Lead Data Scientist in Space Technology

4+ years building AI solutions for space exploration, satellite imagery analysis, and space weather prediction. Passionate about pushing the boundaries of what's possible in space technology and AI.

4+ Years Experience
14+ Publications
20+ Posters & Presentations
4+ Awards
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Featured Projects

Space Weather

Space Weather Forecasting & Early Warnings

Developed innovative AI-based frameworks for space weather monitoring and forecasting, enhancing satellite safety and space mission planning.

Python PyTorch Time series Deep Learning Space Weather
EoFNets Paper CMEGNets Paper
Space Weather Monitoring System showing solar flare predictions and CME detection
Space Weather AI
Disaster Monitoring

Wildfire & Landslide Detection Systems

Developed DETFireNet for wildfire detection and DETSlideNet for landslide monitoring using Dual-Encoder SwinTransformer architectures. Advanced computer vision systems for scalable environmental disaster monitoring and early warning systems.

Swin Transformer Computer Vision Satellite Imagery PyTorch Remote Sensing
IGARSS 2025 IEEE JSTARS
Disaster monitoring system showing wildfire and landslide detection using satellite imagery
Disaster Monitoring AI
Attitude Determination

Advanced Star Tracker System

Developed lightweight deep learning architecture for noise removal and star centroid calculation in star tracker sensors. Optimized for deployment on embedded platforms including Xilinx KV26, Intel Movidius VPU, and NVIDIA Jetson for precise attitude determination.

Attitude Determination Deep Learning C++ Embedded Systems Intel Movidius
IEEE Paper 6-Star Tracker System
Star tracker system showing star field analysis and attitude determination
Star Tracker AI
Edge Computing

AI-based Computational Storage Systems

Developed enhanced computational storage devices employing AI-based triage for efficient data processing and storage optimisation in edge environments. Patented system for intelligent data management in space applications.

AI Triage Computational Storage Edge Computing Patent Hardware Integration
Patent IEEE Paper
3CSD computational storage architecture diagram showing AI-based data triage system
Computational Storage

Key Competencies

Technical Expertise

Computer Vision Deep Learning Predictive Analytics LLM & Generative AI CI/CD / Git / Docker / MLOps Python / Matlab PyTorch / Tensorflow Hardware-Software Integration Embedded Platforms (Xilinx, Intel Movidius, OrangePI) Edge AI Inference VHDL C/C++ Azure/Metaflow/DVC/MLflow

Leadership & Professional

Project Management Team Leadership Mentorship and Coaching Strategic Planning & Risk Management Problem-Solving Cross-functional Collaboration Technical Speaking Research & Development

Professional Experience

2023 - Present

Lead Data Scientist

Ubotica Technologies, Dublin-Ireland

  • Lead development of 3CSD software and hardware product for space and industrial applications
  • Manage data science team in creating and deploying solutions for diverse use cases
  • Develop innovative space weather monitoring and forecasting frameworks
  • Deploy and optimize AI models on embedded platforms, including Xilinx FPGAs, Intel Movidius VPUs, and Orange Pi boards
  • Mentor interns and guide professional growth in AI/ML space technology
  • Lead R&D in anomaly detection and synthetic data generation
2024 - Present

DevOps/MLOps Teacher

University of Carthage, Tunis-Tunisia

  • Educate Engineering/MSc students on DevOps/MLOps principles and practices
  • Deliver training on continuous integration, deployment (CI/CD), and automation
  • Teach MLOps techniques for integrating machine learning workflows with DevOps pipelines
  • Provide hands-on labs and practical exercises to reinforce concepts and tools through real-world scenarios

Academic Background

2018-2021

Electronics-Microelectronics Engineering

Higher Institute of Computer Science and Mathematics of Monastir

Advanced studies in electronics, microelectronics, and embedded systems

2015-2018

Bachelor's in Electronics & Telecommunications

Higher Institute of Computer Science and Mathematics of Monastir

Foundation in electronics, telecommunications, and computer systems

2011-2015

Baccalaureate in Experimental Sciences

Higher School Ibn Khaldoun Mednine

Foundation in scientific studies with focus on mathematics and physics

Professional Activities & Leadership

Current Activities

IEEE GRSS Member & Contributor

Disaster Management Working Group

Contributing to advanced disaster management solutions using satellite technology and AI

Advisory Board Member

G100: Mission Million

Providing strategic guidance for global technology initiatives and innovation programs

Tech Panelist & Speaker

Global Events (ML4H, Women4Space, IEEE)

Sharing expertise in space technology, AI, and women in STEM at international conferences

Past Contributions

Conference Co-Chair

ICSOC 2024 - AI on Edge Workshop

Led the 1st International Workshop on Optimising AI Models for Resource-Constrained Edge Devices

Session Chair

CoDiT 2024

Chaired "Efficient Training Paradigms for Edge Devices: Balancing Memory and Time Constraints"

Mentor & Reviewer

ML4H, Climate Change AI, Teens in AI

Mentored students and reviewed papers for Machine Learning for Health Conference (2023-2024)

Awards & Publications

Best Paper Award

SRC24, UAE Space Agency

Position, Navigation, and Timing (PNT) Track

2024

Best Industrial Paper Award

ICSOC 2024

Visual Anomaly Detection in Industrial Systems

2024

Best MLOps Poster Award

Deep Learning Indaba 2024

3CSD Edge MLOps (Poster ID: 120, Session: 168)

2024

IADF Travel Grant Award

IADF School 2025

Machine Learning for Earth Observation

2025

System and Method for Actively Triaging Data in a Computational Storage System Deployed in an Edge Environment

Co-authored by Guesmi, B.

US Patent US20250118052A1

Computational Storage Edge Computing Data Triage AI Optimization System Architecture
View Patent

OilSpillNets: Detecting and Estimating Oil Spills using Fusion

Guesmi, B., et al.

Springer Journal

Oil Spill Detection Sensor Fusion Marine Monitoring Environmental AI Remote Sensing
Springer Link

Enhanced Computational Storage Device Employing AI-based Triage

Guesmi, B., et al.

ESA EDHPC 2023

Computational Storage AI Triage Edge Computing Data Optimization Hardware Acceleration
IEEE Xplore

EoFNets: EyeonFlare Networks to Predict Solar Flare using Temporal Convolutional Network (TCN)

Guesmi, B., et al.

CoDiT 2024

Solar Flare Prediction Temporal Convolutional Networks Space Weather Time Series Deep Learning
IEEE Xplore

Visual Anomaly Detection in Modern Industrial Manufacturing Systems: Survey, Challenges and Future Directions

Co-authored by Guesmi, B.

Springer Chapter - Best Industrial Paper Award

Anomaly Detection Computer Vision Industrial AI Survey Manufacturing
Springer Link

Hardware-aware Deep Learning Approaches for Image Denoising and Star Detection for Star Tracker Sensor

Guesmi, B., et al.

CoDiT 2024

Star Tracker Image Denoising Hardware-aware AI Embedded Systems Space Navigation
IEEE Xplore

Maximizing Celestial Awareness: 6-Synchronized-Star-Trackers for Attitude Determination

Co-authored by Guesmi, B.

ESA SPAICE 2024

Star Tracker Attitude Determination Space Navigation Sensor Fusion Celestial Awareness
ADS Abstract

The Use of AI in Operational Space Weather Missions

Co-authored by Guesmi, B.

AMS Conference 2024

Space Weather Operational AI Satellite Safety Mission Planning Real-time Systems
ADS Abstract

Balancing Accuracy and Efficiency: Navigating The Trade-off Between Machine-Readable Code Detection and Data Size Reduction

Co-authored by Guesmi, B.

CoDIT 2025 - Under Publication

Code Detection Data Compression Efficiency Trade-off Machine Learning Optimization
Coming Soon

DETSlideNet: Dual-Encoder SwinTransformer for Scalable Landslides Detection & Monitoring

Guesmi, B., et al.

IEEE TGRS - Under Publication

Landslide Detection Swin Transformer Dual-Encoder Remote Sensing Disaster Monitoring
IGARSS 2025

CMEGNets: A Self-Supervised Framework for Coronal Mass Ejections (CMEs) Classification & Detection

Guesmi, B., et al.

Advances in Space Research - Under Publication

Coronal Mass Ejections Self-Supervised Learning Space Weather Solar Physics Graph Neural Networks
Coming Soon

EoFTCNets: Efficient Solar Flare Forecasting using 3D Temporal Convolutional Networks (3TCN)

Guesmi, B., et al.

Advances in Space Research - Under Review

Solar Flare Forecasting 3D TCN Time Series Space Weather Deep Learning
Under Review

DETFireNet: Dual-Encoder SwinTransformer for Scalable Wildfire Detection & Monitoring

Guesmi, B., et al.

IEEE J-STARS - To be published

Wildfire Detection Swin Transformer Dual-Encoder Satellite Imagery Environmental Monitoring
Coming Soon

MSSD Framework: MSSD-Net for Marine Surface Debris Detection Using Transformer & MSSD-App for Early Warnings

Co-authored by Guesmi, B.

IEEE J-STARS - To be published

Marine Debris Transformer Early Warning Ocean Monitoring Environmental AI
Coming Soon

Professional Recommendations

Silvia Liberata Ullo

IET Image Processing Editor in Chief. IEEE Senior Member. IEEE GRSS AdCom Member, Europe Liaison, IADF TC Member. IEEE AESS Italy Chapter Chair. Networld Europe Steering Board Member.

September 30, 2025 · Worked with Besma but on different teams

"Happy to have collaborated with Besma Guesmi on our IEEE GRSS research in disaster management. Besma demonstrated excellent skills in data analysis and a strong motivation to apply remote sensing for real-world impact. Her analytical rigor and collaborative spirit were key to the success of our papers. I have no doubt she will continue to thrive in her research endeavors. Besides the scientific skills I appreciate her soul, unique and special, and her ability to teamworking and handling several tasks achieving all objectives."

Excellent Skills in Data Analysis and Collaborative Spirit

Habib Fathallah

Professor ITC, University of Carthage, Senior Member IEEE/OSA

May 31, 2025 · Worked together on the same team

"Besma Guesmi recently delivered a comprehensive DevOps course to our Software Engineering & AI students, and the feedback has been overwhelmingly positive. Her engaging teaching style, effective pedagogy, and masterful balance between fundamental concepts and practical hands-on work were highly appreciated by all. Furthermore, her mastery of state-of-the-art technologies ensured that students were learning the most current and relevant practices, and she brilliantly showcased practical implementations of machine learning in various industrial settings. Besma's dedication truly made a difference in the students' learning experience. Very Highly recommended!"

A Stellar DevOps Educator!

David Moloney

CTO/Chief Scientist, PhD AI HW/SW - Ubotica Technologies

November 22, 2021 · Managed Besma directly

"Besma approached me about an internship with Ubotica and was so insistent that she wanted to work for us that it was impossible to say no. Even though still an undergraduate she took on a very challenging project to implement a star-tracker using novel deep-learning techniques. She brought a very open and enthusiastic approach to her work at all times and performed exceptionally well despite never having met me face to face because of the pandemic. She did everything from researching SoTA star-tracking algorithms to assembling training data-sets and training the deep-networks singlehandedly. She also evaluated a variety of tools that were not known to the Ubotica team and ported the code to several embedded platforms during her six month internship. This scope of work would have been a challenge even for a senior engineer. Besma is an exceptional talent with a very inquisitive mind and keen intellect who will go far in her chosen profession. I'm glad to have her as a permanent member of my team."

Exceptional Talent with Keen Intellect

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