Hyung-Pil Chang | Deep Learning | Best Researcher Award

Posted on by ScienceFather

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.

 

 

 

Prasanna Kumar G | Ubiquitous Networks | Excellence in Research

Posted on by ScienceFather

Dr. Prasanna Kumar G | Ubiquitous Networks | Excellence in Research

Dr Prasanna Kumar G The National Institute of Engineering India

Dr. Prasanna Kumar G has made substantial contributions to the fields of cybersecurity and ubiquitous networks through a diverse range of publications and research activities. His scholarly work spans several key areas including machine learning in cybersecurity, IoT-based networking solutions, and advanced network models for seamless connectivity.

scholar

Academic History 🎓

Ph.D. in Networking and Internet Engineering, Visvesvaraya Technological University, Sri Jayachamarajendra College of Engineering, Mysore (2023).M.Tech in Networking and Internet Engineering, Visvesvaraya Technological University, Sri Jayachamarajendra College of Engineering, Mysore (2011) – 80.80%.Bachelor’s in Computer Science and Engineering, Visvesvaraya Technological University, Coorg Institute of Technology, Ponnampet (2009) – 58.14%.PUC, Karnataka PU Board, Sarada Vilas PU College, Mysore (2005) – 62.00%.S.S.L.C., Karnataka Secondary Education Board, Sadvidya High School, Mysore (2003) – 76.00%.

Technical Skills 🛠️

Programming Languages: C, C++, Java, PHP, C#.Web Technologies: HTML, CSS, JavaScript, PHP.Operating Systems: Windows, Linux.Database Management: MySQL.Scripting: Shell Script

Projects and Patents 🏗️

M.Tech Project: “Simulation of S-Bus Protocol Devices” – Development and component testing..Patent 1: “Smart Navigation Stick for the Visually Impaired” (Design No. 6295943).Patent 2: “AI-Based Smart Glasses for Visually Impaired” (Application No. 399870-001).

Training and Workshops 🧑‍🏫

Organized and attended various workshops on Python Programming, IoT, Smart Grid Technologies, Network Technologies, and Business Intelligence.

Achievements 🏅

Guided projects that won awards, such as 1st prize in IEEE Project Expo 2023 and Best Paper Award in NCEIS-2019.

Publication

  • Introduction to Cyber Security
    Authors: S. Jadey, S.C. Girish, K. Raghavendra, H.R. Srinidhi, K.M. Anilkumar
    Book: Methods, Implementation, and Application of Cyber Security Intelligence and Analytics
    Year: 2022

 

  • NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs
    Author: P.K. Gurumallu
    Journal: International Journal of Intelligent Engineering & Systems
    Volume: 15 (5)
    Year: 2022

 

  • Machine Learning in Cybersecurity: A Comprehensive Survey of Data Breach Detection, Cyber-Attack Prevention, and Fraud Detection
    Authors: P. Kumar, D.Y. Gowda, A.M. Prakash
    Book: Pioneering Smart Healthcare 5.0 with IoT, Federated Learning, and Cloud Security
    Year: 2024

 

  • An Efficient IoT-based Ubiquitous Networking Service for Smart Cities Using Machine Learning Based Regression Algorithm
    Authors: G. Prasanna Kumar, N. Shankaraiah
    Journal: International Journal of Information Technology and Computer Science (IJITCS)
    Volume: 15, Pages 15-25
    Year: 2023

 

  • A Novel Approach by Integrating Dynamic Network Selection and Security Measures to Improve Seamless Connectivity in Ubiquitous Networks
    Authors: P. Kumar G, S. N., R. M. B., S. J., S. B. S., D. Y., M. K. B.
    Journal: International Journal of Wireless and Microwave Technologies (IJWMT)
    Volume: 14 (1)
    Year: 2024

 

  • A Metaheuristic Handover Model Using Network Augmentation and Game Theory for Seamless Connectivity in Heterogeneous Networks
    Authors: G. Prasanna Kumar, N. Shankaraiah
    Journal: Wireless Personal Communications
    Volume: 134 (1), Pages 133-150
    Year: 2024

 

  • Basics of Healthcare Informatics
    Authors: J. Sudeep, M. Goutham, G. Prasannakumar, K. Raghavendra, S.C. Girish
    Book: Intelligent Systems in Healthcare and Disease Identification using Data Science
    Year: 2023

 

 

Conclusion:

Dr. Prasanna Kumar G’s body of work reflects a deep engagement with both theoretical and practical aspects of cybersecurity and network engineering. His research not only contributes to the academic community but also offers practical solutions and frameworks applicable to real-world problems. His innovative approaches to network design, security measures, and machine learning applications are indicative of a forward-thinking researcher dedicated to enhancing technological and scientific understanding.

 

 

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Posted on by ScienceFather

Ms. Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Lecturer at  University of Sri Jayewardenepura, Sri Lanka 

M.C. Akarshani Amarasinghe is an accomplished academic and researcher pursuing a PhD in Computer Engineering at the University of Sri Jayewardenepura, Sri Lanka. With a strong background in machine learning, image processing, and drone technology, her work focuses on innovative solutions for public health and agriculture. She has contributed to impactful research projects, such as identifying dengue mosquito breeding sites via drones and optimizing pesticide usage in arable lands. Alongside her research, Akarshani has extensive teaching experience, is a mentor for Google Summer of Code, and holds several prestigious awards for her research excellence.

Publication profile

scholar

🎓 Higher Education

01.2024 – Present PhD in Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Supervisors: Dr. Udaya Wijenayake, Prof. K.L. Jayaratne Research: Path planning algorithm for achieving multiple goals.. 2011 – 2016. BSc (Hons) in Computer Science, University of Colombo School of Computing, Sri Lanka Second Class Upper Division (3.25/4 – Four-Year Program)

🔬 Recent Research

D4D (Drone for Dengue) Sustainable Computing Research Group, University of Colombo School of Computing. Research on machine learning and image processing for identifying dengue mosquito breeding sites via drone images. Advisors: Prof. T.N.K. De Zoysa, Dr. C.I. Keppitiyagama. 2017 – Present GitHub Project

🧑‍🏫 Teaching Experience

03.02.2020 – Present Lecturer, Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Subjects: Operating Systems, Data Mining, Natural Language Processing, Quality Engineering, Compilers.01.01.2019 – 31.01.2020 Assistant Lecturer, Department of Computer Science and Software Engineering, Sri Lanka Institute of Information Technology Subjects: Software Engineering Concepts, Programming, Distributed Systems. 01.02.2018 – 30.12.2018 Assistant Lecturer, University of Colombo School of Computing Subjects: Programming Using C, Data Structures, Operating Systems. 2018 Visiting Lecturer, National Institute of Business Management, Sri Lanka Subject: Image Processing. 02.01.2018 – 01.02.2018 Instructor, University of Colombo School of Computing

🏅 Awards and Achievements

2023 Student Research Project of the Year at the National ICT Awards, NBQSA 2023. 2022 Best Paper in AI and ML Track, ICARC 2022. 2019 N2Women Travel Grant to attend ACM SenSys 2019. 2017 N2Women Travel Grant to attend MobiSys Women’s Workshop

🏢 Professional Service

2023 – Present Treasurer, Past Pupils’ Association, Sadhu Daham Pasala, Sri Lanka. 2015 – Present Committee Member, Thumbowila Api Welfare Society. 2012 – 2016 Committee Member, AIESEC Colombo – South

Publication

  1. Identifying mosquito breeding sites via drone images
    Authors: C Suduwella, A Amarasinghe, L Niroshan, C Elvitigala, K De Zoysa, …
    Conference: Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems
    Year: 2017
    Citations: 29

 

  1. A machine learning approach for identifying mosquito breeding sites via drone images
    Authors: A Amarasinghe, C Suduwella, C Elvitigala, L Niroshan, RJ Amaraweera, …
    Conference: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems
    Year: 2017
    Citations: 15

 

  1. Suppressing dengue via a drone system
    Authors: A Amarasinghe, C Suduwella, L Niroshan, C Elvitigala, K De Zoysa, …
    Conference: 2017 Seventeenth International Conference on Advances in ICT for Emerging Regions
    Year: 2017
    Citations: 15

 

  1. A swarm of crop spraying drones solution for optimizing safe pesticide usage in arable lands
    Authors: A Amarasinghe, VB Wijesuriya, D Ganepola, L Jayaratne
    Conference: Proceedings of the 17th Conference on Embedded Networked Sensor Systems
    Year: 2019
    Citations: 10

 

  1. A path planning algorithm for an autonomous drone against the overuse of pesticides
    Authors: A Amarasinghe, VB Wijesuriya, L Jayaratne
    Conference: 2021 10th International Conference on Information and Automation for Sustainability
    Year: 2021
    Citations: 5

 

  1. Drones vs dengue: a drone-based mosquito control system for preventing dengue
    Authors: A Amarasinghe, VB Wijesuriya
    Conference: 2020 RIVF International Conference on Computing and Communication Technologies
    Year: 2020
    Citations: 4

 

  1. Stimme: a chat application for communicating with hearing impaired persons
    Authors: A Amarasinghe, VB Wijesuriya
    Conference: 2019 14th Conference on Industrial and Information Systems (ICIIS)
    Year: 2019
    Citations: 4

✅ Conclusion

M.C. Akarshani Amarasinghe is an excellent candidate for the Research for Young Scientist Award. Her innovative contributions to drone technology for health and agriculture, leadership roles, and technical skills make her stand out. With continued expansion of her research portfolio and international exposure, she has the potential to achieve even greater recognition in the future.

seyed matin malakouti | AI | Best Researcher Award

Posted on by ScienceFather

seyed matin malakouti | AI | Best Researcher Award

Seyed Matin Malakouti is an accomplished Electrical Engineering professional specializing in machine learning and control systems. He holds an MS in Control System Engineering from the University of Tabriz and a BS in Electrical Engineering from Isfahan University of Technology. Malakouti has published extensively on topics including wind power prediction, temperature change modeling, and heart disease classification. His work has appeared in prominent journals such as Energy Exploration & Exploitation and Case Studies in Chemical and Environmental Engineering. He has received recognition for his research, including awards for Best Researcher and nominations for Best Paper. Malakouti’s research interests span applied machine learning, renewable energy, and biomedical signal processing. He is also an active peer reviewer for various scientific journals.

Publication profile

google scholar

🎓 Education

MS in Electrical Engineering – Control System Engineering University of Tabriz, Tabriz, Iran (2019 – 2022). BS in Electrical Engineering
Isfahan University of Technology (IUT), Isfahan, Iran (2014 – 2019)

🏢 Professional Experience

Undergraduate Teaching Assistant Dept. of Electrical Engineering, Isfahan University of Technology (IUT) (2015 – 2018) Assisted in teaching core courses such as Calculus I, II, Electrical Circuit I, II, and Electronics II.

🏆 Awards & Fellowships

Best Researcher, International Conference on Cardiology and Cardiovascular Medicine (2023). Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods (2023)

👨‍🏫 Teaching Experience

Spring 2018: Calculus I, Teaching Assistant. Spring 2017: Calculus II, Teaching Assistant. Fall 2016: Electrical Circuit I, Teaching Assistant. Spring 2015: Electrical Circuit II, Teaching Assistant

Research for Best Researcher Award: Seyed Matin Malakouti

🌟 Strengths for the Award

  1. Diverse Research Contributions: Seyed Matin Malakouti has an extensive list of publications covering a broad range of topics, from wind power generation and temperature change prediction to heart disease classification and asteroid detection. This indicates a high level of versatility and a strong ability to apply machine learning across different domains.
  2. Cutting-Edge Techniques: His work utilizes advanced machine learning techniques such as CNN-LSTM, ensemble methods, and Bayesian optimization. This demonstrates a commitment to leveraging state-of-the-art methods to address complex problems.
  3. High-Impact Publications: Malakouti has published in high-impact journals such as Energy Exploration & Exploitation, Biomedical Signal Processing and Control, and Case Studies in Chemical and Environmental Engineering. His work is also recognized by prestigious conferences and has received nominations for awards.
  4. Peer Review Engagement: Active involvement in peer review for numerous reputable journals reflects his expertise and recognition within the academic community.
  5. Awards and Recognition: Being named the Best Researcher at an international conference and receiving nominations for best paper awards highlights his research’s quality and impact.

🔍 Areas for Improvement

  1. Broader Impact Assessment: While his technical contributions are substantial, including a focus on how his research impacts broader societal and industrial contexts could further enhance his profile. Emphasizing real-world applications and collaborations could demonstrate the practical significance of his work.
  2. Interdisciplinary Collaboration: Engaging in interdisciplinary projects could further enrich his research profile. Collaborating with researchers from other fields, such as environmental science or healthcare, could lead to innovative solutions and increase the impact of his work.
  3. Public Engagement and Outreach: Increasing efforts in public science communication and outreach could help bridge the gap between academic research and public understanding. Engaging with non-academic audiences through popular science articles, talks, or educational programs could be beneficial.

Publication top notes

  1. Title: Predicting wind power generation using machine learning and CNN-LSTM approaches
    Citations: 46
    Year: 2022
    Journal: Wind Engineering 46(6), 1853-1869

 

  1. Title: Heart disease classification based on ECG using machine learning models
    Citations: 39
    Year: 2023
    Journal: Biomedical Signal Processing and Control 84, 104796

 

  1. Title: Utilizing time series data from 1961 to 2019 recorded around the world and machine learning to create a Global Temperature Change Prediction Model
    Citations: 37
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100312

 

  1. Title: The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
    Citations: 32
    Year: 2023
    Journal: Cleaner Engineering and Technology 15, 100664

 

  1. Title: Use machine learning algorithms to predict turbine power generation to replace renewable energy with fossil fuels
    Citations: 26
    Year: 2023
    Journal: Energy Exploration & Exploitation 41(2), 836-857

 

  1. Title: Evaluation of the application of computational model machine learning methods to simulate wind speed in predicting the production capacity of the Swiss basel wind farm
    Citations: 21
    Year: 2022
    Journal: 2022 26th International Electrical Power Distribution Conference (EPDC), 31-36

 

  1. Title: Improving the prediction of wind speed and power production of SCADA system with ensemble method and 10-fold cross-validation
    Citations: 19
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 8, 100351

 

  1. Title: Estimating the output power and wind speed with ML methods: a case study in Texas
    Citations: 17
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100324

 

  1. Title: Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in Predicting Wind Speed and Energy Generation
    Citations: 15
    Year: 2023
    Journal: Intelligent Systems with Applications 19, 200248

 

  1. Title: AERO2022-flying danger reduction for quadcopters by using machine learning to estimate current, voltage, and flight area
    Citations: 15
    Year: 2022
    Journal: e-Prime-Advances in Electrical Engineering, Electronics and Energy 2, 100084

 

  1. Title: Prediction of wind speed and power with LightGBM and grid search: case study based on Scada system in Turkey
    Citations: 8
    Year: 2023
    Journal: International Journal of Energy Production and Management 8.

 

🏆 Conclusion

Seyed Matin Malakouti is a strong candidate for the Research for Best Researcher Award due to his diverse and impactful research contributions, utilization of advanced machine learning techniques, and recognition within the academic community. By focusing on broader impact, interdisciplinary collaboration, and public engagement, he can further enhance his research profile and increase the overall impact of his work.

Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

Posted on by ScienceFather

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

Assoc Prof Dr.  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.

🎓 Education

2004–2008  Ph.D, Kharazmi University. 2002–2004  M.Sc, Kharazmi University. 1998–2002 B.Sc, Shahid Beheshti University.

🎯 Interests

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

💼 Working Experience

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

🏆 Awards

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

🎤 Invited Talks and Conferences

2009 🇪🇸 Infinite Matrices over Completely Counteractive Banach Algebras, Madrid University, Spain. 2010 🇸🇪 Operator-Valued Convolution Algebras, Chalmers University, Sweden. 2011 🇯🇵 Operator Algebras and their Applications, RIMS, Kyoto University, Japan. 2011 🇵🇱 Operator Algebras and Quantum Groups, Banach Center, Poland. 2011 🇱🇺 Noncommutative Harmonic Analysis and Representation Theory, Luxembourg University, Luxembourg. 2023 🇫🇷 Noncommutative Analysis on Groups and Quantum Groups, Université de Bourgogne Franche-Comté, France.

🎓 Ph.D. Students

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

Publications

  • Wold-type decompositions in Baer⁎-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 plankton–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 Baer⁎-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.