Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

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Mr. Ali Raza | Computer Science and Artificial Intelligence | Young Scientist Award

lecturer The University Of Lahore Pakistan

Ali Raza is a passionate researcher, educator, and developer specializing in computer science. With a strong academic background and extensive experience in machine learning, deep learning, and computer vision, he has contributed significantly to cutting-edge research. Currently serving as a Lecturer at the University of Lahore, Ali has also worked as a Visiting Lecturer at KFUEIT and a Full Stack Python Developer in the software industry. His expertise lies in AI-driven solutions, research writing, and technological advancements in artificial intelligence.

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Education 🎓

  • MS Computer Science (2021-2023) | Khwaja Fareed University of Engineering and Information Technology (KFUEIT), CGPA: 3.93
  • BS Computer Science (2017-2021) | KFUEIT, CGPA: 3.47

Professional Experience 💼

  • Lecturer | University of Lahore (2024 – Present)
  • Visiting Lecturer | KFUEIT (2022 – 2023)
  • Full Stack Python Developer | BuiltinSoft Software Industry (2020 – 2021)

Research Interests 📈

Ali Raza’s research focuses on artificial intelligence, machine learning, deep learning, and computer vision. He is particularly interested in developing AI-driven solutions for medical imaging, agricultural applications, and energy consumption prediction. His contributions span multiple domains, showcasing his ability to integrate AI with real-world challenges.

Awards & Certifications 🏆

  • Best Researcher Award | ScienceFather (26/06/2024)
  • Use of Generative AI in Higher Education | Punjab Higher Education Commission
  • Machine Learning with Python (ML0101EN) | IBM Developer Skills Network

Publications Top Notes: 📚

Ali Raza has authored 61 research publications in reputed journals with high impact factors. Below are some of his recent publications:

“Novel Transfer Learning Approach for Hand Drawn Mathematical Geometric Shapes Classification” (2025) PeerJ Computer Science (IF: 3.8)

“Citrus Diseases Detection Using Innovative Deep Learning Approach and Hybrid Meta-Heuristic” (2025) PLOS ONE (IF: 2.9)

“Novel Deep Neural Network Architecture Fusion for Energy Consumption Prediction” (2025) PLOS ONE (IF: 2.9)

“Novel Transfer Learning Based Bone Fracture Detection Using Radiographic Images” (2025) BMC Medical Imaging (IF: 2.9)

“Novel Transfer Learning Approach for Detecting Infected and Healthy Maize Crops” (2025) Food Science & Nutrition (IF: 3.5)

“BdSentiLLM: A Novel LLM Approach to Sentiment Analysis of Product Reviews” (2024) IEEE Access (IF: 3.4)

“An Innovative Artificial Neural Network Model for Smart Crop Prediction” (2024) PeerJ Computer Science (IF: 3.8)

“Enhanced Interpretable Thyroid Disease Diagnosis Using Synthetic Oversampling and Machine Learning” (2024) BMC Medical Informatics (IF: 3.3)

“Diagnosing Epileptic Seizures Using EEG Data and Independent Components” (2024) Digital Health (IF: 3.7)

“A Novel Meta Learning Based Approach for Thyroid Syndrome Diagnosis” (2024) PLOS ONE (IF: 2.9)

 

Zihan Li | Artificial Neural Networks | Best Researcher Award

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Mr. Zihan Li | Artificial Neural Networks | Best Researcher Award

student College of information Science and Technology, Donghua University China

Li Zihan, a 24-year-old aspiring engineer from Jingdezhen, Jiangxi, is a Master’s student in Information and Communication Engineering at Donghua University, Shanghai. With a strong academic record and hands-on experience in communication systems, autonomous driving, and resource allocation strategies, Li showcases a passion for innovation and excellence in technology.

Profile

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Education 🎓

  • Master’s Program (2022 – Present): Donghua University, Shanghai (211/Double First-Class) in Information and Communication Engineering. Excelling in academics, Li ranks in the top 8% of the class.
  • Undergraduate Degree (2018 – 2022): Donghua University, Shanghai, in Communication Engineering. Ranked in the top 6%, with exceptional grades in core courses like Computer Communication Network (99) and Wireless Mobile Communications (94).

Experience 🛠️

Internship at Shanghai NIO Co., Ltd. (2023.02 – 2023.06):
Worked as a Test Intern in the Intelligent Cockpit Function Test Group, specializing in automated assembly line platforms and vehicle-machine testing. Key contributions included writing Python scripts, conducting functional tests, and maintaining Git repositories to support bug identification and resolution.

Research Interest 🔬

Li’s research focuses on resource allocation strategies for the Internet of Vehicles, integrating sensing and communication to optimize V2X systems. Li employs MATLAB simulations to evaluate parameters like bandwidth and modulation, leveraging advanced techniques such as Q-learning for adaptive conflict resolution.

Awards 🏅

  • “TI” Cup Shanghai College Student Electronic Design Competition (Provincial Second Prize) – 2020.09
  • National Inspirational Scholarship
  • Donghua University Scholarship
  • Xingze Social Scholarship
  • Postgraduate Academic Scholarship

Publications Top Notes: 📚

Research on Resource Allocation Strategy of Side-chain for IoV Integrated with Sensing and Communication

Published in November 2023

Published by [Journal of Vehicle Networking and Communications]

Cited by: 15 articles

Performance Evaluation of SB-SPS Algorithm in Real-world Connected Vehicle Systems

Published in January 2024

Published by [IEEE Transactions on Vehicular Technology]

Cited by: 10 articles