Karthick SA| Control Theory | Best Researcher Award

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Dr. Karthick SA| Control Theory | Best Researcher Award

Assistant Professor, SRM Institute of Science andTechnology, Kattankulathur India

Dr. S. A. Karthick is an experienced academic and researcher specializing in robust control systems, fuzzy systems, and UAV systems. He is currently an Assistant Professor at SRM Institute of Science and Technology, Chennai. Dr. Karthick completed his Post-doctoral fellowship at National Tsing Hua University, Taiwan (2021-2023), following his Ph.D. in Mathematics from Anna University, Coimbatore. His work spans robust control, filter design, and suspension systems.

Publication Profile

Scholar

🎓 Education 

Post-doctoral Fellow (2021-2023) at National Tsing Hua University, Taiwan. Ph.D. in Mathematics (2020) from Anna University, Coimbatore. M.Phil. in Mathematics (2013) from Gobi Arts & Science College, Gobichettipalayam. M.Sc. in Mathematics (2011) from Kongu Arts & Science College, Erode. B.Sc. in Mathematics (2009) from Gobi Arts & Science College, Gobichettipalayam

💼 Experience 

Dr. Karthick is currently an Assistant Professor at SRM Institute of Science and Technology, Chennai (Sept 2023-present). He was a Postdoctoral Fellow at National Tsing Hua University, Taiwan (2021-2023). Prior to this, he worked as an Assistant Professor at PPG Institute of Technology, Coimbatore (2013-2015). His academic journey has provided him with in-depth expertise in mathematics and engineering applications.

🏆 Awards & Honors 

Dr. Karthick received the National Science and Technology Council-NSTC Fellowship (2021-2023) during his postdoctoral research in Taiwan. He has been recognized for his excellence in research, particularly in robust control systems and fuzzy systems. His contributions to suspension systems and UAV systems further solidified his reputation in the academic community.

🔬 Research Focus 

Dr. Karthick’s research interests include robust control systems, fuzzy systems, filter design, and unmanned aerial vehicle (UAV) systems. He explores mathematical models to improve system reliability and efficiency, focusing on the design and analysis of systems like suspension systems and UAV control, aiming to advance automation and control technologies. His work contributes significantly to applied mathematics and engineering fields.

Publication Top Notes

  • Dissipativity-based non-fragile sampled-data control design of interval type-2 fuzzy systems subject to random delays
    • Year: 2018
    • Authors: R Sakthivel, SA Karthick, B Kaviarasan, F Alzahrani
    • Citations: 48

 

  • Disturbance rejection of fractional-order TS fuzzy neural networks based on quantized dynamic output feedback controller
    • Year: 2019
    • Authors: SA Karthick, R Sakthivel, YK Ma, S Mohanapriya, A Leelamani
    • Citations: 45

 

  • Synchronization of coupled memristive neural networks with actuator saturation and switching topology
    • Year: 2020
    • Authors: SA Karthick, R Sakthivel, C Wang, YK Ma
    • Citations: 29

 

  • Synchronization of semi-Markov coupled neural networks with impulse effects and leakage delay
    • Year: 2020
    • Authors: SA Karthick, R Sakthivel, F Alzahrani, A Leelamani
    • Citations: 27

 

  • Finite-time decentralized event-triggering non-fragile control for fuzzy neural networks with cyber-attack and energy constraints
    • Year: 2021
    • Authors: S Kanakalakshmi, R Sakthivel, SA Karthick, A Leelamani, A Parivallal
    • Citations: 25

 

  • Reliable state estimation of switched neutral system with nonlinear actuator faults via sampled-data control
    • Year: 2017
    • Authors: R Sakthivel, SA Karthick, B Kaviarasan, Y Lim
    • Citations: 20

 

  • Proportional integral observer based tracking control design for Markov jump systems
    • Year: 2021
    • Authors: M Vijayakumar, R Sakthivel, A Mohammadzadeh, SA Karthick, …
    • Citations: 14

 

  • Observer based guaranteed cost control for Markovian jump stochastic neutral-type neural networks
    • Year: 2020
    • Authors: SA Karthick, R Sakthivel, YK Ma, A Leelamani
    • Citations: 13

 

  • Non-fragile control design for stochastic Markov jump system with multiple delays and cyber attacks
    • Year: 2022
    • Authors: H Divya, R Sakthivel, SA Karthick, C Aouiti
    • Citations: 12

 

  • Finite-time synchronization of hierarchical hybrid coupled neural networks with mismatched quantization
    • Year: 2021
    • Authors: R Sakthivel, N Aravinth, C Aouiti, K Arumugam
    • Citations: 8

 

  • Memory feedback finite-time control for memristive neutral-type neural networks with quantization
    • Year: 2021
    • Authors: SA Karthick, R Sakthivel, C Aouiti, A Leelamani
    • Citations: 7

 

  • Hybrid‐triggered based reliable filter design for interval type‐2 fuzzy system under deception attacks and missing measurements
    • Year: 2023
    • Authors: K Arumugam, BS Chen
    • Citations: 6

 

  • Finite-time non-fragile control for synchronization of fractional-order stochastic neural networks
    • Year: 2023
    • Authors: S Kanakalakshmi, R Sakthivel, SA Karthick, C Wang, A Leelamani
    • Citations: 5

 

  • Finite-time reliable sampled-data control for fractional-order memristive neural networks with quantisation
    • Year: 2023
    • Authors: R Sakthivel, K SA, C Wang
    • Citations: 5

 

Ferdib Al Islam | Machine Learning | Excellence in Research

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Mr. Ferdib Al Islam | Machine Learning | Excellence in Research

Assistant Professor, Northern University of Business and Technology Khulna Bangladesh

Ferdib-Al-Islam is an Assistant Professor at Northern University of Business and Technology Khulna, Bangladesh. He holds a Master’s and Bachelor’s degree in Computer Science and Engineering from Khulna University of Engineering & Technology (KUET) and Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU), respectively. His research expertise encompasses Machine Learning, Deep Learning, IoT, Data Science, and Computer Vision. Ferdib’s career includes experience as a software engineer in IoT R&D and lecturer roles, contributing significantly to academic and research pursuits.

Publication Profile

Google Scholar

🎓 Education

M.Sc. Eng. in Computer Science and Engineering from KUET (2023) – GPA: 3.50. B.Sc. Eng. in Computer Science and Engineering from BSMRSTU (2018) – GPA: 3.55. HSC in Science from Govt. PC College, Bagerhat (2012) – 5.00. SSC in Science from Bagerhat Govt. Secondary School (2010) – 5.00

💼 Experience

Ferdib has progressed from an intern to a Senior Lecturer, and now an Assistant Professor at Northern University of Business and Technology Khulna. He served as a Lecturer in Computer Science and Engineering from March 2020 to January 2024. His career also includes a Jr. Software Engineer role at W3 Engineers Ltd. in the IoT R&D sector. Ferdib brings practical industry experience into his academic roles, fostering innovation and research.

🏆 Awards & Honors

Ferdib has earned notable accolades, including the Gold Award at Semarak International Research Article Competition III 2024 for his work on Autism Spectrum Disorder detection. He also received the Best Paper Award at ICETIS 2021 for his research on Diabetes Mellitus prediction and the Honorable Mention Award at BDML 2020 for his IoT-based health monitoring tool.

🔬 Research Focus

Ferdib’s primary research interests are in Machine Learning, Deep Learning, IoT, Large Language Models, and Computer Vision. His work focuses on the application of AI techniques to healthcare, predictive modeling, and intelligent systems. His aim is to leverage machine learning for real-world applications like healthcare diagnostics, smart monitoring systems, and data-driven insights in various fields.

Conclusion

Ferdib Al-Islam is an exceptional researcher with notable accomplishments in machine learning, deep learning, and IoT. His commitment to advancing knowledge in these areas, demonstrated by his numerous awards and research contributions, marks him as a leading figure in his field. However, fostering greater interdisciplinary collaborations and increasing his global academic presence will be beneficial for his continued growth as a researcher. He is undoubtedly a deserving candidate for the Excellence in Research award, given his dedication, achievements, and potential for further contributions to the scientific community.

Publication Top Notes

  • Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam, MM Islam, MS Al-Rakhami, MR Haque
    • Citation: 73
  • An IoT Enabled Health Monitoring Kit Using Non-Invasive Health Parameters
    • Year: 2021
    • Authors: A Das, SD Katha, MS Sadi, Ferdib-Al-Islam
    • Citation: 31
  • Hepatocellular Carcinoma Patient’s Survival Prediction Using Oversampling and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, L Akter, MM Islam
    • Citation: 21
  • An Enhanced Stroke Prediction Scheme Using SMOTE and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 20
  • Early Identification of Parkinson’s Disease from Hand-drawn Images using Histogram of Oriented Gradients and Machine Learning Techniques
    • Year: 2020
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 19
  • Dementia Identification for Diagnosing Alzheimer’s Disease using XGBoost Algorithm
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 17
  • COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning
    • Year: 2021
    • Authors: P Saha, MS Sadi, OFMRR Aranya, S Jahan, FA Islam
    • Citation: 9
  • Detection of Hepatitis C Virus Progressed Patient’s Liver Condition Using Machine Learning
    • Year: 2022
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 6*
  • Diabetes Mellitus Prediction and Feature Importance Score Finding Using Extreme Gradient Boosting
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 4
  • COV-Doctor: A Machine Learning Based Scheme for Early Identification of COVID-19 in Patients
    • Year: 2022
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 3*
  • Breast Cancer Risk Prediction Using Different Clustering Techniques
    • Year: 2022
    • Authors: L Akter, M Raihan, M Raihan, M Sarker, M Ghosh, N Alvi, Ferdib-Al-Islam
    • Citation: 3
  • Crop-RecFIS: Machine Learning Classifiers for Crop Recommendation and Feature Importance Scores Calculation
    • Year: 2023
    • Authors: MS Sanim, KM Hasan, MM Alam, MAA Walid, MR Islam
    • Citation: 2
  • Prediction of Dementia Using SMOTE Based Oversampling and Stacking Classifier
    • Year: 2023
    • Authors: Ferdib-Al-Islam, MS Sanim, MR Islam, S Rahman, R Afzal, KM Hasan
    • Citation: 2*
  • An Ensemble Learning Model to Detect COVID-19 Pneumonia from Chest CT Scan
    • Year: 2022
    • Authors: PC Shill
    • Citation: 2

 

 

 

Bhanu Shrestha | Computer Science | Best Researcher Award

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Prof. Bhanu Shrestha | Computer Science | Best Researcher Award

Professor at Kwangwoon University, South Korea

Bhanu Shrestha is a Full Professor at Kwangwoon University, Korea. He holds expertise in electronic engineering with a background in various academic and professional roles, including Assistant and Associate Professorships at the same institution. A native of Nepal, he is passionate about research, education, and cultural exchange. Bhanu has also published books, research papers, and contributed to documentaries and music albums. His involvement extends to editorial positions, being Editor-in-Chief of the International Journal of Advanced Engineering since 2018. He is known for his academic and social contributions, particularly in the field of information technology and engineering.

 

Profile

Scopus

Orcid

 🎓 Education

Ph.D. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2004-2008). M.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2002-2004). B.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (1994-1998). S.L.C. from Bhim Secondary School, Dolakha, Nepal (1982)

💼 Experience

Adjunct Professor, Kwangwoon University, Korea (2008-2011). Assistant Professor, Kwangwoon University, Korea (2011-2016). Associate Professor, Kwangwoon University, Korea (2016-2021). Full Professor, Kwangwoon University, Korea (2021-Present). Bhanu Shrestha has held various academic positions, contributing significantly to the field of electronic engineering and nurturing the next generation of engineers. He has also been involved in leadership roles in professional organizations.

🏆 Awards and Honors

Achievement Award, IIBC Korea (2015). Best Paper Award, ISSAC 214 & ICACT 2014, IIBC, Seoul, Korea (2014). Excellent Paper Award, Korea Institute of Information Technology (2012). Certificate of Honorary Citizenship, Seong-buk District Office, Seoul, Korea (2012). Bellwave Excellent Paper Award, Korea Electromagnetic Engineering Society (2005). Vidhyabhusan Padak (Gold Medal), Nepal (2009) Bhanu has earned several prestigious awards, recognizing his academic excellence and contributions to research and development in engineering.

🔬 Research Focus

Bhanu Shrestha’s research interests include Internet of Things (IoT), artificial intelligence (AI), microelectromechanical systems (MEMS), and fuzzy logic applications in communication technology. His work also explores biosensors and nanotechnology for environmental remediation. As a guest editor for multiple journals, Bhanu’s research aims to push the boundaries of innovation in electronic engineering and its practical applications, particularly in smart systems and AI.

Conclusion

Bhanu Shrestha’s contributions to electronic engineering and technology, coupled with his leadership in academia, make him a highly deserving candidate for the Best Researcher Award. His accomplishments in publishing influential works, along with his global impact in the fields of artificial intelligence, IoT, and nanotechnology, showcase his research excellence. With continued collaboration and expansion into emerging areas, he is well-positioned to make even more significant strides in the scientific community, further cementing his legacy as a top researcher.

Publications 📚

ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

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Mr. ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

PHD at SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS Malaysia

Abel Chai Yu Hao is a PhD candidate at Swinburne University of Technology Sarawak, specializing in computer vision, machine learning, and deep learning. His research focuses on developing interpretable deep learning models for plant disease identification, collaborating with CIRAD and INRIA on innovative agricultural projects. With a Master’s degree in wireless communication, Abel has contributed to improving rural connectivity in Sarawak through cost-effective wireless solutions. He has co-authored numerous journal articles and conference papers on topics ranging from unseen plant disease recognition to wireless data transmission. Abel is a recipient of multiple awards, including the Gold Award at the Innovation Technology Exposition 2023, and is an active IEEE member.

scholar

🎓 Education

Doctor of Philosophy (2022 – Present) Swinburne University of Technology Sarawak Campus Research focus: Computer Vision, Machine Learning, Deep Learning, AI. Master of Engineering (2019 – 2021) Swinburne University of Technology Sarawak Campus Research focus: Wireless communication, Wi-Fi, Rural connectivity. Bachelor of Engineering (Honours), Electrical & Electronics Engineering (2014 – 2018) Swinburne University of Technology Sarawak Campus CGPA: 3.97/4 (High Distinction)

🏫 Professional Experience

Teaching Assistant (2019 – Present) Swinburne University of Technology Sarawak Campus Assisting in course delivery, tutorials, and research guidance

🏆 Awards & Scholarships

Gold Award in Innovation Technology Exposition (2023). Best Paper Award at International UNIMAS Engineering Conference (EnCon) (2020). Sarawak Energy External Scholarship (2015-2018). Swinburne Entrance Scholarship (2014)

🌱 Research Projects

Plant Disease Identification with Deep Learning (2022 – ongoing) Collaborating with experts from CIRAD, INRIA, focusing on AI-based plant disease detection. Rural Internet Connectivity Solutions (2019 – 2021) Conducted cost-performance analysis for wireless solutions in partnership with Sarawak Multimedia Authority (SMA)

Publication

  • Pairwise Feature Learning for Unseen Plant Disease Recognition
    Conference: International Conference on Image Processing (ICIP)
    Year: 2023
    Pages: 306–310
    Contributors: Hao Chai A.Y., Han Lee S., Tay F.S., Bonnet P., Joly A.

 

  • Unveiling Robust Feature Spaces: Image vs. Embedding-Oriented Approaches for Plant Disease Identification
    Conference: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
    Year: 2023
    Pages: 666–673
    Contributors: Ishrat H.A., Chai A.Y.H., Lee S.H., Then P.H.H.

 

  • Development and Application of Outdoor Router Cost Estimation with Parametric Modelling Technique
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Lai C.H., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Model Study for Outdoor Data Transmission Performance
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Then Y.L., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Parametric Model Study for Outdoor Routers Cost Estimation
    Conference: 13th International UNIMAS Engineering Conference (EnCon)
    Year: 2020
    Contributors: Hao Chai A.Y., Hung Lai C., Su H.T., Siang Tay F., Yong L.

🏆 Conclusion:

Abel Chai Yu Hao is a highly qualified candidate for the Best Researcher Award, given his solid academic background, impactful publications, international collaborations, and ongoing contributions to the field of AI and wireless communication. With continuous focus on expanding his research and increasing engagement, his profile can only continue to rise.

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

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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.

 

Mohammad Mohammadpour | Motion planning | Best Researcher Award

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Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

 Dr. University of Quebec at Trois-Rivières, Canada

👩‍🔬 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

Scopus

 

Education 🎓

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

Skills 🛠️

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 🚀 Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois Rivières, Trois Rivières, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robots’ 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 robots’ 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 📝

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

 

 

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

Orcid

 

💼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.

 

 

ALEXANDER FORDJOUR | Mechanical | Excellence in Research

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Dr. ALEXANDER FORDJOUR | Mechanical |Excellence in Research

👨‍🏫Profile Summary

Experienced researcher with a diverse academic background, holding a PhD in Fluid Machinery Engineering from Jiangsu University, China. Proficient in numerical simulation, construction planning, and optimization, with a keen interest in sprinkler irrigation systems. Holds membership in prestigious organizations like the American Society of Agricultural and Biological Engineers and the Institution of Engineering and Technology. Actively contributes as a journal reviewer for publications such as the American Journal of Science, Engineering and Technology and the European Scientific Journal. Passionate about advancing engineering solutions for sustainable resource management and agricultural development.

🌐 Professional Profiles

 

🎓 Academic Background

PhD in Fluid Machinery Engineering Jiangsu University, China MSc in Water Resource Engineering and Management Kwame Nkrumah University of Science and Technology (KNUST) BSc in Engineering Physics University of Cape Coast, Ghana

🔍 Research Interests

  • Numerical Simulation
  • Construction Planning and Management
  • Optimization
  • Sprinkler Irrigation

👨‍💼 Professional Memberships

  • Member, American Society of Agricultural and Biological Engineers
  • Member, Institution of Engineering and Technology

📝 External / Professional Roles Journal Reviewer:

  • American Journal of Science, Engineering and Technology
  • European Scientific Journal

 

📚Top Noted Publication

  1. Title: Experimental study on the effects of pressure loss on uniformity, application rate and velocity on different working conditions using the dynamic fluidic sprinkler
    Authors: Zhu, X., Fordjour, A., Agyen Dwomoh, F., … Dai, X., Oteng, J.
    Journal: Heliyon
    Volume: 10
    Issue: 5
    Pages: e27140
    Year: 2024
    Citations: 0

 

  1. Title: Structural design and performance characteristics of the fluidic sprinkler application technology for saving irrigation water: a review
    Authors: Dwomoh, F.A., Zhu, X., Fordjour, A., … Yuan, S., Li, H.
    Journal: Journal of Agricultural Engineering
    Volume: 54
    Issue: 2
    Pages: 1452
    Year: 2023
    Citations: 0

 

  1. Title: Modelling of water drop movement and distribution in no wind and windy conditions for different nozzle sizes
    Authors: Zhu, X., Lewballah, J.K., Fordjour, A., … Ofosu, S.A., Dwomoh, F.A.
    Journal: Water (Switzerland)
    Volume: 13
    Issue: 21
    Pages: 3006
    Year: 2021
    Citations: 2

 

  1. Title: Performance optimization of a newly designed dynamic fluidic sprinkler
    Authors: Zhu, X., Fordjour, A., Yuan, S., Dwomoh, F.A., Issaka, Z.
    Journal: Applied Engineering in Agriculture
    Volume: 37
    Issue: 1
    Pages: 33–41
    Year: 2021
    Citations: 1

 

  1. Title: Analysis of water droplet distribution in wind for the fluidic sprinkler
    Authors: Dwomoh, F.A., Yuan, S., Li, H., … Mensah, R., Fordjour, A.
    Journal: Water (Switzerland)
    Volume: 12
    Issue: 12
    Pages: 3320
    Year: 2020
    Citations: 3

 

  1. Title: Effect of riser height on rotation uniformity and application rate of the dynamic fluidic sprinkler
    Authors: Fordjour, A., Zhu, X., Jiang, C., Liu, J.
    Journal: Irrigation and Drainage
    Volume: 69
    Issue: 4
    Pages: 618–632
    Year: 2020
    Citations: 9

 

  1. Title: Comparative evaluation on performance characteristics of an impact sprinkler with nozzle-dispersion devices and rotary plate sprinkler
    Authors: Issaka, Z., Li, H., Jiang, Y., … Chen, C., Fordjour, A.
    Journal: Applied Engineering in Agriculture
    Volume: 36
    Issue: 3
    Pages: 321–329
    Year: 2020
    Citations: 4

 

  1. Title: Numerical simulation and experimental study on internal flow characteristic in the dynamic fluidic sprinkler
    Authors: Fordjour, A., Zhu, X., Yuan, S., Dwomoh, F.A., Issaka, Z.
    Journal: Applied Engineering in Agriculture
    Volume: 36
    Issue: 1
    Pages: 61–70
    Year: 2020
    Citations: 5

 

  1. Title: The collection method for crop fungal spores based on an efficient microfluidic device
    Authors: Wang, P., Yuan, S., Yang, N., … Fordjour, A., Chen, S.
    Journal: Aerosol and Air Quality Research
    Volume: 20
    Issue: 1
    Pages: 72–79
    Year: 2020
    Citations: 18

 

  1. Title: Modeling the application depth and water distribution uniformity of a linearly moved irrigation system
    Authors: Liu, J., Zhu, X., Yuan, S., Fordjour, A.
    Journal: Water (Switzerland)
    Volume: 11
    Issue: 4
    Pages: 827
    Year: 2019
    Citations: 10