Virtual Reality and Artificial Intelligence Club. He also contributed to maintaining ABET accreditation, aligning curriculum development with institutional and industry standards. His mentorship has supported student participation in key events such as the Brooklyn Navy Yard Competition, Maker Faire, and the CUNY Black Male Initiative Conference.

๐Ÿ“š Academic Citations & Publications

Dr. Zhangโ€™s scholarly work is extensively cited in the domains of VR-based education, 3D reconstruction, force-feedback robotics, and embedded systems. His contributions have not only advanced academic research but also enriched applied engineering education. As one of the main investigators in several NSF-funded projects, his research continues to influence both academic curricula and practical engineering tools.

๐Ÿ’ป Technical Skills

Dr. Zhang is proficient in a variety of engineering and programming tools, including virtual reality system design, computer-aided engineering, middleware integration, finite element methods (FEM), and AI/machine learning applications in robotics. His skills encompass real-time 3D reconstruction, electromagnetic field simulation, and embedded systems design, with applications extending to DSP, ARM-based controls, and semiconductor converters.

๐Ÿง‘โ€๐Ÿซ Teaching Experience

With over two decades of teaching experience, Dr. Zhang has taught a wide array of courses across institutions like SUNY Farmingdale, CUNY, NJIT, and Middle Tennessee State University. His teaching portfolio includes Mechanical Measurement, Stress Analysis, Rapid Prototyping, Programmable Logic Controllers, and AI-integrated robotics courses. He has served in diverse capacitiesโ€”course designer, club advisor, curriculum developer, and research mentorโ€”demonstrating his commitment to academic excellence and student engagement.

๐Ÿ† Awards and Honors

Dr. Zhang has received multiple accolades for his dedication to academic and research excellence. In addition to the James Harry Potter Award, he earned graduate travel grants from Stevens Institute of Technology, recognizing his contributions to engineering research and academic dissemination.

๐Ÿš€ Legacy and Future Contributions

Dr. Zhangโ€™s legacy lies in his ability to blend innovative research with effective teaching, transforming traditional mechanical engineering education through technology. His future goals include advancing interdisciplinary robotics education, expanding virtual learning platforms, and fostering global academic-industry collaborations. With a career devoted to bridging theoretical knowledge and real-world applications, Dr. Zhang continues to inspire students and colleagues alike, shaping the future of engineering education and technological innovation.

 

Publications

The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection

  • Authors: Momina Liaqat Ali, Zhou Zhang
    Journal: Computers
    Year: 2024

Project-Based Courses for B.Tech. Program of Robotics in Mechanical Engineering Technology

  • Authors: Zhang Z., Zhang A.S., Zhang M., Esche S.
    Journal:     Computers in Education Journal
    Year:     2020

A Virtual laboratory system with biometric authentication and remote proctoring based on facial recognition

  • Authors: Zhang, Z.; Zhang, M.; Chang, Y.; Esche, S.K.; Chassapis, C.
    Journal: Computers in Education
    Year: 2016

Real-time 3D reconstruction for facilitating the development of Game-based virtual laboratories

  • Authors: Zhang, Z.; Zhang, M.; Chang, Y.; Esche, S.K.; Chassapis, C.
    Journal:     Computers in Education
    Year:     2016

Usability evaluation of a virtual educational laboratory platform

  • Authors: Chang, Y.; Aziz, E.-S.S.; Zhang, Z.; Zhang, M.; Esche, S.K.
    Journal: Computers in Education
    Year: 2016

Dr. Ghulam Murtaza | Image Processing | Best Academic Researcher Award

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Dr. Ghulam Murtaza | Image Processing | Best Academic Researcher Award

Doctorate at National University of Modern Languages, Pakistan

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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๐Ÿ“Œ Summary

Dr. Ghulam Murtaza is an Assistant Professor in the Department of Mathematics at the National University of Modern Languages (NUML), Islamabad. His research focuses on developing new mathematical models in cryptography, particularly in elliptic curve and chaotic maps-based cryptosystems. With a passion for innovation, he mentors students and actively contributes to cutting-edge research in mathematical cryptography and machine learning-based cryptosystems.

๐ŸŽ“ Education

  • PhD in Mathematics (2019โ€“2023) โ€“ Quaid-i-Azam University
    Dissertation: Image Cryptosystems Using Elliptic Curve Cryptography

  • MPhil in Mathematics (2015โ€“2017) โ€“ Quaid-i-Azam University
    Dissertation: Learning From Data Using Algebraic Geometry

  • MSc in Mathematics (2013โ€“2015) โ€“ Quaid-i-Azam University

  • BSc in Mathematics & Physics (2010โ€“2012) โ€“ Bahauddin Zakariya University

๐Ÿ‘จโ€๐Ÿซ Professional Experience

  • Assistant Professor โ€“ NUML, Islamabad (2023โ€“Present)

  • Visiting Assistant Professor โ€“ Quaid-i-Azam University (2023)

  • Visiting Lecturer โ€“ Quaid-i-Azam University (2023โ€“2024)

  • Lecturer โ€“ University of Lahore, Pakpattan Campus (2017โ€“2019)

๐Ÿ† Awards & Honors

  • First-class academic record from Matric to MPhil

  • Mrs. Rehmat Shahbuddin Memorial Scholarship (MSc, 2013โ€“2015)

  • Merit Scholarship โ€“ Quaid-i-Azam University

  • Shahbaz Sharif Youth Initiative Laptop Scheme (2012)

๐Ÿ”ฌ Research Interests

  • Elliptic Curve Cryptography

  • Chaotic Maps-Based Cryptography

  • Machine Learning for Cryptosystems

  • Dynamical Systems & Isogeny-Based Cryptography

 

Publications

Efficient Image Encryption Algorithm Based on ECC and Dynamic S-Box

  • Author: Ghulam Murtaza, Umar Hayat
    Journal: Journal of Information Security and Applications
    Year: 2025

Enumerating Discrete Resonant Rossby/Drift Wave Triads and Their Application in Information Security

  • Author: Umar Hayat, Ikram Ullah, Ghulam Murtaza, Naveed Ahmed Azam, Miguel D. Bustamante
    Journal: Mathematics
    Year: 2022

Designing an Efficient and Highly Dynamic Substitution-Box Generator for Block Ciphers Based on Finite Elliptic Curves

  • Author: Ghulam Murtaza, Naveed Ahmed Azam, Umar Hayat, Iqtadar Hussain
    Journal: Security and Communication Networks
    Year: 2021

Mr. Jiahao Nie | Image Processing | Best Researcher Award

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Mr. Jiahao Nie | Image Processing | Best Researcher Award

Hangzhou Dianzi University, China

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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๐Ÿ“Œย Summary

Mr. Jiahao Nie is a dedicated Ph.D. candidate at Hangzhou Dianzi University (HDU) and Hanyang University (HYU), specializing in computer vision, 2D image processing, and 3D point cloud processing. Under the guidance of Prof. Zhiwei He and Assoc. Prof. Dong-Kyu Chae, he is actively engaged in cutting-edge research in autonomous driving and object tracking.

๐ŸŽ“ย Education

  • Ph.D. in Electronic Science and Technology (HDU, 2022-2025)
  • Joint Ph.D. in Computer Science (HYU, 2024-2025)
  • B.Eng. in Electronic Information Engineering (HDU, 2020-2022)

๐Ÿ”ฌย Research Interests

His research is primarily focused on computer vision, including 2D image processing, 3D point cloud processing, and object tracking for autonomous driving.

๐Ÿ†Honors & Awards

  • Ph.D. National Scholarship (Rank: 1/75)ย |ย Full Postgraduate Scholarship (2020-2025)
  • First-Class Academic Scholarship (Top 3%)ย |ย National Scholarship for Studying Abroad (2023)

๐Ÿ“‘ Academic Contributions

  • Reviewer for ICCV, CVPR, ICLR, ICML, ECCV, NeurIPS, AAAI, ACM MM
  • Presenter at ICLR (2024), IJCAI (2023), AAAI (2023)

 

Publications

TTSNet: state-of-charge estimation of Li-ion battery in electrical vehicles with temporal transformer-based sequence network

  • Authors: Zhengyi Bao, Jiahao Nie, Huipin Lin, Kejie Gao, Zhiwei He, Mingyu Gao
  • Journal: IEEE Transactions on Vehicular Technology
  • Year: 2024

A fine-grained feature decoupling based multi-source domain adaptation network for rotating machinery fault diagnosis

  • Authors: Xiaorong Zheng, Jiahao Nie, Zhiwei He, Ping Li, Zhekang Dong, Mingyu Gao
  • Journal: Reliability Engineering & System Safety
  • Year: 2024

A progressive multi-source domain adaptation method for bearing fault diagnosis

  • Authors: Xiaorong Zheng, Zhiwei He, Jiahao Nie, Ping Li, Zhekang Dong, Mingyu Gao
  • Journal: Applied Acoustics
  • Year: 2024

Dual-task learning for joint state-of-charge and state-of-energy estimation of lithium-ion battery in electric vehicle

  • Authors: Zhengyi Bao, Jiahao Nie, Huipin Lin, Zhi Li, Kejie Gao, Zhiwei He, Mingyu Gao
  • Journal: IEEE Transactions on Transportation Electrification
  • Year: 2024

TM2B: Transformer-Based Motion-to-Box Network for 3D Single Object Tracking on Point Clouds

  • Authors: Anqi Xu, Jiahao Nie*, Zhiwei He, Xudong Lv
  • Journal: IEEE Robotics and Automation Letters
  • Year: 2024

Dr. Hua Ren | Image Processing | Best Researcher Award

Published on by Computer Vision Awards

Dr. Hua Ren | Image Processing | Best Researcher Award

Doctorate at Henan Normal University, China

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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๐Ÿ“Œย Summary

Dr. Hua Ren is a dedicated researcher and lecturer specializing in image security, encryption, and data hiding. His expertise lies in visually secure encryption and authentication technologies, contributing significantly to high-impact journals and research projects in these domains.

๐ŸŽ“ย Education

  • Ph.D.ย in Computer Science and Technology, Beijing University of Posts and Telecommunications (2019-2023)
  • Masterโ€™sย in Computer Science and Technology, Henan Normal University (2016-2019)
  • Bachelorโ€™sย in Computer Science and Technology, Henan Normal University (2012-2016)

๐Ÿ’ผย Work & Research Experience

  • Lecturer (2023-Present)ย โ€“ School of Computer and Information Engineering, Henan Normal University
  • Principal Investigatorย โ€“ Henan Science and Technology Research Project on image reversible authentication (2025-2026)

๐Ÿ”ฌย Research Interests

  • Image Security & Encryption
  • Reversible Data Hiding
  • Visual Authentication & Cryptography
  • Digital Image Processing

 

Publications

A novel reversible data hiding method in encrypted images using efficient parametric binary tree labeling

  • Authors: Hua Ren, Zhen Yue, Feng Gu, Ming Li, Tongtong Chen, Guangrong Bai
  • Journal: Knowledge-Based Systems
  • Year: 2024

Multi-scale attention context-aware network for detection and localization of image splicing

  • Authors: Ruyong Ren, Shaozhang Niu, Junfeng Jin, Jiwei Zhang, Hua Ren, Xiaojie Zhao
  • Journal: Applied Intelligence
  • Year: 2023

ERINet: Efficient and robust identification network for image copy-move forgery detection and localization

  • Authors: Ruyong Ren, Shaozhang Niu, Junfeng Jin, Keyang Xiong, Hua Ren
  • Journal: Applied Intelligence
  • Year: 2023

ESRNet: Efficient Search and Recognition Network for Image Manipulation Detection

  • Authors: Ruyong Ren, Shaozhang Niu, Hua Ren, Shubin Zhang, Tengyue Han, Xiaohai Tong
  • Journal: ACM Transactions on Multimedia Computing, Communications, and Applications
  • Year: 2022

Joint encryption and authentication in hybrid domains with hidden double random-phase encoding

  • Authors: Hua Ren, Shaozhang Niu
  • Journal: Multimedia Tools and Applications
  • Year: 2022

Dr. Recai Yilmaz | Applications of Computer Vision | Best Researcher Award

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Dr. Recai Yilmaz | Applications of Computer Vision | Best Researcher Award

Doctorate at Children’s National Hospital, Washington, D.C, United States

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๐ŸŽ“ย Early Academic Pursuits

Dr. Recai Yilmaz’s academic journey began with a strong foundation in medicine, earning his M.D. fromย Istanbul Faculty of Medicineย in 2017. His passion for medical innovation led him to pursue aย Ph.D. in Experimental Surgeryย atย McGill University, focusing on neurosurgical simulation and artificial intelligence. His early education atย Private Anafen Gaye High Schoolย in Istanbul, where he was a full-scholarship student, demonstrated his academic excellence from a young age.

๐Ÿ’ผย Professional Endeavors

Dr. Yilmaz has amassed extensive experience at the intersection ofย medicine, artificial intelligence, and computer vision. As aย Postdoctoral Research Fellow at Children’s National Medical Center, Washington, D.C., he appliesย computer vision and machine learningย to intraoperative surgical video analysis, aiming to improve real-time surgical performance assessment. His tenure atย MultiCIM Technologies Inc. (CareChain)ย further reflects his leadership in integrating AI intoย patient triage and clinical decision-making systems.

๐Ÿ”ฌย Contributions and Research Focus

Dr. Yilmazโ€™s research is centered onย AI-driven surgical assessment, medical data organization, and neurosurgical simulation. Atย McGill Universityโ€™s Neurosurgical Simulation and Artificial Intelligence Learning Centre, he developedย virtual reality surgical simulation models, advanced AI-based assessment tools, andย real-time feedback mechanismsย for neurosurgical expertise evaluation. His research also includesย cloud-based medical data management and optical flow analysis in surgical procedures.

๐ŸŒย Impact and Influence

His pioneering work has significantly influencedย AI applications in surgery and clinical decision-making. By integratingย computer vision and deep learningย into medical practice, he has improved the efficiency and accuracy ofย surgical skill evaluation, patient triage, and clinical outcome prediction. His projects have not only enhanced surgical education but also contributed to safer and more effectiveย surgical procedures worldwide.

๐Ÿ“šย Academic Citations and Recognitions

Dr. Yilmaz has been recognized with numerousย awards and grants, including the prestigiousย Innovator of the Year Award (2023) by the Congress of Neurological Surgeonsย and research funding from theย Brain Tumour Foundation of Canadaย and theย Royal College of Physicians and Surgeons of Canada. His work has been published inย high-impact journals and conferences, advancing the field of AI in medicine.

๐Ÿ’ปย Technical Expertise

  • Artificial Intelligence & Machine Learningย (Medical AI applications, Neural Networks)
  • Computer Vision & Image Processingย (Surgical video analysis, Optical flow)
  • Programming Languagesย (Python, MATLAB, C++, IBM SPSS)
  • Statistical Analysis & Data Scienceย (AI-driven performance assessment, Data modeling)

๐ŸŽ“ย Teaching and Mentorship

Dr. Yilmaz has actively mentoredย graduate students, medical researchers, and undergraduate studentsย inย AI, neurosurgical simulation, and data analysis. His mentorship spans institutions such asย McGill University and Marianopolis College, where he has guided students inย machine learning applications, research methodologies, and clinical AI integration.

๐ŸŒŸย Legacy and Future Contributions

Dr. Yilmazโ€™s legacy lies in his commitment toย bridging AI and medicine. His contributions toย surgical performance evaluation, AI-driven triage systems, and neurosurgical educationย continue to shape theย future of AI-assisted medical practice. Moving forward, he aims toย expand AI integration in real-time surgical decision-making, enhance global accessibility to AI-driven surgical training, and pioneer intelligent healthcare solutions.

 

Publications

AI in surgical curriculum design and unintended outcomes for technical competencies in simulation training

  • Authors:Ali M Fazlollahi, Recai Yilmaz, Alexander Winkler-Schwartz, Nykan Mirchi, Nicole Ledwos, Mohamad Bakhaidar, Ahmad Alsayegh, Rolando F Del Maestro
  • Journal: JAMA network open
  • Year: 2023

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

  • Authors: Sharif Natheir, Sommer Christie, Recai Yilmaz, Alexander Winkler-Schwartz, Khalid Bajunaid, Abdulrahman J Sabbagh, Penny Werthner, Jawad Fares, Hamed Azarnoush, Rolando Del Maestro
  • Journal: Computers in Biology and Medicine
  • Year: 2023

O022 real-time artificial intelligence instructor vs expert instruction in teaching of expert level tumour resection skillsโ€“a randomized controlled trial

  • Authors: R Yilmaz, M Bakhaidar, A Alsayegh, R Del Maestro
  • Journal: British Journal of Surgery
  • Year: 2023

Effect of artificial intelligence tutoring vs expert instruction on learning simulated surgical skills among medical students: a randomized clinical trial

  • Authors: Ali M Fazlollahi, Mohamad Bakhaidar, Ahmad Alsayegh, Recai Yilmaz, Alexander Winkler-Schwartz, Nykan Mirchi, Ian Langleben, Nicole Ledwos, Abdulrahman J Sabbagh, Khalid Bajunaid, Jason M Harley, Rolando F Del Maestro
  • Journal: JAMA network open
  • Year: 2022

Assessment of learning curves on a simulated neurosurgical task using metrics selected by artificial intelligence

  • Authors: Nicole Ledwos, Nykan Mirchi, Recai Yilmaz, Alexander Winkler-Schwartz, Anika Sawni, Ali M Fazlollahi, Vincent Bissonnette, Khalid Bajunaid, Abdulrahman J Sabbagh, Rolando F Del Maestro
  • Journal: Journal of neurosurgery
  • Year: 2022

Prof. Nema Salem | Image Processing | Best Researcher Award

Published on by Computer Vision Awards

Prof. Nema Salem | Image Processing | Best Researcher Award

Professor at Effat University, Saudi Arabia

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๐ŸŽ“ Early Academic Pursuits

Prof. Nema Salemโ€™s academic journey began with a strong foundation in engineering and medical imaging. She earned her B.Sc. with honors in 1987 and later obtained her M.Sc. in 1990 from Alexandria University (AU), Egypt, specializing in mitral valve diagnosis. She further pursued her Ph.D. in “Classification of Breast Tumors by Acutance Measure and Shape Factors” through a joint program between the University of Calgary, Canada, and AU in 1996. Her early research laid the groundwork for advancements in medical diagnostics, particularly in breast cancer detection, setting the stage for a distinguished academic and research career.

๐Ÿ† Professional Endeavors

Prof. Salemโ€™s professional trajectory spans multiple prestigious institutions. Since 1987, she has held progressive academic roles at AU, the Asian Institute of Technology (AIT), Hadramout University in Yemen, and Effat University in Saudi Arabia, where she has been an Assistant Professor since 2008. She has also served as the Chair of the Electrical and Computer Engineering Department at Effat University, contributing to curriculum development and accreditation processes such as NCAAA and ABET. Her leadership extends beyond academia, as she has organized international competitions like the IET GCC Robotics Challenge and the World Robot Olympiad, promoting innovation among young engineers.

๐Ÿ”ฌ Contributions and Research Focus

Prof. Salemโ€™s research portfolio is marked by interdisciplinary contributions in medical imaging, artificial intelligence, control systems, and renewable energy. She has pioneered AI-driven applications, including ECG analysis, skin lesion segmentation, and glaucoma detection, enhancing the accuracy of medical diagnostics. Additionally, she has played a crucial role in renewable energy advancements, optimizing solar power generation and thermoelectric systems. Her expertise in robotics and control engineering is evident in her work on PID and LQR controllers for performance enhancement in automation and energy-efficient designs.

๐ŸŒ Impact and Influence

Prof. Salemโ€™s influence extends beyond her research, as she actively mentors students, supervises masterโ€™s and Ph.D. theses, and collaborates with international researchers. Her dedication to fostering innovation has resulted in students winning prestigious awards, including a bronze medal at the 49th International Exhibition in Geneva. She has also contributed significantly to the academic community through her editorial roles and peer-reviewing for high-impact journals. Her recognition includes the Queen Effat Award for Teaching Excellence (2019-2020, 2022-2023) and a UK Fellowship for teaching excellence, affirming her commitment to quality education and research.

๐Ÿ“š Academic Citations and Publications

Prof. Salemโ€™s research is well-documented in reputable journals and conferences. She has published extensively in IEEE Transactions on Medical Imaging, PLOS ONE, Sensors, and IEEE Access, with a strong presence in high-impact publications. Her work is widely cited, reflecting its significance in medical imaging, artificial intelligence, and renewable energy. Her research contributions are accessible via Google Scholar and the AD Scientific Index 2024, demonstrating her academic reach and influence.

๐Ÿ’ก Technical Skills and Expertise

Prof. Salem possesses a diverse technical skill set, encompassing AI-driven signal and image processing, robotics, logic design, and renewable energy optimization. She has expertise in developing machine learning models for medical diagnostics, implementing control strategies for automation, and designing CMOS-based circuits. Her ability to integrate interdisciplinary approaches has made her a sought-after researcher in multiple domains, from biomedical engineering to energy-efficient systems.

๐Ÿ“– Teaching and Mentorship

With over three decades of teaching experience, Prof. Salem has played a pivotal role in shaping the next generation of engineers. She has designed and delivered courses in signal processing, artificial intelligence, control systems, and electronics. Her student-centered approach has been recognized through multiple teaching awards. She actively engages in student mentorship, encouraging innovative research projects and guiding them to success in international competitions and academic publishing.

๐Ÿ”ฎ Legacy and Future Contributions

Prof. Salemโ€™s legacy is defined by her relentless pursuit of innovation and knowledge dissemination. Her research continues to push the boundaries of technology, particularly in AI-driven healthcare and renewable energy systems. She remains committed to mentoring students, expanding research collaborations, and advancing engineering education. Through her leadership, she aims to drive impactful change in medical diagnostics, sustainable energy, and robotics, ensuring a lasting influence in academia and industry.

 

Publications

Artificially Intelligent Detection of Retinal Pigment Sign Using P3S-Net for Retinitis Pigmentosa Analysis

  • Authors: Syed Muhammad Ali Imran, Abida Hussain, Nema Salem, Muhammad Arsalan
    Journal: Results in Engineering
    Year: 2025

Causal Speech Enhancement Using Dynamical-Weighted Loss and Attention Encoder-Decoder Recurrent Neural Network

  • Authors: Fahad Khalil Peracha, Abdullah M. Mutawa, Muhammad Irfan Khattak, Nema Salem, Nasir Saleem
    Journal: PLOS ONE
    Year: 2023

Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization

  • Authors: Abeer Mushtaq, Maria Mumtaz, Ali Raza, Nema Salem, Muhammad Naveed Yasir
    Journal: Sensors
    Year: 2022

Automated Diagnosis of Leukemia: A Comprehensive Review

  • Authors: Afshan Shah, Syed Saud Naqvi, Khuram Naveed, Nema Salem, Mohammad A. U. Khan, Khurram S. Alimgeer
    Journal: IEEE Access
    Year: 2021

DAVS-NET: Dense Aggregation Vessel Segmentation Network for Retinal Vasculature Detection in Fundus Images

  • Authors: Mohsin Raza, Khuram Naveed, Awais Akram, Nema Salem, Amir Afaq, Hussain Ahmad Madni, Mohammad A. U. Khan, Mui-zzud-din
    Journal: PLOS ONE
    Year: 2021