Mr. Liang Peng | Tracking | Best Researcher Award

Mr. Liang Peng, Yangtze University, China

Peng Liang is a dedicated researcher in the field of computer vision and deep learning, currently pursuing a Master’s degree through a joint training program between Yangtze University and the Institute of Software at the Chinese Academy of Sciences. He holds a Bachelor’s degree in Software Engineering from Fuyang Normal University. His research focuses on object tracking, detection, and medical image analysis. Peng has led several high-impact projects, including VastTrack—an industry-leading visual object tracking dataset accepted at NeurIPS 2024—and developed advanced algorithms for product detection and video text spotting. He has interned at Pengcheng Laboratory and the Institute of Software, contributing to algorithm migration and medical imaging research. Proficient in Python, Java, PyTorch, and Linux, he has authored multiple software copyrights and received numerous academic and technical awards, including scholarships, innovation project leadership roles, and national competition prizes. Peng also shares his knowledge widely through his blog, which has gained over 500,000 views. He is recognized for his strong problem-solving ability, technical expertise, and leadership in collaborative research environments.

Professional Profile:

GOOGLE SCHOLAR

🎓 Education

Master’s Degree (Joint Training Program)
Yangtze University & Institute of Software, Chinese Academy of Sciences (Sep 2022 – Jun 2025)
- GPA: 3.43 / 4.0
- Research Interests: Deep Learning, Computer Vision, Object Tracking, Object Detection
- Relevant Courses: Data Structures (90), Algorithm Design (96), Data Mining (97), Operating Systems (90), Design Patterns (97), Probability Theory (95), UML Modeling (98)
Bachelor’s Degree in Software Engineering
Fuyang Normal University (Sep 2017 – Jun 2021)

💼 Work Experience

Algorithm Intern — Pengcheng Laboratory (May 2022 – Dec 2022)
- Migrated ByteTrack (multi-object tracking algorithm) from PyTorch to MindSpore framework
- Reconstructed and optimized algorithm to maintain performance and accuracy
- Shared code/documentation on GitHub for cross-framework migration
Algorithm Intern — Institute of Software, Chinese Academy of Sciences (Sep 2020 – Sep 2023)
- Collaborated on medical imaging project with Fuwai Hospital
- Developed 3D U-Net ventricular segmentation model for cardiac CT sequences
- Designed abnormal ventricular diagnosis algorithm with clinically validated accuracy

🏆 Achievements & Awards

2024 University Third Prize Scholarship
2023 University Second Prize Scholarship
2023 MindSpore Active Contributor
2022-2023 First author on three software copyright applications
2021 “Three Good Student” Award
2020 First Prize Scholarship & National Encouragement Scholarship, “Three Good Student”
2019 First Prize, Anhui Province Big Data and AI Application Competition
2019 Second Prize, Anhui Province Blue Bridge Cup Java Group
2019 Third Prize, Anhui Province AI Solution Design, Chinese University Student Design Competition
2019 Third Prize, Anhui Province Big Data Application, Chinese University Computer Design Competition
2019 “Three Good Student” Honor & First Prize Scholarship
2018 Second Prize, Anhui Province Big Data and AI Application Competition

Publication Top Notes:

Vasttrack: Vast category visual object tracking

CITED:15

Mr. Ioannis Daramouskas, Computer Technology Institute and Press “Diophantus”, Greece.

Ioannis Daramouskas, a Greek national born on July 30, 1989, is a Research Software Engineer with extensive experience in unmanned aerial systems and localization technologies. He holds a position at the Applied Mechanics Lab, Mechanical Engineering & Aeronautics Department, University of Patras, Greece, where he has contributed to various high-profile projects. His work includes the “EuroSWARM” project, focused on unmanned heterogeneous swarm systems for the European Defense Agency, and the “EuroDRONE” project, aimed at developing U-Space functionalities. Additionally, he is involved in the Computer Technology Institute and Press “Diophantus” project, designing wearable devices for locating and rescuing individuals. Currently, he is engaged in the Metropolis 2 project, addressing air traffic management in urban environments. Daramouskas’s expertise spans task allocation, autonomous systems, sensor fusion, and localization algorithms, with a strong focus on real-time tracking and integration.

Summary of Suitability:

Ioannis Daramouskas has demonstrated significant contributions in the fields of unmanned aerial systems, localization technologies, and real-time tracking. His work on innovative UAV technologies, particularly in swarm systems and urban air traffic management, highlights his expertise and impact in these areas. His involvement in prominent projects like EuroSWARM and Metropolis 2, along with his extensive publication record, underscores his suitability for the Best Researcher Award.

Education

[B.Sc. in Computer Engineering and Informatics]
University of Patras, Greece
Graduated: 2011
[M.Sc. in Computer Engineering and Informatics]
University of Patras, Greece
Graduated: 2014

Work Experience

Research Software Engineer
Applied Mechanics Lab, Mechanical Engineering & Aeronautics Department, University of Patras
Patra, Greece
31/08/2017 – 22/02/2018
- Research Topic: Unmanned Heterogeneous Swarm of Sensor Platforms (EuroSWARM Project)
- Responsibilities: Task Allocation, Autonomous Flights, Multi-agent System Architecture, Sensor Fusion, Real-time Tracking, Integration, Demo Preparation, and Testing.
- Frameworks and Libraries: ROS, mavros, bebop_autonomy, OpenCV
- Project Link: EuroSWARM Project
Research Software Engineer
Applied Mechanics Lab, Mechanical Engineering & Aeronautics Department, University of Patras
Patra, Greece
31/05/2019 – 29/04/2020
- Research Topic: U-Space Functionalities (EuroDRONE Project)
- Responsibilities: Demo Preparation, Testing, Integration, FLARM Messages Interpretation for Sense and Avoid Subsystem.
- Frameworks and Libraries: Dronekit, DroNav, FLARM
- Project Link: EuroDRONE Project