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.

 

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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

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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

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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.