My name is Fadoua Ghourabi. I am from the Republic of Tunisia in North Africa. I came to Japan to pursue my Master’s and Ph.D. degrees.
I have more than 10 years of research experience in the fields of formal logic and symbolic computation with application to “Computational Origami”.
I have pursued my research activities at the University of Tsukuba, Kwansei Gakuin University and Ochanomizu University. At Ochanomizu University, I formed a “Data Science Study Group” with students from various departments and focused on data engineering and machine learning algorithms.

Q1 /
Why I joined AWL?

The Company Vision
to challenge the limits of technology

I joined AWL in September, 2019 and now a Group Manager in the AWL Trainer Group. I was in the world of Academia. After participating in the “Data Science Festival” in Munich, Germany where I learned more about practical applications of AI-related fields in the industry, my research interests have been more attuned to the business world.
I had a couple of interviews with AI companies in Japan. During the interview with AWL, the CTO explained the concept of the AI model development tool “AWL Trainer”. I knew that this venture company has a realistic expectation of AI, knows the limitations, and has a vision of how to overcome them.
Consequently, I joined AWL, now a leading Edge AI Solutions Company.

Q2 /
What’s the best thing about AWL?

The extreme effort
that goes into meeting every client’s needs.

The shortage of labor due to the aging society, Japanese retail stores are facing the challenge of maintaining their high quality service. My team is developing AI models that help retail stores get valuable insights into their customers’ needs and how to perform their operations with greater efficiency and more automation.
Since joining AWL I have gained experience in customizing AI development, systems for particular needs. I have more knowledge of various techniques and approaches. I am very passionate to lead my team to exceed our clients’ expectations.

Q3 /
Future challenges

Business applications,
more accessible and more practical.

One tool that has made incredible progress in AI in the last 10 years or so, is “Supervised Deep Learning”. This is to take thousands of images, annotate them by indicating of what information they contain, so that the deep learning algorithm can “learn” to recognize new samples of similar images.
However, the preparation of data is cumbersome and expensive. Can’t AI learn by itself just like humans do? Several approaches can be pursued, such as “Unsupervised Learning” with no annotated data, “Few-shot Learning” with very little input data, or logical reasoning and cognition where the machine is programmed to imitate human thinking abilities. Currently, the area we are studying still has less studies. However, I believe AWL team can develop practical business applications by exploring these areas. In the future, I dream to launch “AWL Tunisia” and expand our business in Africa and the Middle East.

A typical day at AWL

9:00 am

Arrive at the office

Start up the device in the demo room being worked on.
Reply to the messages.

9:30 am

Start work

Prepare demonstration for a client.

10:15 am

Team meeting

Discuss a plan to mount a new AI model to an edge device.

11:15 am


Face-to-face discussion with team members.

12:00 pm


1:00 pm

Back to work

Research on CG data, etc.

3:30 pm

Regular meeting

Share and discuss the status of each project.

4:00 pm


Discuss R&D activities
with members of AWL Vietnam.

5:00 pm


Regular meeting to discuss ongoing PoC projects.

6:00 pm


Discuss ongoing AI development with
Prof. Biplab of Indian Institute of Technology Bombay (IIT Bombay).

7:00 pm

Finish working

What I do in my free time?

My family and I enjoy visiting the mountains and rivers to get in touch with nature. Stopping in to see the owners and regular customers at one of the many friendly local restaurants is also what I like to do. After a long day, I take a steaming hot bath to refresh / rejuvenate myself.

Message to those interested in joining AWL

You may need to adjust the mindset from Academia to Business. However, for those who are coming from an academic and research background, at AWL there are opportunities for research projects, collaboration and publishing. Furthermore, it is fun to meet and work with people from around the world. Join in the challenge together with us at AWL!

Interviews with other employees

Fadoua Ghourabi

Joined September, 2019
AWL Trainer Group

Joshua Ezekiel Sambo

Joined April, 2020
AWL Trainer Group

Eduardo Narvaez Fuertes

Joined April, 2020
Core Engine Group

Emerico Habacon Aguilar

Joined September, 2021
Core Engine Group

Moorthy Babu Sridhar Babu

Joined April, 2020
AI Applications Group