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Dr. Anas Neumann, Optimization, Best Researcher Award

Doctorate at Polytechnique Montréal / Université Laval, Canada


Dr. Anas Neumann is a highly skilled researcher and educator with expertise in artificial intelligence, optimization, and deep learning. He holds a Ph.D. in Administration with a specialization in Operations and Decision Systems from Université Laval. Throughout his academic journey, Dr. Neumann has demonstrated a strong commitment to advancing knowledge and solving real-world problems through innovative research and practical applications.

With over seven years of experience as an Assistant Lecturer at FSA ULaval, Dr. Neumann has played a significant role in teaching algorithmic and data-related courses, preparing students for the challenges of modern industry. Additionally, his tenure as an AI, optimization, and deep learning researcher at CIRRELT has enabled him to contribute to cutting-edge research projects, leveraging machine learning techniques to address complex problems in various domains.

Professional Profile:

Scopus Profile

Google Scholar Profile

👩‍🎓Education & Qualification:

Post-doctorate in Deep Learning

  • Institution: Polytechnique Montréal
  • Duration: September 2023 – September 2024

Ph.D. in Administration, Operations, and Decision Systems (ODS)

  • Institution: Université Laval
  • Duration: January 2019 – June 2023
  • Scholarships: Ulaval/FSA Scholarship of Excellence, NSERC Scholarship in partnership with Genius Solutions

Bachelor of Computer Science and Mathematics (1st year), Computer Science

  • Institution: Université d’Évry
  • Duration: 2010 – 2011

Professional Experience:  

Dr. Anas Neumann has a diverse professional experience spanning academia, research, and software development:

Assistant Lecturer at FSA ULaval (September 2019 – Present):

  • Responsibilities include teaching algorithmic and data-related topics in various courses such as Integrated Management Systems, Production Planning and Control, Operations and Logistics in the era of Industry 4.0, and Mathematical Programming and Optimization.
  • Actively involved in course development, delivering lectures, conducting workshops, and participating in faculty meetings.

AI, Optimization, and Deep Learning Researcher at CIRRELT (March 2017 – Present):

  • Engaged in research activities focusing on artificial intelligence, optimization techniques, and deep learning.
  • Conducts research independently and collaboratively, contributing to projects aimed at addressing real-world challenges.
  • Manages and contributes to various research projects, with a particular emphasis on machine learning applications.

Freelance Web Developer at uprodit.com (January 2018 – January 2019):

  • Worked as a freelance web and mobile developer, participating in the creation of several projects.
  • Involved in the development of websites and mobile applications, contributing to project planning, design, implementation, and deployment.

Lecturer at Institut Supérieur des Arts Multimédia de la Manouba (ISAMM) (January 2018 – July 2018):

  • Taught “Video game development with C# and Unity3D” class, providing instruction and guidance to students on game development techniques.
  • Contributed to curriculum development and course delivery, fostering a conducive learning environment for students.

Student Internship / Full-stack Web and Mobile Developer at FSA ULaval (March 2017 – August 2017):

  • Participated in a student internship focusing on full-stack web and mobile development.
  • Collaborated with a team to develop sustainable web applications, gaining hands-on experience in software development methodologies.

Dr. Anas Neumann’s professional journey reflects a strong commitment to both academia and practical application, with a focus on teaching, research, and software development in the fields of artificial intelligence, optimization, and deep learning.

Research Interest:

Algorithmic and Data Sciences: He explores novel algorithms and methodologies for optimization, mathematical programming, and data analysis to improve decision-making processes and operational efficiency.

Deep Learning and Neural Networks: Dr. Neumann investigates deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models, for tasks such as natural language processing, image recognition, and sequence prediction.

Meta-Learning and Transfer Learning: He explores meta-learning and transfer learning techniques to adapt pre-trained deep learning models for specific industrial applications, enabling automatic customization and configuration based on customer needs and preferences.

Operations and Logistics in Industry 4.0: Dr. Neumann examines the integration of advanced technologies, such as AI, IoT, and big data analytics, into production planning, supply chain management, and logistics operations to enhance efficiency and responsiveness in the era of Industry 4.0.

Applied AI and Industry Collaboration: He collaborates with industry partners to apply AI and optimization techniques to real-world problems, contributing to the development of innovative solutions and improving business processes.

Publication Top Noted:

Title: A model for advanced planning systems dedicated to the Engineer-To-Order context

  • Journal: International Journal of Production Economics
  • Volume: 252
  • Pages: 108557
  • Year: 2022
  • Citations: 7

Title: A Didactic Review On Genetic Algorithms For Industrial Planning And Scheduling Problems

  • Journal: IFAC-PapersOnLine
  • Volume: 55
  • Issue: 10
  • Pages: 2593-2598
  • Year: 2022
  • Citations: 6

Title: Genetic algorithms for planning and scheduling engineer-to-order production: a systematic review

  • Journal: International Journal of Production Research
  • Volume: 62
  • Issue: 8
  • Pages: 2888-2917
  • Year: 2024
  • Citations: 4

Title: A Two-Level Optimization Approach For Engineer-To-Order Project Scheduling

  • Journal: IFAC-PapersOnLine
  • Volume: 55
  • Issue: 10
  • Pages: 2587-2592
  • Year: 2022
  • Citations: 3

Title: Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm

  • Journal: International Journal of Production Economics
  • Volume: 267
  • Pages: 109077
  • Year: 2024
  • Citations: 2
Anas Neumann | Optimization | Best Researcher Award

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