SMART 4.0
SMART 4.0 fellows
The Marie Skłodowska-Curie actions (MSCAs) support researchers at all stages of their careers, encourage cooperation between industry and academia, and provide innovative training to enhance employability and career development. Below, please see some further background information on the talented individuals who were awarded fellowships during recent SMART 4.0 open competition calls.
Dr. Iman Abaspur Kazerouni
Project: Imaging System Development For Industrial Autonomous Vehicles (ISD-IAV)
Iman received both his BSc and MSc degrees in Electronic Engineering from the Hakim Sabzevari University, Iran, in 2008 and 2010 respectively. In 2014, he completed a PhD ..
Dr. Iman Abaspur Kazerouni
Iman is a SMART 4.0 Marie Skłodowska-Curie fellow researcher with CONFIRM Centre. He received both his BSc and MSc degrees in Electronic Engineering from the Hakim Sabzevari University, Iran, in 2008 and 2010 respectively. In 2014, he completed a PhD in Hakim Sabzevari University on the topic “Early breast cancer detection using thermal images”. His PhD research focused on the design of a smart system for mass detection in mammography and thermography images.
Later, Iman worked at the Department of Electronics and Computer Engineering (Esfarayen University of Technology) as an assistant professor. In 2019, he joined the Centre for Robotics and Intelligent Systems (CRIS, University of Limerick) as a postdoctoral researcher. His research interests focus on image processing, machine learning, deep learning, and robotic processing systems.
Qualifications:
- PhD in Electronic Engineering, Hakim Sabzevari University, Iran.
- MSc in Electronic Engineering, Hakim Sabzevari University, Iran.
- Eng in Electronic Engineering, Hakim Sabzevari University, Iran.
Professional Memberships and Activities:
- Postdoctoral Research Fellow, CRIS group, University of Limerick, Ireland
- Assistant Professor, Electronic and Computer Science Department, Esfarayen University of Technology, Iran
Expertise:
- Real time robots image processing
- Developing smart robotic technologies
- Medical image processing development
- Underwater robots imaging systems
Research Interests:
- Image processing
- Neural Network
- Deep Learning
- Artificial Intelligence
- Machine Vision
- Smart System Design
Selected Publications:
- I Abaspur Kazerouni, G Dooly, D Toal, Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching, Journal of Marine Science and Engineering 8 (6), 449, 2020.
- HM Hossein-Abad, M Shabanian, IA Kazerouni, Fuzzy c-means clustering method with the fuzzy distance definition applied on symmetric triangular fuzzy numbers, Journal of Intelligent & Fuzzy Systems 38 (3), 2891-2905, 2020.
- H Ghayoumi Zadeh, A Montazeri, I Abaspur Kazerouni, J Haddadnia, Clustering and screening for breast cancer on thermal images using a combination of SOM and MLP, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 5(1), 68-76, 2017.
- IA Kazerouni, J Haddadnia, A mass classification and image retrieval model for mammograms, The Imaging Science Journal 62 (7), 353-357, 2014.
Dr. Sourabh Bharti
Project: Edge Computing based Predictive Maintenance for Time Critical Applications
Sourabh received his PhD degree in 2018 from Indian Institute of Information Technology and Management, Gwalior, India. His doctoral research focused on ..
Dr. Sourabh Bharti
Sourabh received his PhD degree in 2018 from Indian Institute of Information Technology and Management, Gwalior, India. His doctoral research was focused on maintaining cross-layer quality of service in IoT sensory environment. Since 2018, he had been working with IGDTUW, Delhi as an Assistant Professor. He has published various papers in reputed journals and conferences in this research area.
His research during this fellowship will pertain to the domain of edge computing based predictive maintenance for industrial equipment/machines.
Qualifications:
- PhD (Information Technology)
- MTech (Computer Science & Engineering)
Professional Memberships and Activities:
- Member, IEEE
- Reviewer of IEEE Systems Journal, Springer JAIHC Journal and Wiley IJCS Journal
Expertise:
- Quality of Service provisioning in IoT sensory environment
- Edge Computing
- Machine Learning
Research Interests:
- Edge Computing
- Delay-aware Federated Learning
- Intelligent Sensor Networks
Selected Publications:
- Rahul K. Verma, K. K. Pattanaik, Sourabh Bharti, Divya Saxena, Jiannong Cao, A Query Processing Framework for Efficient Network Resource Utilization in Shared Sensor Networks, ACM Transactions on Sensor Networks (TOSN), vol. 16(4), pp 1-28, 2020.
- Sourabh Bharti, K. K. Pattanaik and Paolo Bellavista, Value of Information Based Sensor Ranking for Efficient Sensor Service Allocation in Service Oriented Wireless Sensor Networks, IEEE Transactions on Emerging Topics in Computing, DOI:10.1109/TETC.2019.2891716, 2019.
Dr. Jobish John
Project: Learning assisted scalability solutions for ultra-dense cellular industrial Iot (LASS4CIIT)
Jobish received his Ph.D. in Electrical Engineering from Indian Institute of Technology Bombay, India in 2020. His PhD research was ..
Dr. Jobish John
Jobish John, received his Ph.D. in Electrical Engineering from Indian Institute of Technology Bombay, India in 2020. His Ph.D. research was focused on wireless sensor networks for low-duty cycled sensing applications. He is a co-founder of an Agri-startup called Proximal Soilsens Technologies Pvt. Ltd., which implements wireless solutions for agricultural applications.
Jobish has a B-Tech in Electronics & Communication Engineering from Chengannur College of Engineering (2007). He has also worked with Larsen & Toubro-Embedded Systems, Bharat Sanchar Nigam Ltd. and at the Indian Institute of Information Technology, Kerala, India.
Qualifications:
- PhD in Electrical Engineering, Indian Institute of Technology Bombay, India
- BTech in Electronics & Communication Engineering, College of Engineering Chengannur, Kerala, India
Professional Memberships and Activities:
- Member of IEEE
Expertise:
- Internet of Things/ Wireless sensor networks
- Embedded Systems
- Commercialisation of research activities through start-ups
Research Interests:
- Wireless networks/solutions for Industry 4.0
- Embedded System Design
- Application of Machine Learning in resource constrained devices
Selected Publications:
- John, G. S. Kasbekar, D. K. Sharma, V. Ramulu, M. Shojaei Baghini, “Design and implementation of a Wireless Sensor Network for Agricultural Applications," EAI Transactions on Internet of Things, April 2019.
- John, G. S. Kasbekar, M. Shojaei Baghini, “Maximum Lifetime Convergecast Tree in Wireless SensorNetworks," arXiv preprint arXiv:1910.09793 (2019).
- Jorapur, V. S Palaparthy, S. Sarik, J. John, M. Shojaei Bhagini and G. K. Ananthasuresh, “A Low-Power, Low-Cost Soil-Moisture Sensor Using Dual-Probe Heat-Pulse Technique," Elsevier Sensors & Actuators: A. Physical, September 2015.
Dr. Saeed Alsamhi
Project: ROBOTLEDGER: A Decentralized Ledger System For Multiple Robot Collaborations
Saeed Alsamhi is based at the Software Research Institute at Athlone Institute of Technology, Ireland. He received his PhD and MTech degrees ..
Dr. Saeed Alsamhi
Saeed Alsamhi is based at the Software Research Institute at Athlone Institute of Technology, Ireland. He received his Ph.D. Degree and M. Tech. Degree from Indian Institute of Technology, Varanasi, UP, India in 2013 and 2016, respectively. His Ph.D. and M.Tech. research focused on the quality of service enhancement techniques in high-altitude platform-based communication networks. In 2019, Saeed worked as an assistant professor at Shenzhen Institutes of advanced technology, Chinese Academy of Sciences, Shenzhen, China. His research focused on the optimal and smart wireless network to enhance robotics technologies.
Qualifications:
- D. in Communication Engineering, Indian Institute of Technology, Varanasi, UP, India.
- Tech. in Communication Engineering, Indian Institute of Technology, Varanasi, UP, India.
- Eng in Communication Engineering, IBB University, Ibb, Yemen.
Professional Memberships and Activities:
- Assistant Professor, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
- President International Fellowship Initiative (PIFI), Chinese Academy of Sciences, China
- PostDoc, Tsinghua University, Beijing, China.
- Research assistant, Shri Mata Vaishno Devi University, India
Expertise:
- Quality of services
- Green IoT
- Multi-robot collaboration
- Drone technology
- Multi-user activity recognition
Research Interests:
- Decentralized multi-robot collaboration
- Blockchain technology
- Edge intelligence
- Machine learning
- Digital technologies and COVID-19
Selected Publications:
- H. Alsamhi, Brian Lee. “Blockchain for Multi-Robot Collaboration to Combat COVID-19 and Future Pandemics,” Accepted, IEEE Access. 2020.
- Qimeng Li, Raffaele Gravina, Ye Li, H. Alsamhi, Fangmin Sun, Giancarlo Fortino” Multi-user Activity Recognition: Challenges and Opportunities, “. Information Fusion, 2020
- H. Alsamhi, Ou. Ma, M. Samar Ansari,” Convergence of Machine Learning and Robotics Communication in Collaborative Assembly: Mobility, Connectivity, and Future Perspectives,”. Journal of Intelligent and Robotic Systems, 2019.
- H. Alsamhi, J. Liang, O. Ma, M. S. Ansari, Q. Meng. “Greening Internet of things for Smart Everything with A Green- Environment Life: A Survey and Future Perspectives,”. Telecommunication Systems, 2019.
- H. Alsamhi, O. Ma, M. S. Ansari.” Survey on Collaborative Smart Drones and Internet of Things for improving smartness of Smart Cities,”. IEEE Access, 2019.
- H. Alsamhi, F. Almalki, O. Ma, M. S. Ansari, Brian Lee. “Predictive Estimation of Optimal Signal Strength for Efficient Coexistence of Drones and IoT Frameworks in Smart Cities,” Accepted with major revision, IEEE Transaction on Mobile Computing, 2020
Dr. Ahmad Farhadi
Project: Development of a Digital Twin for High Speed Computer Controlled Drilling
Ahmad received his B.Sc. (2007) and M.Sc. (2010) in mechanical engineering (manufacturing) from Isfahan University of Technology. His deep interest in the manufacturing of aeronautical components lead ..
Dr. Ahmad Farhadi
Ahmad received his B.Sc. (2007) and M.Sc. (2010) in mechanical engineering (manufacturing) from Isfahan University of Technology. His deep interest in aeronautical component manufacture lead him to review “Superalloy machining” as an undergrad and study “Ultrasonic Assisted Creep Feed Grinding of Superalloy Inconel 738LC” in his master’s thesis. After working in an R&D role in industry for five years, he commenced his Ph.D. studies and graduated from Shanghai Jiao Tong University, China in 2020. His dissertation title was “Study on Sweep Blasting Erosion Arc Machining for fabricating open channels in turbomachinery Components” which is a novel technique to enhance machining of specific rotary components in aero-space industry.
Qualifications:
PhD. in Mechanical Engineering, Shanghai Jiao Tong University, China
- Award: Fully Funded scholarship from China Scholarship Council (CSC-A1)
- Award: Excellent International Post-Graduate Student
MSc. in Mechanical Engineering, Isfahan University of Technology, Iran
- Grade: Excellent
BSc. in Mechanical Engineering, Isfahan University of Technology, Iran
Professional Memberships and Activities:
- Member of Society of Manufacturing Engineering of Iran (SMEIR)
- Membership of American Society of Mechanical Engineers (ASME)
Expertise:
- Analytical & Numerical modelling of machining processes
- Mechanical design & Production (CAD/CAM/CAE)
- Advanced & Conventional machining technologies
- Vibration assisted MFG processes.
- Machining of hard to cut materials
- Geometric Dimensioning and Tolerancing (GD&T)
Research Interests:
- Smart Manufacturing & Industry 4.0
- Machine learning, Digital Twin & IoT
- Aerospace components production
- Novel techniques in advanced manufacturing
- Hybrid & Assisted machining technologies
Selected Publications:
- A. Farhadi, L. Gu, W. Zhao, K. Rajurkar, “Tool path optimization based on wear prediction in Electric Arc Sweep Machining”, Journal of Manufacturing Processes, 2020, Vol. 54, pp 328-336
- L. Gu, A. Farhadi, Y. Zhu, G. He, W. Zhao, K. Rajurkar “A novel tool design procedure for arc sweep machining technology”, Journal of Materials and Manufacturing Processes, 2020, Vol. 35, pp 113-121
- A. Farhadi, Y. Zhu, L. Gu, W. Zhao, “Electric Arc Sweep Milling of open channels”, The International Journal of Advanced Manufacturing Technology, 2019, Vol. 102, Issue 1–4, pp 673–683
- Y. Zhu, A. Farhadi, G. He, X. Liu, L. Gu, W. Zhao, “High-efficiency machining of large aspect-ratio rotational parts by rapid contour approaching WEDM”, The International Journal of Advanced Manufacturing Technology, 2018, Vol. 94, Issue 9–12, pp 3577–3590
- A. Abdullah, A. Farhadi, A. Pak, “Ultrasonic-assisted dry creep-feed up-grinding of superalloy Inconel738LC”, Journal of Experimental Mechanics, 2012, Vol. 52, pp 843-853
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SMART 4.0 Marie Skłodowska-Curie fellow Robotics & Control
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Iman Abaspur Kazerouni
Job Title, Role at CONFIRM, Competency:
- SMART 4.0 Marie Skłodowska-Curie fellow
- Robotics & Control
About Me:
Iman is a SMART 4.0 Marie Skłodowska-Curie fellow researcher with CONFIRM. He received both his BSc and MSc degrees in Electronic Engineering from the Hakim Sabzevari University, Iran, in 2008 and 2010 respectively. In 2014 he completed a PhD in Hakim Sabzevari University on the topic “Early breast cancer detection using thermal images”. His PhD research focused on the design of a smart system for mass detection in mammography and thermography images. He worked at the Department of Electronics and Computer Engineering (Esfarayen University of Technology) as an assistant professor since 2015. He joined the Centre for Robotics and Intelligent Systems (CRIS-University of Limerick) in 2019 as a postdoc researcher. His research interests focus on image processing, machine learning, deep learning, and robotic processing systems.
Qualifications:
- PhD in Electronic Engineering, Hakim Sabzevari University, Iran.
- MSc in Electronic Engineering, Hakim Sabzevari University, Iran.
- Eng in Electronic Engineering, Hakim Sabzevari University, Iran.
Professional Memberships and Activities:
- Postdoctoral Research Fellow, CRIS group, University of Limerick, Ireland
- Assistant Professor, Electronic and Computer Science Department, Esfarayen University of Technology, Iran
Expertise:
- Real time robots image processing
- Developing smart robotic technologies
- Medical image processing development
- Underwater robots imaging systems
Research Interests:
- Image processing
- Neural Network
- Deep Learning
- Artificial Intelligence
- Machine Vision
- Smart System Design
Selected Publications:
- I Abaspur Kazerouni, G Dooly, D Toal, Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching, Journal of Marine Science and Engineering 8 (6), 449, 2020.
- HM Hossein-Abad, M Shabanian, IA Kazerouni, Fuzzy c-means clustering method with the fuzzy distance definition applied on symmetric triangular fuzzy numbers, Journal of Intelligent & Fuzzy Systems 38 (3), 2891-2905, 2020.
- H Ghayoumi Zadeh, A Montazeri, I Abaspur Kazerouni, J Haddadnia, Clustering and screening for breast cancer on thermal images using a combination of SOM and MLP, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 5(1), 68-76, 2017.
- IA Kazerouni, J Haddadnia, A mass classification and image retrieval model for mammograms, The Imaging Science Journal 62 (7), 353-357, 2014.
Contact Details:
- Email Address: abaspur@ul.ie
- Phone Number: +353834442194
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SMART 4.0 Marie Skłodowska-Curie fellow Robotics & Control
xxxxxxxxxxxxxx
Iman Abaspur Kazerouni
Job Title, Role at CONFIRM, Competency:
- SMART 4.0 Marie Skłodowska-Curie fellow
- Robotics & Control
About Me:
Iman is a SMART 4.0 Marie Skłodowska-Curie fellow researcher with CONFIRM. He received both his BSc and MSc degrees in Electronic Engineering from the Hakim Sabzevari University, Iran, in 2008 and 2010 respectively. In 2014 he completed a PhD in Hakim Sabzevari University on the topic “Early breast cancer detection using thermal images”. His PhD research focused on the design of a smart system for mass detection in mammography and thermography images. He worked at the Department of Electronics and Computer Engineering (Esfarayen University of Technology) as an assistant professor since 2015. He joined the Centre for Robotics and Intelligent Systems (CRIS-University of Limerick) in 2019 as a postdoc researcher. His research interests focus on image processing, machine learning, deep learning, and robotic processing systems.
Qualifications:
- PhD in Electronic Engineering, Hakim Sabzevari University, Iran.
- MSc in Electronic Engineering, Hakim Sabzevari University, Iran.
- Eng in Electronic Engineering, Hakim Sabzevari University, Iran.
Professional Memberships and Activities:
- Postdoctoral Research Fellow, CRIS group, University of Limerick, Ireland
- Assistant Professor, Electronic and Computer Science Department, Esfarayen University of Technology, Iran
Expertise:
- Real time robots image processing
- Developing smart robotic technologies
- Medical image processing development
- Underwater robots imaging systems
Research Interests:
- Image processing
- Neural Network
- Deep Learning
- Artificial Intelligence
- Machine Vision
- Smart System Design
Selected Publications:
- I Abaspur Kazerouni, G Dooly, D Toal, Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching, Journal of Marine Science and Engineering 8 (6), 449, 2020.
- HM Hossein-Abad, M Shabanian, IA Kazerouni, Fuzzy c-means clustering method with the fuzzy distance definition applied on symmetric triangular fuzzy numbers, Journal of Intelligent & Fuzzy Systems 38 (3), 2891-2905, 2020.
- H Ghayoumi Zadeh, A Montazeri, I Abaspur Kazerouni, J Haddadnia, Clustering and screening for breast cancer on thermal images using a combination of SOM and MLP, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 5(1), 68-76, 2017.
- IA Kazerouni, J Haddadnia, A mass classification and image retrieval model for mammograms, The Imaging Science Journal 62 (7), 353-357, 2014.
Contact Details:
- Email Address: abaspur@ul.ie
- Phone Number: +353834442194
XXXXXXXXX
SMART 4.0 Marie Skłodowska-Curie fellow Robotics & Control
xxxxxxxxxxxxxx
Iman Abaspur Kazerouni
Job Title, Role at CONFIRM, Competency:
- SMART 4.0 Marie Skłodowska-Curie fellow
- Robotics & Control
About Me:
Iman is a SMART 4.0 Marie Skłodowska-Curie fellow researcher with CONFIRM. He received both his BSc and MSc degrees in Electronic Engineering from the Hakim Sabzevari University, Iran, in 2008 and 2010 respectively. In 2014 he completed a PhD in Hakim Sabzevari University on the topic “Early breast cancer detection using thermal images”. His PhD research focused on the design of a smart system for mass detection in mammography and thermography images. He worked at the Department of Electronics and Computer Engineering (Esfarayen University of Technology) as an assistant professor since 2015. He joined the Centre for Robotics and Intelligent Systems (CRIS-University of Limerick) in 2019 as a postdoc researcher. His research interests focus on image processing, machine learning, deep learning, and robotic processing systems.
Qualifications:
- PhD in Electronic Engineering, Hakim Sabzevari University, Iran.
- MSc in Electronic Engineering, Hakim Sabzevari University, Iran.
- Eng in Electronic Engineering, Hakim Sabzevari University, Iran.
Professional Memberships and Activities:
- Postdoctoral Research Fellow, CRIS group, University of Limerick, Ireland
- Assistant Professor, Electronic and Computer Science Department, Esfarayen University of Technology, Iran
Expertise:
- Real time robots image processing
- Developing smart robotic technologies
- Medical image processing development
- Underwater robots imaging systems
Research Interests:
- Image processing
- Neural Network
- Deep Learning
- Artificial Intelligence
- Machine Vision
- Smart System Design
Selected Publications:
- I Abaspur Kazerouni, G Dooly, D Toal, Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching, Journal of Marine Science and Engineering 8 (6), 449, 2020.
- HM Hossein-Abad, M Shabanian, IA Kazerouni, Fuzzy c-means clustering method with the fuzzy distance definition applied on symmetric triangular fuzzy numbers, Journal of Intelligent & Fuzzy Systems 38 (3), 2891-2905, 2020.
- H Ghayoumi Zadeh, A Montazeri, I Abaspur Kazerouni, J Haddadnia, Clustering and screening for breast cancer on thermal images using a combination of SOM and MLP, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 5(1), 68-76, 2017.
- IA Kazerouni, J Haddadnia, A mass classification and image retrieval model for mammograms, The Imaging Science Journal 62 (7), 353-357, 2014.
Contact Details:
- Email Address: abaspur@ul.ie
- Phone Number: +353834442194
