Yongseok Son | Parallel and distributed systems | Best Researcher Award

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Assoc. Prof. Dr. Yongseok Son | Parallel and distributed systems | Best Researcher Award

Associate Professor at Chung-Ang University,Ā  South Korea

Yongseok Son is an Associate Professor at Chung-Ang University’s Department of Computer Science and Engineering and leads the Systems and Storage Laboratory.Ā  He earned a Ph.D. in Electrical Engineering and Computer Science from Seoul National University, with research focused on optimizing file systems for high-performance storage.Ā  Before his academic career, Dr. Son gained industry experience, including an internship at Sindoh R&D Center.Ā  Known for his expertise in system architecture, he previously held a postdoctoral position at the University of Illinois at Urbana-Champaign.Ā  As a skilled educator, he lectures on operating systems, distributed systems, and computer architecture.Ā  Dr. Son has contributed significantly to innovations in operating and storage systems, aiming to enhance modern computing performance and reliability.Ā  His dedication to the field has earned him recognition as a leading scholar and mentor.

 

Profile

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Education šŸŽ“

Ā Ph.D. in Electrical Engineering and Computer Science, Seoul National University, Feb 2018 ā€” Dissertation on optimizing file systems for high-performance storage, advised by Heon Young Yeom.Ā  Postdoctoral Research Associate, University of Illinois at Urbana-Champaign (UIUC), Jan 2018 ā€“ Aug 2018 ā€” Focused on advanced computer systems, under advisor Nam Sung Kim.Ā  M.S. in Intelligent Convergence Systems, Seoul National University, Aug 2012 ā€” Specialized in priority boosting and load balancing for Android smartphones, advised by Seongsoo Hong.Ā  B.S. in Information and Computer Engineering, Ajou University, Aug 2010, graduating magna cum laude.

Experience šŸ§‘ā€šŸ«

Associate Professor, Department of Computer Science and Engineering, Chung-Ang University (Sep 2024 ā€“ Present). Ā Assistant Professor, same department, Chung-Ang University (Sep 2018 ā€“ 2024).
Part-time Instructor in Operating Systems, Sookmyung Womenā€™s University, Korea (Sep 2015 ā€“ Jan 2016). Ā Internship at Sindoh R&D Center, working on Linux device driver development (Dec 2010 ā€“ Mar 2011).
Dr. Son has led courses in operating systems, distributed systems, and computer architecture. His teaching and professional roles emphasize practical and innovative computing solutions.

Awards and Honors šŸ†

Magna Cum Laude upon graduation with a B.S. from Ajou University. Received accolades for contributing to advancements in computing systems. Recognition for excellence in postdoctoral research at the University of Illinois at Urbana-Champaign. Prestigious internships and impactful collaborations throughout his career. Acknowledged for mentoring students and promoting academic excellence in the field of computer engineering. Awards for significant contributions to research on file systems and emerging technologies.

Research Focus šŸ”

Ā Dr. Son specializes in enhancing operating systems and storage solutions for modern hardware. His research includes designing Linux task schedulers, improving I/O subsystems, and optimizing page cache and memory subsystems. Focused on parallel and distributed systems, he works on lock-free data structures and efficient load balancing. Ā Dedicated to developing advanced file systems for distributed and parallel environments. Ā His work also encompasses improving database storage engines, aligning with new hardware capabilities. Dr. Sonā€™s research bridges theoretical insights and practical applications, striving for performance and scalability in computing systems.

Conclusion

Associate Professor Yongseok Sonā€™s dedication to advancing the fields of operating systems, file storage systems, and distributed computing through his research, teaching, and leadership makes him a strong candidate for the Best Researcher Award. His contributions to optimizing computing performance for emerging hardware reflect a high level of expertise and commitment. By enhancing international collaborations and securing larger-scale funding, he could further elevate his research profile and broaden the impact of his work on a global scale.

Publications šŸ“š

Title: Sequentialized Virtual File System: A Virtual File System Enabling Address Sequentialization for Flash-Based Solid State Drives
Year: 2024
Authors: Inhwi Hwang, Sunggon Kim, Hyeonsang Eom, Yongseok Son

 

Title: Comprehensive survey of sensor data verification in internet of things
Year: 2023
Authors: LA Nguyen, PT Kiet, S Lee, H Yeo, Y Son

 

Title: An efficient and parallel file defragmentation scheme for flash-based SSDs
Year: 2022
Authors: G Zhu, J Lee, Y Son

 

 

Title: FlexGPU: A flexible and efficient scheduler for GPU sharing systems
Year: 2020
Authors: Q Chen, H Lee, HY Yeom, Y Son

 

Title: z-READ: Towards Efficient and Transparent Zero-Copy Read
Year: 2019
Authors: J Park, C Min, HY Yeom, Y Son

 

Title: A low-latency storage stack for fast storage devices
Year: 2017
Authors: Y Son, NY Song, HY Yeom, H Han

 

Title: A2FL: autonomous and adaptive file layout in HPC through real-time access pattern analysis
Year: 2024
Authors: DK Sung, Y Son, A Sim, K Wu, S Byna, H Tang, H Eom, C Kim, S Kim

 

Title: ScaleCache: A Scalable Page Cache for Multiple Solid-State Drives
Year: 2024
Authors: KT Pham, S Cho, S Lee, LA Nguyen, H Yeo, I Jeong, S Lee, NS Kim

 

Title: UAV-Satellite Integration for Communication System: Potential Applications and Key Challenges
Year: 2023
Authors: QT Do, AT Tran, DS Lakew, H Kim, Y Son, HT Lee, J Paek, S Cho

 

 

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,Ā  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

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Education šŸŽ“

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 šŸ’¼

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 šŸ†

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 šŸ”¬

Changā€™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.

šŸ“ 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.

 

 

 

Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

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Assoc Prof Dr. Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

Assoc Prof Dr.Ā  Ali Bagheri Bardi Persian Gulf University Iran

Ali Bagheri Bardi is an accomplished mathematician with a Ph.D. from Kharazmi University, specializing in pure and applied mathematics, including functional analysis, Fourier analysis, and algebraic signal processing. He has held prestigious positions, such as a postdoctoral researcher and visiting professor at the University of Montenegro and has a significant teaching career at Persian Gulf University. Recognized for his contributions, he has received awards like the Abbas Kermani Mathematics Award. His research focuses on operator algebras, noncommutative harmonic analysis, and graph signal processing, with numerous publications in esteemed journals. He has also mentored Ph.D. students and delivered invited talks at international conferences.

Publication Profile

Scholar

Evaluation for Best Researcher Award: Ali Bagheri Bardi

Strengths for the Award:

  1. Extensive Academic and Research Background: Dr. Ali Bagheri Bardi has an impressive academic background with a Ph.D. in Mathematics from Kharazmi University and significant experience in both teaching and research at renowned institutions, including the University of Montenegro and Persian Gulf University.
  2. Diverse Research Contributions: His research spans a broad spectrum of mathematical disciplines, including pure mathematics, functional analysis, Fourier analysis, von Neumann algebras, and applied mathematics, specifically in algebraic signal processing and graph signal processing.
  3. Publication Record: Dr. Bardi has a strong publication record, with numerous papers in prestigious journals such as Signal Processing, Digital Signal Processing, and Linear Algebra and its Applications. His work is recognized for its depth and contribution to the fields of functional analysis and signal processing.
  4. International Recognition: Dr. Bardi has been invited to speak at various international conferences and universities, showcasing his expertise on a global platform. This recognition by the international community is a testament to the impact and significance of his research.
  5. Mentorship: He has supervised several Ph.D. students, guiding them through complex mathematical research, which reflects his dedication to fostering the next generation of researchers.
  6. Awards and Honors: His receipt of the Abbas Kermani Mathematics Award and an Honorable Mention in the International Mathematics Competition further highlight his excellence in research and mathematical problem-solving.

Areas for Improvement:

  1. Interdisciplinary Collaborations: While his work is strong within the realm of pure and applied mathematics, Dr. Bardi could enhance his research profile by engaging in more interdisciplinary collaborations that connect mathematics with other fields, such as computer science or engineering.
  2. Broader Impact and Outreach: Increasing public engagement through popular science articles or public lectures could help disseminate his work to a wider audience and elevate his influence beyond the academic community.
  3. Securing Larger Grants: Pursuing and securing larger-scale research grants, particularly those that support collaborative, multi-institutional projects, could further bolster his standing as a leading researcher.

šŸŽ“ Education

2004ā€“2008Ā  Ph.D, Kharazmi University. 2002ā€“2004Ā  M.Sc, Kharazmi University. 1998ā€“2002 B.Sc, Shahid Beheshti University.

šŸŽÆ Interests

Pure Math. & Functional Analysis – Fourier Analysis – von Neumann Algebras. Applied Math. & Algebraic Signal Processing – Graph Signal Processing

šŸ’¼ Working Experience

2023ā€“2024Ā  Postdoctoral Position, University of Montenegro, Electrical Engineering Department. 2022ā€“2023Ā  Visiting Professor, University of Montenegro, Electrical Engineering Department. 2020ā€“2022Ā  Associate Professor, Persian Gulf University. 2010ā€“2020Ā  Assistant Professor, Persian Gulf University.

šŸ† Awards

2000Ā  Honorable Mention, International Mathematics Competition for University Students (University College London). 2021 Abbas Kermani Mathematics Award (Shiraz University).

šŸŽ¤ Invited Talks and Conferences

2009 šŸ‡ŖšŸ‡ø Infinite Matrices over Completely Counteractive Banach Algebras, Madrid University, Spain. 2010 šŸ‡øšŸ‡Ŗ Operator-Valued Convolution Algebras, Chalmers University, Sweden. 2011 šŸ‡ÆšŸ‡µ Operator Algebras and their Applications, RIMS, Kyoto University, Japan. 2011 šŸ‡µšŸ‡± Operator Algebras and Quantum Groups, Banach Center, Poland. 2011 šŸ‡±šŸ‡ŗ Noncommutative Harmonic Analysis and Representation Theory, Luxembourg University, Luxembourg. 2023 šŸ‡«šŸ‡· Noncommutative Analysis on Groups and Quantum Groups, UniversitĆ© de Bourgogne Franche-ComtĆ©, France.

šŸŽ“ Ph.D. Students

Current Student
Fatemeh Zarei, Spectral Theory of Polynomial Transforms and Fourier Transform on Graphs
2021. Ā S. Javani, Some Analysis of K-Frames and its Dual
2019 . A. Elyaspour, An Algebraic Approach to the Structure Theory of B(H)
2018. Ā M. Khosheghbal, An Approach to Operator-Valued Measurable Functions

Publications

  • Wold-type decompositions in BaerāŽ-rings
    GA Bagheri-Bardi, A Elyaspour, GH Esslamzadeh
    2018
  • The role of algebraic structure in the invariant subspace theory
    GA Bagheri-Bardi, A Elyaspour, GH Esslamzadeh
    2019
  • Operator-valued measurable functions
    GA Bagheri-Bardi
    2015
  • Operator-valued convolution algebras
    GA Bagheri-Bardi, AR Medghalchi, N Spronk
    2010
  • Numerical solutions of a mathematical model of planktonā€“oxygen dynamics using a meshless method
    A Shirzadi, S Ghayedi, M Safarpoor, G Bagheri Bardi
    2018
  • Borel structures coming from various topologies on
    GA Bagheri-Bardi, M Khosheghbal-Ghorabayi
    2017
  • Zero-padding on Connected Directed Acyclic Graphs for Spectral Processing
    L Stanković, M Daković, M Brajović, I Stanković, AB Bardi
    2023
  • Vector-valued measurable functions
    GA Bagheri-Bardi
    2019
  • An extension of Riesz dual pairing in non-commutative functional analysis
    GA Bagheri-Bardi, A Elyaspour, S Javani, M Khosheghbal-Ghorabayi
    2018
  • Fourier Analysis of Signals on Directed Acyclic Graphs (DAG) Using Graph Zero-Padding
    L Stankovic, M Dakovic, AB Bardi, M Brajovic, I Stankovic
    2023
  • Eigenvalues of Symmetric Non-normalized Discrete Trigonometric Transforms
    AB Bardi, M Dakovic, T Yazdanpanah, L Stankovic
    2023
  • The Schur decomposition of discrete Sine and Cosine transformations of type IV
    Ali Bagheri Bardi, Milos Dakovic, Taher Yazdanpanah, Fatemeh Zarei, Ljubisa Stankovic
    2023
  • Wold-type decomposition of semigroups of isometries in BaerāŽ-rings
    GA Bagheri-Bardi, GH Esslamzadeh, M Sabzevari
    2021
  • Four Algorithms to Produce Approximate K-Dual Frames
    S Javani, GA Bagheri Bardi, F Takhteh
    2020

Conclusion:

The conclusion for the professional and academic profile of Ali Bagheri Bardi highlights his extensive expertise in both pure and applied mathematics, with a particular focus on functional analysis, operator algebras, and algebraic signal processing. Throughout his career, he has held prominent academic positions, contributed significantly to mathematical research, and received recognition for his scholarly achievements, including prestigious awards and invitations to international conferences. His research has led to numerous publications in high-impact journals, and his work continues to influence various fields, particularly in signal processing and noncommutative analysis. His dedication to mentoring Ph.D. students further underscores his commitment to advancing mathematical sciences.

 

Anuradha Laishram | Computer vision | Best Researcher Award

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Dr. Anuradha Laishram | Computer vision | Best Researcher Award

Doctorate at National Institute of Technology Manipur, India

Dr. Anuradha Laishram is an accomplished Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology Manipur. With a Ph.D. in Computer Science from the same institution, her research has significantly contributed to the fields of medical image processing and deep learning. She holds a Master’s degree from UVCE, Bangalore University, and a Bachelor’s degree from Visvesvaraya Technological University, Belgaum. Dr. Laishram is known for her expertise in machine learning and her active involvement in impactful research projects, including mHealth solutions and AI translation software. Her dedication to teaching and research makes her a prominent figure in the academic community.

profile:

Scopus Profile

šŸŽ“ Education

  • Ph.D. in Computer Science and Engineering
    • University: National Institute of Technology Manipur
    • Year of Award: 2022
    • Thesis Title: Automatic Classification of Kidney Diseases and Oral Types and Anomalies using Ultrasound Images and Orthopantomogram Radiography Images based on Hybrid Neural Networks and Deep Learning
  • Master of Engineering in Computer Science and Engineering
    • University: UVCE, Bangalore University
    • Year of Passing: 2011
    • Percentage: 79.8%
    • Project: Minimizing Delay and Maximizing Lifetime of Wireless Sensor Network
  • Bachelor of Engineering in Computer Science and Engineering
    • University: Visvesvaraya Technological University, Belgaum
    • Year of Passing: 2008
    • Percentage: 64.5%
  • Other Educational Achievement:
    • Qualified GATE Exam 2008 with an All India Rank of 474 and 97.29 percentile.

Professional Experience

Dr. Anuradha Laishram has extensive experience in academia, currently serving as an Assistant Professor at the National Institute of Technology Manipur in the Department of Computer Science and Engineering since 2014. Prior to this, she gained six months of teaching experience as a lecturer at Alpha College of Engineering, Bangalore in 2011. Her teaching repertoire includes both undergraduate and postgraduate courses such as Computer Programming in C, Data Structures and Algorithm, Computer Organization and Architecture, and Data Communication and Computer Networks. She is proficient in programming languages including C, C++, and Python.

šŸ”¬ Research

Dr. Laishram’s research interests lie in the fields of machine learning, deep learning, medical image processing, and wireless sensor networks. Her doctoral research focused on the automatic classification of kidney diseases and oral anomalies using advanced neural network techniques and deep learning models. She has also contributed to various sponsored research projects, including the development of mHealth solutions for remote tribal areas and AI translation software.

Publication:šŸ“