Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

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

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“

 

Christopher Boafo | Technology | Best Researcher Award

Dr. Christopher Boafo | Technology | Best Researcher Award

Christopher Boafo is a researcher at Leipzig University’s International SEPT Competence Centre, based in Leipzig, Germany. He holds a PhD in Management Science and an MBA in Small and Medium-Sized Enterprise Development, both from Leipzig University, along with a BA in Publishing Management from Kwame Nkrumah University of Science and Technology, Ghana. His expertise spans quantitative and qualitative methodologies, university-business linkages, and SME internationalization. Christopher has received notable awards including the ACCESS Scholarship Grant for PhD Studies and the DAAD Carlo-Schmid Fellowship at UN Volunteers Headquarters.

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šŸŽ“Education:

  • PhD in Management Science, Leipzig University
  • MBA in Small and Medium-Sized Enterprise Development, Leipzig University
  • BA in Publishing Management, Kwame Nkrumah University of Science and Technology, Ghana

šŸ“ŠSpecializations: Quantitative & qualitative methodologies, university-business linkages, SME internationalization.

Professional Experience:

  • Current: Researcher at International SEPT Competence Center, Leipzig University
  • Previous roles include international consultancy and UN volunteer work

šŸŽ“Teaching Activities:

  • Lecturer at SEPT MBA Unit, Leipzig University, focusing on Entrepreneurship and SME Internationalization

šŸ…Awards:

  • ACCESS Scholarship Grant for PhD Studies
  • DAAD Carlo-Schmid Fellowship at UN Volunteers Headquarters

Publications Top Notes šŸ“

 

  • Knowledge Transfer From Business Schools to Firms Through Academics: An AMO Perspective in an Emerging Economy
    • Journal: Thunderbird International Business Review
    • Year: 2024 (Article in Press)
    • Access: Open access

 

  • International entrepreneurship in Sub-Saharan Africa: interfirm coordination and local economy dynamics in the informal economy
    • Journal: Journal of Small Business and Enterprise Development
    • Year: 2023
    • Volume: 30
    • Issue: 3
    • Pages: 587ā€“620
    • Citations: 3

 

  • Understanding internationalisation of informal African firms through a network perspective
    • Journal: International Small Business Journal: Researching Entrepreneurship
    • Year: 2022
    • Volume: 40
    • Issue: 5
    • Pages: 618ā€“649
    • Access: Open access
    • Citations: 10

 

  • Informal born regional enterprises in Ghana: an extension of internationalisation theories
    • Journal: International Journal of Entrepreneurship and Small Business
    • Year: 2022
    • Volume: 47
    • Issue: 4
    • Pages: 450ā€“493
    • Citations: 0

Mohammad Mohammadpour | Motion planning | Best Researcher Award

Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

Ā Dr. University of Quebec at Trois-RiviĆØres, Canada

šŸ‘©ā€šŸ”¬ Ph.D. in Mechanical Engineering with over eight years of specialized experience in R&D, contributing to cutting-edge projects at two renowned institutions.

 

Profile

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Education šŸŽ“

Ph.D. in Mechanical Engineering (Robotics), University of Quebec at Trois RiviĆØres, QC, Trois RiviĆØres, Canada; May 2019-Feb 2024Masterā€™s degree in Aerospace Engineering (Flight Dynamic & Control), Amirkabir University of Technology, Tehran, Iran; 2014Bachelor’s degree in Mechanical Engineering, Tehran, Iran; 2011

Skills šŸ› ļø

Programming Language: Python, C++Software: ROS, Gazebo, Rviz, MATLAB & Simulink Research: Navigation and Sensor Data Fusion Motion Planning (Guidance)Movement Sciences (Kinetic & Kinematic)Dynamic Modelling and Control Machine Learning and Deep Learning Obstacle Avoidance Applications: Autonomous Mobile Robots (simulation and experiment)Learning Frameworks: Scikit-learn, Keras, TensorFlow

Experience šŸš€ Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois RiviĆØres, Trois RiviĆØres, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robotsā€™ motion Implementing motion planning (guidance) algorithms on an Autonomous Mobile Robot and an Autonomous Forklift (simulation and experiment)Developing motion planning (guidance) algorithms using deep neural networks and the robotsā€™ kinetic models (simulation and experiment)Designing and implementing motion controllers (simulation and experiment). Research And Development Engineer Research Center of Amirkabir University of Technology, Tehran, Iran; 2015-2019Contributed to the Attitude Determination And Control System Executed MIL, SIL, PIL, and HIL simulation and testing Conducted operation and calibration tests of sensors Participated in dynamic modelling

Publications Top Notes šŸ“

i. Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model, Authors: M. Mohammadpour et al., 2023

 

ii. Energy-efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position, Authors: Not provided, 2022

 

iii. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots, Authors: M. Mohammadpour et al., 2021

 

 

sofia aftab | Neural network | Best Researcher Award

Ā Ms. sofia aftab | Neural network | Best Researcher Award

Ms. Norges Teknisk-Naturvitenskapelige Universitet,Ā Norway

šŸ‘©ā€šŸ”¬ Highly experienced Data Scientist with expertise in research, data science, machine learning, advanced analytics, and Generative AI. Proficient in Python, SQL, SAS, Teradata, R, and QlikView. Possesses strong skills in business analysis, model building, and communication. Excels in statistical techniques, machine learning algorithms, deep learning frameworks, NLP, data engineering, and Generative AI. Experienced in agile project management and collaborative team environments.šŸŒŸ

Profile

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Scholar

 

šŸŽ“šŸ“šAcademics

  • MS (IT) specialization in Data Mining/Analytics from NUST
  • Ph.D (Machine Learning/Data Science) from NTNU

 

šŸ’¼šŸ“ŠCareer Skills/Knowledge

Over 12 years of experience as an enthusiastic Data Scientist Strong business analysis and data mining skills Expertise in model building and execution Proficient in segmentation and customer value management analytics Skilled in statistical techniques including regression, A/B testing, and statistical significance of ML models Experienced in machine learning algorithms such as NN, SVM, Naive Bayes, ensemble modeling, and deep learning (DNN)Knowledgeable in NLP techniques, data engineering, MLOps, and cloud deployments Experienced in Generative AI techniques including prompt engineering, Lang chain, and Semantic search Research-focused with experience in improving evaluation metrics and developing recommendation algorithms Proficient in agile project management methodologies

šŸ¢šŸ’¼Experience

Accenture-Norway (Aug 2022 – Present)Data Science Consultant/Team Lead Built and maintained data and ML pipelines Developed ML models and CI/CD workflows Collaborated with cross-functional teams Led agile projects and worked on Generative AI Telenor-Norway (Dec 2020 – Aug 2022)Data Scientist Evaluated and improved ML projects Transformed business questions into analysis Led agile projects and presented to management NTNU (Apr 2018 – 2020)Research Scientist Worked on Recommendation systems using deep learning Improved evaluation metrics for recommender systems HPE (May 2016 – 2018)Data Scientist (Consultant)Identified cross-sell and upsell opportunities Developed and maintained next best action engine Telenor (Aug 2015 – May 2016)Specialist Advance Analytics and Consumer Insight Conducted subscriber analysis and developed churn/retention framework Telenor (Aug 2013 – Aug 2015)Executive Advance Analytics and Consumer Insight Developed behavioral segmentation and churn prediction models ProtĆ©gĆ© Global (Aug 2012 – 2013)Team Lead Data Miner/Data Scientist Managed a team for data mining projects and conducted exploratory data analysis Muhammad Ali Jinnah University (MAJU) (2012 – 2013)Lecturer, Trainer National University of Science and Technology (NUST) (2011 – 2012)Research Assistant

Publications Top Notes šŸ“

  1. Title: Data Mining in Insurance Claims (DMICS) Two-way mining for extreme values
    • Authors: S Aftab, W Abbas, MM Bilal, T Hussain, M Shoaib, SH Mehmood
    • Conference: Eighth International Conference on Digital Information Management (ICDIM)
    • Year: 2013
    • Citations: 6

 

  1. Title: Evaluating top-n recommendations using ranked error approach: An empirical analysis
    • Authors: S Aftab, H Ramampiaro
    • Journal: IEEE Access
    • Volume: 10
    • Pages: 30832-30845
    • Year: 2022
    • Citations: 4

 

  1. Title: Improving top-N recommendations using batch approximation for weighted pair-wise loss
    • Authors: S Aftab, H Ramampiaro
    • Journal: Machine Learning with Applications
    • Volume: 15
    • Pages: 100520
    • Year: 2024

 

  1. Title: Deep Contextual Grid Triplet Network for Context-Aware Recommendation
    • Authors: S Aftab, H Ramampiaro, H Langseth, M Ruocco
    • Journal: IEEE Access
    • Year: 2023

 

  1. Title: Data Mining in Insurance Claims (DMICS)
    • Authors: S Aftab, W Abbass, MM Bilal, T Hussain, M Shoaib, SH Mehmood

 

Sahar Zeinali | Autonomous systems| Best Researcher Award

Dr. Sahar Zeinali| Autonomous systems | Best Researcher Award

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

šŸ‘©ā€šŸ”¬ With a Ph.D. in Control Systems from Sharif University of Technology and experience as a Researcher in Automotive Systems at the University of LĆ¼beck, 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.šŸŒŸ

Profile

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Orcid

 

šŸ’¼Professional Experience

Researcher in Automotive Systems University of LĆ¼beck, LĆ¼beck, Germany 2022ā€“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 2018ā€“2019

šŸŽ“Education

Ph.D. in Control Systems Sharif University of Technology, Tehran, Iran 2016ā€“2021 Visiting Researcher in Control Systems Universitat AutĆ²noma de Barcelona, Barcelona, Spain 2019ā€“2020 M.Sc. in Modeling, Simulation and Control Sharif University of Technology, Tehran, Iran 2013ā€“2015 B.Sc. in Chemical Engineering Sharif University of Technology, Tehran, Iran 2009ā€“2013 Notable Projects Design of Interaction-Aware Driving Assistance Systems for Autonomous Vehicles University of LĆ¼beck, LĆ¼beck, Germany 2023ā€“Present

šŸ–„ļø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

šŸ†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 Iranā€™s National Elites Foundation. Admitted to Exceptional Talents Schools, 2002ā€“2009, Tabriz, Iran.

Publications Top Notes šŸ“

  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.