Mohammad Mohammadpour | Motion planning | Best Researcher Award

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

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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

 

 

sofia aftab | Neural network | Best Researcher Award

 Ms. sofia aftab | Neural network | Best Researcher Award

Ms. Norges Teknisk-Naturvitenskapelige Universitet, Norway

👩‍🔬 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.🌟

Profile

Scopus

 

 

Scholar

 

🎓📚Academics

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

 

💼📊Career 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

🏢💼Experience

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 Protégé 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 📝

  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

👩‍🔬 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

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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.