Hyung-Pil Chang | Deep Learning | Best Researcher Award

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Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University,  South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

Scopus

Orcid

Scholar

Education 🎓

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience 💼

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors 🏆

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus 🔬

Chang’s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

📝 Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

  • Wav2wav: Wave-to-Wave Voice Conversion
    C Jeong, H Chang, IC Yoo, D Yook
    Applied Sciences, 2024, 14(10), 4251.

 

  • Zero-Shot Unseen Speaker Anonymization via Voice Conversion
    HP Chang, IC Yoo, C Jeong, D Yook
    IEEE Access, 2022, 10, 130190-130199.

 

  • CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
    D Yook, G Han, HP Chang, IC Yoo
    Applied Sciences, 2024, 14(20), 9595.

 

 

 

Sahar Zeinali | Autonomous systems| Best Researcher Award

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Dr. Sahar Zeinali| Autonomous systems | Best Researcher Award

Dr, Institute for Electrical Engineering in Medicine, University of Luebeck, Germany

👩‍🔬 With a Ph.D. in Control Systems from Sharif University of Technology and experience as a Researcher in Automotive Systems at the University of Lübeck, Germany, I specialize in developing driving assistance systems for autonomous vehicles. Collaborating with industry leaders like ZF Group and Infineon Technologies, my work focuses on model-based and AI-based methods to enhance energy efficiency, driving comfort, and safety. Proficient in MATLAB, Simulink, and Python, I have a strong background in software architecture design and algorithm implementation. Recognized for academic excellence and ranked among top university entrants, I bring expertise in control engineering and a dedication to innovation in automotive technology.🌟

Profile

Scopus

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💼Professional Experience

Researcher in Automotive Systems University of Lübeck, Lübeck, Germany 2022–Present Collaborated with ZF Group and Infineon Technologies on the EEmotion project. Developed driving assistance systems for autonomous vehicles using model-based and AI-based methods. Enhanced energy-efficiency, driving comfort, and safety. Created software and system simulation requirements. Designed software architecture and interfaces for integration and evaluation purposes. Implemented and validated algorithms in the simulation environment. Conducted Software-in-the-loop (SIL) testing. Control Engineer (Part-time) Namvaran Consulting Company, Tehran, Iran 2018–2019

🎓Education

Ph.D. in Control Systems Sharif University of Technology, Tehran, Iran 2016–2021 Visiting Researcher in Control Systems Universitat Autònoma de Barcelona, Barcelona, Spain 2019–2020 M.Sc. in Modeling, Simulation and Control Sharif University of Technology, Tehran, Iran 2013–2015 B.Sc. in Chemical Engineering Sharif University of Technology, Tehran, Iran 2009–2013 Notable Projects Design of Interaction-Aware Driving Assistance Systems for Autonomous Vehicles University of Lübeck, Lübeck, Germany 2023–Present

🖥️Skills

  • Software: MATLAB & Simulink, IPG CarMaker, Comsol Multiphysics
  • Python Packages & Libraries: TensorFlow, Keras, Scikit-learn, Gymnasium
  • Programming Language: Python, MATLAB, C++
  • Agile Methodology: Scrum
  • Development Tools: Git
  • Typesetting: LaTeX, Microsoft Office
  • Operating System: Windows, macOS

🏆Honors

Recognized for studying at Sharif University of Technology, Iran’s top university. Ranked 3rd out of over 2000 participants in the Ph.D. Entrance Exam in Iran, 2015. Directly admitted to the M.Sc. program as an Exceptional Talented Student, top 10% by GPA, at Sharif University of Technology, Tehran, Iran, 2013. Ranked 500th among more than 350,000 university entrance participants in Iran, 2009. Member of Iran’s National Elites Foundation. Admitted to Exceptional Talents Schools, 2002–2009, Tabriz, Iran.

Publications Top Notes 📝

  1. S. Zeinali, M. Fleps-Dezasse, J. King, and G. Schildbach, “Design of a utility-based lane change decision making algorithm and a motion planning for energy-efficient highway driving,” Control Engineering Practice, 146, 105881, 2024.

 

  1. X. Zhang, S. Zeinali, and G. Schildbach, “Interaction-aware traffic prediction and scenario-based model predictive control for autonomous vehicles on highways,” European Control Conference (ECC), 2024.

 

  1. X. Zhang, S. Zeinali, and G. Schildbach, “Interaction-aware traffic prediction and scenario-based model predictive control for autonomous vehicles on highways,” Accepted in IEEE Transactions on Control Systems Technology, 2024.

 

  1. S. Zeinali, M. Shahrokhi, and A. Pishro, “Observer-based controller for treatment of hepatitis C infection using fractional order model,” Mathematical Methods in the Applied Sciences, 45(17), 10689-10709, 2022.

 

  1. S. Zeinali and M. Shahrokhi, “Observer-based singularity-free nonlinear controller for uncertain systems subject to input saturation,” European Journal of Control, 52, 49-58, 2020.

 

  1. S. Zeinali, M. Shahrokhi, and A. Ibeas, “Observer-based impulsive controller design for treatment of hepatitis C disease,” Industrial & Engineering Chemistry Research, 59(43), 19370-19382, 2020.

 

  1. S. Zeinali and M. Shahrokhi, “Adaptive control strategy for treatment of hepatitis C infection,” Industrial & Engineering Chemistry Research, 58(33), 15262-15270, 2019.

 

 

Ming Xu | Spatio-Temporal Data Mining | Best Researcher Award

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Assoc Prof Dr. Ming Xu | Spatio-Temporal Data Mining |Best Researcher Award

👨‍🏫Profile Summary

Ming Xu is an accomplished Associate Professor at Liaoning Technical University, specializing in computer science, particularly in transportation systems. With a Ph.D. from Beijing University of Posts and Telecommunications and a wealth of academic and research experience, Dr. Xu has made significant contributions to the field. He has authored numerous publications in prestigious journals and has been recognized with awards such as the World Artificial Intelligence Conference Youth Outstanding Paper Award. Dr. Xu’s expertise lies in learning to rank nodes in road networks, anomaly detection, traffic signal control, and traffic flow prediction using advanced data mining and deep learning techniques

🌐 Professional Profiles

 

  1. Orcid  Profile

📚Education 

PhD in Computer Science Beijing University of Posts and Telecommunications Duration: September 2010 – July 2015.  Master in Computer Science Shenyang Ligong University Duration: September 2005 – April 2008. Bachelor in Computer Science Liaoning Technical University Duration: September 1999 – 2003

👨‍💼Professional Service

  • Guest editor of special issue of Journal of Advanced Transportation (SCI)
  • Reviewer of IEEE Trans. on ITS\Physica A\ITSC

🏆 Awards

  • World Artificial Intelligence Conference Youth Outstanding Paper Award (2020)

🎓Academic experience

Associate Professor Software College, Liaoning Technical University Duration: October 2020 – Present. Postdoctoral position Tsinghua University Duration: February 2016 – February 2019

 

📚Top Noted Publication

    1. Title: MGL2Rank: Learning to Rank the Importance of Nodes in Road Networks Based on Multi-Graph Fusion
      • Authors: Ming Xu, Jing Zhang
      • Journal: Information Sciences
      • Status: In press
      • DOI: 10.1016/j.ins.2024.120472

     

    1. Title: Discovery of Critical Nodes in Road Networks through Mining from Vehicle Trajectories
      • Authors: Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2018
      • Volume: 20
      • Issue: 2
      • Pages: 583-593
      • Award: World Artificial Intelligence Conference Youth Outstanding Paper Award
      • Links: Award, Report

     

    1. Title: Anomaly Detection in Road Networks using Sliding-Window Tensor Factorization
      • Authors: Ming Xu, Jianping Wu, Haohan Wang, Mengxin Cao
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2019
      • Volume: 20
      • Issue: 12
      • Pages: 4704-4713

     

    1. Title: Network-wide Traffic Signal Control based on Discovery of Critical Nodes and Deep Reinforcement Learning
      • Authors: Ming Xu, Jianping Wu, Ling Huang, Rui Zhou, Tian Wang, Dongmei Hu
      • Journal: Journal of Intelligent Transportation Systems
      • Year: 2020
      • Volume: 24
      • Issue: 1
      • Pages: 1-10

     

    1. Title: Traffic Flow Prediction with Rainfall Impact Using A Deep Learning Method
      • Authors: Yuhan Jia, Jianping Wu, Ming Xu
      • Journal: Journal of Advanced Transportation
      • Year: 2017

     

    1. Title: Charging Pile Siting Recommendations via the Fusion of Points of Interest and Vehicle Trajectories
      • Authors: Yuan Kong, Jianping Wu, Ming Xu, Kezhen Hu
      • Journal: China Communications
      • Year: 2017
      • Volume: 14
      • Issue: 11
      • Pages: 29-38

     

    1. Title: Rumor propagation dynamic model based on evolutionary game and anti-rumor
      • Authors: Yunpeng Xiao, Diqiang Chen, Shihong Wei, Qian Li, Haohan Wang, Ming Xu
      • Journal: Nonlinear Dynamics
      • Year: 2019
      • Volume: 95
      • Pages: 523-539

     

    1. Title: Leveraging longitudinal driving behaviour data with data mining techniques for driving style analysis
      • Authors: Geqi Qi, Yiman Du, Jianping Wu, Ming Xu
      • Journal: IET intelligent transport systems
      • Year: 2015
      • Volume: 9
      • Issue: 8
      • Pages: 792-801

     

    1. Title: Emission pattern mining based on taxi trajectory data in Beijing
      • Authors: Tingting Li, Jianping Wu, Anrong Dang, Lyuchao Liao, Ming Xu
      • Journal: Journal of cleaner production
      • Year: 2019
      • Volume: 206
      • Pages: 688-700

     

    1. Title: 3-HBP: A three-level hidden Bayesian link prediction model in social networks
      • Authors: Yunpeng Xiao, Xixi Li, Haohan Wang, Ming Xu, Yanbing Liu
      • Journal: IEEE Transactions on Computational Social Systems
      • Year: 2018
      • Volume: 5
      • Issue: 2
      • Pages: 430-443

 

Farah Jemili | Cybersécurité

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Assist Prof Dr Farah Jemili: Leading Researcher in Cybersécurité

Assist Prof Dr Farah Jemili at University of Sousse Tunisia.

🎉🏆Congratulations, Assist Prof Dr Farah Jemili, on winning the esteemed Women Researcher Award from Young scientist Awards! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done 🌟

👨‍🏫  Farah Jemili, an Professor at the  University of Sousse, Tunisia, stands as a distinguished academic and researcher in the Computer Science. Holding a Ph.D Assistant Professor research in artificial intelligence &Big Data Analysis at MARS lab.,IsITCom, University of Sousse, Tunisia . their professional journey exemplifies dedication and expertise. 📚

Professional Profile

Academic Qualifications

Ph.D, Eng., Assistant Professor, Researcher in Artificial Intelligence & Big Data Analysis at MARS Lab , ISITCom, University of Sousse, Tunisia

💼Employment :

Assistant Professor(FSB BIZERTE) 2004 to 2010|Employment

Farah Jemili’s citation metrics and indices from Google Scholar are as follows:

📊 Citation Metrics (Google Scholar):

  • Cited by: All – 398, Since 2018 – 286
  • h-index: All – 11, Since 2018 – 9
  • i10-index : All -11 Since 2018 -9
Publications

32 Documents

📚Top Noted Publications (Journals)

A framework for an adaptive intrusion detection system using Bayesian network  Published in 2007/5/23 Cited by 115

Distributed deep learning approach for intrusion detection system in industrial control systems based on big data technique and transfer learning Published online: 25 Jul 2023.

A framework for an adaptive intrusion detection system using Bayesian network

Using MongoDB databases for training and combining intrusion detection datasets Published in 2018 Cited by 11.

A survey of attacks in mobile ad hoc networks

Anomaly-based behavioral detection in mobile Ad-Hoc networks

Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques

Distributed Architecture of an Intrusion Detection System in Industrial Control Systems Published in 2022/9/21 Cited by 8

Neuro-fuzzy and genetic-fuzzy based approaches in intrusion detection: Comparative study Published in 2017 cited by 5

OuajdiKorbaa.” Neuro-fuzzy and genetic-fuzzy based approaches in intrusion detection: Comparative study.” Software, Telecommunications and Computer Networks (SoftCOM) Published in 2017 Cited by 5