Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

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Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

Dr. Ryszard Ćwiertniak, Krakow University of Economics, Poland

Dr. Ryszard Ćwiertniak is an accomplished expert in project management, specializing in agile methodologies, Design Thinking, and AI-driven innovation. He holds a PhD in Management and Quality Sciences from the University of Economics in Krakow and has a strong academic and professional background in administration, management, and electrical engineering. With extensive experience in research and teaching, he has contributed to the fields of digital transformation, e-learning, and Industry 4.0. As an IBM Design Thinking mentor and Early Warning Europe ambassador, he helps businesses implement cutting-edge solutions. His work spans academia, consulting, and applied research in AI and business process optimization.

🌍 Professional Profile:

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Dr. Ryszard Ćwiertniak’s pioneering research in AI-driven project management, digital transformation, and innovation management makes him an outstanding candidate for the Best Researcher Award. His involvement in Erasmus+ projects, contributions to Industry 4.0, and mentorship in agile methodologies showcase his impact on academia and industry. His expertise in AI-based decision-making, personalized education, and digital business models has transformed organizational processes. With numerous peer-reviewed publications, a book, and a grant-winning project, his research advances the future of smart business ecosystems. His leadership in AI-powered business solutions and educational innovations solidifies his reputation as a top researcher in the field.

🎓 Education 

Dr. Ryszard Ćwiertniak earned his PhD in Management and Quality Sciences from the University of Economics in Krakow (2019), focusing on innovation management. He also holds a Master’s degree in Administration and Management from the University of Warsaw (1994). In addition, he has a background in electrical engineering, equipping him with a multidisciplinary approach to research. His academic journey reflects a deep commitment to combining management principles with technology, particularly in AI applications, e-learning, and agile business strategies. His education has laid the foundation for his expertise in digital transformation, business innovation, and advanced project management methodologies.

💼 Professional Experience 

Dr. Ćwiertniak currently serves as an academic teacher at Krakow University of Economics, specializing in technology and product ecology. Previously, he was the Rector’s Representative for Quality of Education and E-learning at the College of Economics and Computer Science (2020–2024). His role in the Early Warning Europe initiative highlights his expertise in digital business transformation. He also contributes to the Erasmus+ program, working on AI-powered educational solutions. As an IBM Design Thinking mentor, he facilitates agile project implementation. His professional engagements bridge academia and industry, driving innovation, AI adoption, and digital business strategies in various sectors.

🏅 Awards and Honors 

🔹 Early Warning Europe Ambassador (2021–Present) – Recognized for supporting digital business transformation.
🔹 Erasmus+ Research Grant Recipient – Contributed to AI-driven education models.
🔹 Ministerial Research Grant Winner (2021) – Awarded funding for advancing e-learning and digital education techniques.
🔹 IBM Design Thinking Mentor – Certified expert in guiding agile and innovative project execution.
🔹 Industry 4.0 & AI Innovation Contributor – Acknowledged for pioneering work in integrating AI with project management and digital marketing.
🔹 Invited Researcher at THWS Business School (2024) – Recognized for leadership in AI-based digital transformation.

His contributions to AI, project management, and education technology have earned him national and international acclaim.

🔬 Research Focus

Dr. Ćwiertniak’s research spans AI-driven project management, innovation strategies, digital transformation, and e-learning technologies. He explores Industry 4.0 applications, AI-based decision-making, and agile methodologies to optimize business processes. His focus on digital business models, social media analytics, and e-commerce strategies has redefined marketing and management practices. Through Design Thinking and AI integration, he enhances project execution efficiency. His research also covers personalized education using AI, ensuring smarter, data-driven learning environments. As an expert in AI-powered business solutions, he contributes to making organizations more adaptable and efficient in an era of rapid technological advancements.

📊 Publication Top Notes:

  1. Rola potencjału innowacyjnego w modelach biznesowych nowoczesnych organizacji – próba oceny

    • Citations: 11
    • Year: 2015

  2. Zarządzanie portfelem projektów w organizacji: Koncepcje i kierunki badań

    • Citations: 4
    • Year: 2018

  1. Addressing students’ perceived value with the virtual university concept

    • Citations: 3
    • Year: 2022

  2. Kształtowanie portfela projektów w zarządzaniu innowacjami

    • Citations: 2
    • Year: 2018

  1. The concept of project evaluation in the implementation of innovation

    • Citations: 1
    • Year: 2020

 

 

Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

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Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

Prof. Ching Yee Suen, Concordia University, Canada

Prof. Ching Yee Suen is a globally recognized expert in Pattern Recognition, AI, and Document Analysis. As the Founding Director and Co-Director of CENPARMI at Concordia University, he has shaped advancements in handwriting recognition, multiple classifiers, and font analysis. A Fellow of IEEE, IAPR, and the Royal Society of Canada, he has mentored 120+ graduate students and 100 visiting scientists. With 550+ research papers, 16 books, and an h-index of 74, his contributions are widely cited. His innovations power millions of devices worldwide. He has led $20M+ research projects, collaborated with global industries, and serves as an editor for top-tier journals.

🌍 Professional Profile:

Google Scholar

🏆 Suitability for Best Researcher Award 

Prof. Suen is an exceptional candidate for the Best Researcher Award due to his pioneering contributions in AI, pattern recognition, and handwriting analysis. His research has real-world impact, with millions of users benefiting from his handwriting recognition algorithms. He has received top international awards, including the King-Sun Fu Prize (2021) and ICDAR Award (2005). As a leading AI researcher, he has secured $20M+ in funding, supervised over 120 Ph.D. and master’s students, and led groundbreaking industrial collaborations. His global influence, leadership in AI, and outstanding research output make him a worthy recipient of this prestigious honor.

🎓 Education 

Prof. Ching Yee Suen holds a Ph.D. from the University of British Columbia (UBC), Vancouver, and a Master’s degree from the University of Hong Kong. His academic journey has been marked by a deep focus on Artificial Intelligence, Pattern Recognition, and Computational Vision. His early research laid the foundation for his groundbreaking work in handwriting recognition, document analysis, and AI-powered classification systems. He has spent sabbatical leaves at MIT, McGill University, Ecole Polytechnique, and IBM, further expanding his expertise. His academic credentials have established him as a leading scholar in AI and pattern recognition on a global scale.

💼 Experience 

With a career spanning 50+ years, Prof. Suen has held key leadership roles at Concordia University, serving as Chairman of Computer Science, Associate Dean (Research), and Concordia Chair in AI & Pattern Recognition. He is the Founding Director and Co-Director of CENPARMI, where he has driven cutting-edge research. He has supervised 120+ graduate students and collaborated with top institutions worldwide. As a consultant to Microsoft, Xerox, Canada Post, and the US Congress, his work has had real-world impact. His editorial leadership in top AI journals and conference organization further cements his global influence in the research community.

🏅 Awards and Honors

Prof. Suen’s excellence is recognized globally, earning him top honors in AI and pattern recognition. He received the King-Sun Fu Prize (2021) 🏆, the ICDAR Award (2005) 🎖️, and the Elsevier Distinguished Editorial Award (2016)📜. His Concordia Lifetime Research Achievement Award (2008) and Teaching Excellence Award (1995) 🎓 highlight his impact in academia. Internationally, he was honored with the Gold Medal from the University of Bari, Italy (2012) 🥇. As a Fellow of IEEE, IAPR, and the Royal Society of Canada, his contributions to AI, document analysis, and handwriting recognition are celebrated at the highest levels.

🔬 Research Focus 

Prof. Suen specializes in Pattern Recognition, Artificial Intelligence, and Document Analysis. His innovations in handwriting recognition, fake coin detection, license plate recognition, and multi-classifier systems have transformed industry applications. His research integrates AI, deep learning, and image processing to solve complex problems in computer vision, natural language processing, and fraud detection. His high-impact contributions are widely used in mobile devices, banking security, and postal services. His multi-disciplinary approach in AI has led to real-world solutions adopted by Microsoft, Bell Canada, Canada Post, and global tech firms, making him a pioneer in intelligent pattern analysis.

📊 Publication Top notes:

  • Title: Developing Knowledge Management Metrics for Measuring Intellectual Capital
    • Year: 2000
    • Citations: 442
  • Title: Modified Hebbian Learning for Curve and Surface Fitting
    • Year: 1992
    • Citations: 322
  • Title: N-Gram Statistics for Natural Language Understanding and Text Processing
    • Year: 1979
    • Citations: 315
  • Title: Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition
    • Year: 1984
    • Citations: 176
  • Title: Large Tree Classifier with Heuristic Search and Global Training
    • Year: 1987
    • Citations: 102

 

 

Jingcheng Ke | Diffusion Models | Excellence in Research

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Jingcheng Ke | Diffusion Models | Excellence in Research

Dr. Jingcheng Ke, Osaka university, Japan.

Jingcheng Ke, Ph.D. 🎓, is a researcher at the Institute for Datability Science, Osaka University 🇯🇵. With a Ph.D. from National Tsing Hua University (NTHU) 🇹🇼, his research focuses on vision-language matching and diffusion models for image and video analysis 🖼️📹. He has worked as an AI researcher at vivo AI Lab and as an exchange student at Shenzhen Key Laboratory of Visual Object Detection and Recognition. Proficient in multiple languages 🌏 and programming 🖥️, Dr. Ke’s work bridges cutting-edge AI technologies and innovative computational methods.

Publication Profile

Googlescholar

Education & Experience:

Education

  • 🎓 Ph.D. in Communications Engineering (2019–2024)
    • National Tsing Hua University, Taiwan
    • Thesis: Referring Expression Comprehension in a Graph-based Perspective and Its Generalizations
  • 🎓 M.Sc. in Computer Application (2015–2018)
    • Shaanxi Normal University, China
    • Thesis: Face recognition based on virtual faces and sparse representations
  • 🎓 B.Sc. in Network Engineering (2010–2014)
    • Southwest Minzu University, China
    • Thesis: An improved encryption algorithm based on Data Encryption Standard

Experience

  • 🧑‍🔬 Researcher (2024–Present)
    • Institute for Datability Science, Osaka University
  • 🤖 AI Researcher (2018–2019)
    • vivo AI Lab
  • 🔬 Exchange Student (2016–2018)
    • Shenzhen Key Laboratory of Visual Object Detection and Recognition

Suitability for the Award

Dr. Jingcheng Ke is an exceptional candidate for the Excellence in Research Award, demonstrating a profound impact on AI and computational sciences. His Ph.D. research at National Tsing Hua University, focused on graph-based referring expression comprehension, has advanced the fields of vision-language matching and diffusion models for image and video analysis. With professional experience at Osaka University and vivo AI Lab, Dr. Ke has effectively bridged theoretical innovation and practical application. His technical expertise in Python, PyTorch, and C++, coupled with knowledge in matrix theory, stochastic processes, and topology, underscores his interdisciplinary strength. Dr. Ke’s groundbreaking contributions position him as a leader in AI research.

Professional Development

Dr. Jingcheng Ke’s professional journey spans academia and industry, specializing in artificial intelligence 🤖 and computer vision 👁️. His Ph.D. research at NTHU explored graph-based perspectives for referring expression comprehension, advancing the intersection of vision and language technologies 🌐. With hands-on experience in AI innovation at vivo AI Lab and collaboration with top-tier research labs, he has honed his expertise in diffusion models and image/video analysis 📊. Proficient in coding languages like Python and PyTorch 🖥️, he leverages advanced mathematical concepts like matrix theory and stochastic processes to push AI boundaries 🚀.

Research Focus

Dr. Ke’s research is centered on the intersection of vision and language 🤝, with a keen focus on diffusion models for image and video analysis 🎥. His work addresses challenges in vision-language matching, exploring graph-based approaches to enhance comprehension and generalization capabilities 🔍. Passionate about advancing AI technologies, he delves into areas like sparse representation and encryption algorithms 🔒. By integrating robust coding skills in Python and PyTorch with theoretical foundations, his research contributes to groundbreaking advancements in artificial intelligence and computational methodologies 🚀.

Awards and Honors

  • 🏆 Best Paper Award – Recognized for excellence in vision-language research.
  • 🥇 Graduate Fellowship – National Tsing Hua University, Taiwan.
  • 🥉 Outstanding Thesis Award – Shaanxi Normal University, China.
  • 🎖️ Research Excellence Recognition – vivo AI Lab, 2019.
  • 🌟 Academic Merit Scholarship – Southwest Minzu University, China.

Publication Highlights

  • 📄 An improvement to linear regression classification for face recognition – 26 citations, published in International Journal of Machine Learning and Cybernetics, 2019.
  • 📘 Referring Expression Comprehension via Enhanced Cross-modal Graph Attention Networks – 12 citations, published in ACM TOMM, 2022.
  • 🖼️ Face recognition based on symmetrical virtual image and original training image – 12 citations, published in Journal of Modern Optics, 2018.
  • 📊 Sample partition and grouped sparse representation – 8 citations, published in Journal of Modern Optics, 2017.
  • 🤖 A novel grouped sparse representation for face recognition – 7 citations, published in Multimedia Tools and Applications, 2019.

Mr. Congcong Ren | AI Award | Best Researcher Award

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Mr. Congcong Ren | AI Award | Best Researcher Award

Mr. Congcong Ren, Henan University of Science and Technology, China

Mr. Congcong Ren is a dedicated Master’s student in Vehicle and Traffic Engineering at Henan University of Science and Technology, with a Bachelor’s degree in Mechanical and Electrical Engineering from Henan Agricultural University. His expertise spans deep learning, algorithm development, and software testing, with practical experience in developing intelligent vehicles and defect detection systems. Mr. Ren has contributed to projects like an intelligent small car and wire rope defect detection, and he has gained hands-on experience during internships at Iflytek and Zeekr. His technical proficiency includes Python, PyTorch, and HIL test software, complemented by multiple school-level awards for innovation and entrepreneurship.

Professional Profile:

Orcid

Suitability for the Award

Mr. Congcong Ren is a highly suitable candidate for the Best Researcher Award based on the following points:

  1. Innovative Research:
    • His work on nighttime pedestrian detection and trajectory tracking addresses critical safety concerns in autonomous and intelligent vehicle systems. The use of fusion techniques combining visual and radar data showcases innovation in enhancing vehicle safety.
  2. Practical Experience:
    • His participation in significant projects like the intelligent small car and wire rope defect detection demonstrates his ability to apply theoretical knowledge to real-world challenges. These projects not only reflect technical skill but also his capability to collaborate effectively with industry partners.
  3. Academic and Professional Growth:
    • Mr. Ren’s ongoing master’s studies in artificial intelligence and traffic engineering, combined with his hands-on experience in internships at leading companies like Iflytek and Zeekr, underline his rapid professional development and adaptability in a fast-evolving field.
  4. Recognition and Skills:
    • His recognition through scholarships, awards, and publication of SCI papers highlights his academic excellence and contribution to the field. His proficiency in deep learning frameworks, coupled with practical software testing skills, positions him as a strong contender for research excellence.

Summary of Qualifications

  1. Educational Background:

    • Bachelor’s Degree in Mechanical and Electrical Engineering – Henan Agricultural University (2018-2022).
      • Major courses included Mechanical Design, Automobile Design, New Energy, and Traffic Engineering.
    • Master’s Degree (ongoing) in Vehicle and Traffic Engineering – Henan University of Science and Technology (2022-2025).
      • Major courses include Principles and Methods of Artificial Intelligence, Traffic Simulation Technology, System Control Theory, and Intelligent Network Technology.

  2. Project Experience:

    • Challenge Cup Project (2022-2023): Developed an intelligent small car with adjustable wheelbase and chassis height, integrating camera and millimeter-wave radar data for obstacle detection and avoidance.
    • Wire Rope Defect Detection Project (2023): Collaborated with Luoyang Wilrop Testing Technology Co., LTD. to improve YOLOv5s algorithm for defect detection in wire ropes using industrial camera images, meeting the project’s expected requirements.

  3. Internship Experience:

    • Iflytek (2023-2024): Tested large model voice assistant software, proficient in Android Studio and Adobe Audition, and used Python for batch pressure testing.
    • Zeekr (2024): Proficient in HIL test software (ECU-TEST, Canoe, INCA), familiar with software development processes and protocols (LIN/CAN), and involved in new energy vehicle controller testing.

  4. Technical Skills:

    • Proficient in Python, PyTorch, Matlab, Simulink, and various HIL test software.
    • Strong capabilities in deep learning, algorithm development, and software testing.
    • Recognized with school-level scholarships and awards, including the innovation and entrepreneurship competition fund.

Publication Top Notes:

1.  Study on Nighttime Pedestrian Trajectory-Tracking from the Perspective of Driving Blind Spots –  (2024).

2.  Nighttime Pedestrian Detection Based on a Fusion of Visual Information and Millimeter-Wave Radar –  (2023).

Both articles reflect his focus on advanced technologies in vehicle safety, particularly in challenging environments like nighttime driving.

Conclusion

Mr. Congcong Ren is an outstanding candidate for the Best Researcher Award, given his solid educational foundation, innovative research contributions in vehicle safety, and substantial practical experience in engineering and software testing. His ability to combine academic research with practical applications, particularly in the field of intelligent vehicle systems, makes him a deserving recipient of this award.

 

 

 

Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

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Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

Dr. Kuanxin Shen , Shenyang University of Technology , China

Kuanxin Shen, a 27-year-old PhD candidate in Control Science and Engineering at Shenyang University of Technology, China, focuses his research on 3D Gaze Estimation using neural networks and deep learning. He holds a Bachelor’s degree earned in 2021 and a Master’s degree obtained in 2024. From 2022 to 2024, Kuanxin worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His research achievements include a Chinese utility model patent, several Chinese computer software copyrights, and three Chinese invention patents related to 3D eye tracking and gaze estimation. Kuanxin has also authored a book on industrial robot simulation and published a paper in the journal Sensors. He has been recognized with the third prize in the Henan Province College Students’ Robot Innovation Competition, a first-class academic scholarship, and the Excellent Thesis Award from Liaoning Province for his master’s thesis.

Professional Profile:

Orcid

🎓Educational Background:

Kuanxin Shen earned his Bachelor’s degree in 2021 and obtained his Master’s degree in 2024. He is currently pursuing a PhD in Control Science and Engineering at Shenyang University of Technology, China.

🏢Work Experience:

From 2022 to 2024, Kuanxin Shen worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His responsibilities included driver gaze detection, skeleton landmark detection, behavior detection (such as smoking and phone usage), and the detection of driver distraction and fatigue. His tasks encompassed image processing, 3D detection, data annotation, cleaning, augmentation, neural network training, and model testing.

🏆Awards and Recognitions:

During his undergraduate studies, Kuanxin Shen won the Third Prize in the 6th Henan Province College Students’ Robot Innovation Competition. In April 2024, he was awarded the First-Class Academic Scholarship during his master’s studies. In May 2024, his master’s thesis titled “Research on the Application of Driver Gaze Estimation Technology in DMS” received the Excellent Thesis Award from Liaoning Province, China

Publication Top Notes:

Title: Model-Based 3D Gaze Estimation Using a TOF Camera

  • Journal: Sensors

 

 

Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

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Ms. Nathalia Hidalgo Leite | Artificial Neural Networks | Best Researcher Award

Ms. Nathalia Hidalgo Leite, State University of Campinas, Brazil

🎓 Nathalia Hidalgo Leite is a Ph.D. candidate in Energy Systems Planning at the State University of Campinas (Unicamp) 🇧🇷, focusing on electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, and a B.S. in Agronomic Engineering from UFSCar 🌱. As a researcher at CPTEn and CPFL Energy, and an instructor at Unicamp, she has contributed significantly to energy systems planning and education. Her international academic experience includes programs in Portugal 🇵🇹, Denmark 🇩🇰, Spain 🇪🇸, Italy 🇮🇹, and the USA 🇺🇸. Nathalia’s research interests span the economic and financial viability of energy systems, artificial neural networks, and renewable energy integration 🌞. Proficient in Portuguese, English, and Spanish, she holds numerous certifications in finance and technical skills 📊. Her achievements are recognized by multiple academic and extracurricular awards, underscoring her dedication and multifaceted talents 🌟.

🌐 Professional Profile:

Google Scholar

🎓 Educational Background

Nathalia Hidalgo Leite is currently pursuing a Ph.D. in Energy Systems Planning at the State University of Campinas (Unicamp) 🇧🇷, focusing on the economic and financial viability for electric mobility. She also holds an MBA in Value Investing from UniBTA and an M.S. in Energy Systems Planning from Unicamp, where she studied the economic viability of photovoltaic solar energy. Nathalia completed her B.S. in Agronomic Engineering at the Federal University of Sao Carlos (UFSCar), researching artificial neural networks applied to Asian soybean rust 🌱.

🏢 Professional Experience

Nathalia is an accomplished researcher and instructor. At Unicamp, she has taught courses in computer algorithms, programming, numerical calculation, and discrete mathematics. As a researcher at the Sao Paulo Center for Energy Transition Studies (CPTEn) and previously at CPFL Energy, she has made significant contributions to energy systems planning. Nathalia also worked as a Financial Planning and Analysis Specialist at Grupo JLJ and interned at Ecomark Indústria e Comércio de Fertilizantes Especiais Ltda 🌟.

🌍 International Experience

Nathalia has enriched her academic journey with several exchange programs. She spent six months at the University of Lisbon 🇵🇹 and the University of Southern Denmark 🇩🇰, three months at Universitat Politècnica de València 🇪🇸, one month at Università degli Studi di Roma La Sapienza 🇮🇹, and also attended Beverly Hills High School 🇺🇸 and Moore Elementary School in Colorado 🇺🇸 during her earlier education 📚.

📝 Research Interests

Nathalia’s research interests include the economic and financial viability of energy systems, artificial neural networks, and the integration of renewable energy sources. She is particularly focused on interdisciplinary approaches to solving complex problems in energy planning and sustainability 🌞.

🌐 Certifications and Skills

Nathalia holds numerous certifications in finance, photovoltaic systems, scientific writing, and programming. She is proficient in Portuguese (native), English (fluent), and Spanish (advanced). Her technical skills and continuous learning make her a versatile and knowledgeable professional in her field 📊.

🏆 Awards and Recognitions

Nathalia has received several awards for academic and extracurricular excellence, including the Excellence in Academic Performance award from Anglo Middle School 🇧🇷 and multiple accolades from Lincoln Junior High School 🇺🇸 for academic achievement, athletic performance, and leadership. These recognitions highlight her dedication and multifaceted talents 🌟.

Publication Top Notes:

1.  Artificial Neural Networks Applied to Plant Disease
2.  Study of Asian Soybean Rust

 

 

Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

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Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

Mr. Asif Mehmood, National university of technology, Pakistan

Asif Mehmood is a dedicated professional with a strong academic background and diverse expertise in computer sciences. Currently pursuing a PhD in Computer Sciences at COMSATS University Islamabad, Wah Campus, he holds a Master’s degree and a Bachelor’s degree in the same field. With a keen interest in machine learning and deep learning, Asif has contributed to notable publications in prestigious journals, focusing on human gait recognition and biometric techniques. His experience spans from research associate roles to lecturing positions at HITEC University Taxila, showcasing his commitment to academia and research. Asif’s technical proficiency includes programming languages such as MATLAB, JavaScript, and Java, along with extensive experience in project development and academic projects. He resides in Attock, Punjab, Pakistan, and is open to providing references upon request.

Professional Profile:

Scopus

🎓 Education:

Asif Mehmood has pursued a remarkable academic journey, demonstrating consistent excellence in his educational endeavors. He commenced his formal education with a Bachelor of Science in Computer Sciences (BSCS) from the University of Wah, spanning from 2013 to 2017, where he attained a commendable CGPA of 3.46 out of 4.0. Building upon this foundation, he pursued a Master of Science in Computer Sciences (MSCS) at COMSATS University Islamabad, Wah Campus, from 2018 to 2020, achieving an impressive CGPA of 3.84. Asif further advanced his academic pursuits by undertaking a PhD in Computer Sciences at the same institution, currently in progress, with an outstanding CGPA of 3.94 thus far.

💼 Experience:

Asif Mehmood has enriched his professional experience through roles at HITEC University Taxila. He commenced as a Research Associate in January 2022, where he actively contributed to research endeavors until June 2022. Building upon his expertise, Asif transitioned into the role of Lecturer in Computer Science at the same institution in September 2022, a position he currently holds. These roles have allowed Asif to apply his academic knowledge and research skills in a practical setting while also nurturing the next generation of computer science professionals through teaching and mentorship.

📝 Projects:

Asif Mehmood has demonstrated his proficiency in software development and research through various notable projects. Among these, he developed a Document Clustering Search Engine using Java and MySQL, showcasing his skills in both programming and database management. Additionally, his thesis focused on Prosperous Human Gait Recognition, employing Machine Learning techniques within MATLAB, highlighting his expertise in this advanced field. Furthermore, Asif has undertaken diverse academic projects encompassing Assembly Language programming, Android app development, and web development, reflecting his versatility and innovative approach to problem-solving in the realm of computer science.

Publication Top Notes:

  1. Human Gait Recognition by using Two Stream Neural Network along with Spatial and Temporal Features
    • Authors: Mehmood, A.; Amin, J.; Sharif, M.; Kadry, S.
    • Journal: Pattern Recognition Letters, 2024, 180, pp. 16–25
    • Citations: 0
  2. Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection
    • Authors: Mehmood, A.; Khan, M.A.; Sharif, M.; Riaz, N.; Ashraf, I.
    • Journal: Multimedia Tools and Applications, 2024, 83(5), pp. 14979–14999
    • Citations: 24
  3. TS2HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities
    • Authors: Khan, M.A.; Mehmood, A.; Kadry, S.; Alsubai, S.; Alqatani, A.
    • Journal: Future Generation Computer Systems, 2023, 147, pp. 292–303
    • Citations: 3
  4. Human gait analysis for osteoarthritis prediction: a framework of deep learning and kernel extreme learning machine
    • Authors: Khan, M.A.; Kadry, S.; Parwekar, P.; Khan, J.A.; Naqvi, S.R.
    • Journal: Complex and Intelligent Systems, 2023, 9(3), pp. 2665–2683
    • Citations: 23
  5. Human gait recognition: A deep learning and best feature selection framework
    • Authors: Mehmood, A.; Khan, M.A.; Tariq, U.; Mostafa, R.R.; ElZeiny, A.
    • Journal: Computers, Materials and Continua, 2021, 70(1), pp. 343–360
    • Citations: 8

 

 

Farshad Bolouri | Artificial Intelligence | Best Researcher Award

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Mr Farshad Bolouri: Artificial Intelligence | Best Researcher Award

Research Associate at Texas Tech University, United States

Farshad Bolouri is an accomplished researcher with a Master’s degree in Electrical Engineering from Texas Tech University, specializing in Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing. His research interests focus on Agricultural Robotics, Precision Farming, and Machine Learning in Digital Agriculture.

🌐 Professional Profiles:

🎓 Education : 

Farshad Bolouri, a mastermind in Electrical Engineering, graduated with a Master of Science from Texas Tech University in August ’23 🎓. His stellar GPA of 3.86 reflects his dedication to his studies, with a focus on cutting-edge fields like Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing 🌐🤖.

Prior to his master’s journey, Farshad excelled in his Bachelor’s in Computer Engineering, graduating Summa Cum Laude with a perfect GPA of 4.0 in May ’21 🏆. He added a touch of diversity with a minor in Mathematics and Computer Science, earning accolades such as the Highest Ranking Graduate from the College of Engineering and the ‘Outstanding Design Project’ award from ECE 🏅🔧.

Farshad’s academic journey is not just about grades; it’s a testament to his passion for pushing boundaries and achieving excellence in the realm of technology and engineering 🚀.

🔍 Research Interests : 

Farshad Bolouri’s research interests are a captivating blend of technology and agriculture 🌾. In the realm of Agricultural Robotics and Precision Farming, he’s delving into the development of custom robotic solutions. His focus lies on intelligent multi-sensor integration, aiming to optimize in-field plant phenotyping specifically for specialty crops 🤖🌱. Venturing into the realm of Machine Learning in Digital Agriculture, Farshad applies cutting-edge AI/ML techniques for data interpretation. His goal is to enable accurate high-throughput phenotyping and precise yield estimation, revolutionizing the way we approach modern farming practices 📊🌾. In the domain of 3D Computer Vision for Field Mapping, Farshad employs advanced techniques for accurate and real-time field mapping. By integrating 3D computer vision, he aims to enhance the precision and efficiency of agricultural decision-making processes 🌐🚜.

Research Focus:

Farshad Bolouri’s research focus spans across Agricultural Robotics and Precision Farming 🌾, as evident in his groundbreaking work on “CottonSense.” This High-Throughput Field Phenotyping System leverages intelligent multi-sensor integration for optimized cotton fruit segmentation and enumeration on edge devices, revolutionizing cotton farming practices 🤖🌱. Additionally, his contribution to improving short-term multiphase production forecasts in unconventional tight oil reservoirs showcases a keen interest in merging technology with geoenergy science and engineering ⛽🔍. Farshad’s commitment to advancing phenotyping for flower abortion in soybeans through image analysis and machine learning demonstrates a versatile expertise in the intersection of agriculture, computer vision, and AI 🌺🔬.

Publications Top Notes  :
  • CottonSense: A high-throughput field phenotyping system for cotton fruit segmentation and enumeration on edge devices