Help & Supportcareers@gravityer.com
Computer Systems Engineer | Doctoral Researcher (Ph.D Student) at INSA Strasbourg
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
INSA Strasbourg
Data Scientist
June 28, 2026 – Present
BAD-BatteryAnomalyDetection
April 7, 2026 – Present
Toward Early Battery Anomaly Detection: Deep Learning Framework for Lithium- Ion Batteries
View ProjectAnomaly-Detection-in-Multi-Rate-CNC-Machining
February 25, 2026 – Present
Anomaly-Detection-in-Multi-Rate-CNC-Machining — GitHub repository
View ProjectOntology-Guided-LLM-for-Battery-Information-Extraction
December 14, 2025 – December 14, 2025
Ontology-Guided-LLM-for-Battery-Information-Extraction — GitHub repository
View ProjectSNN-model-for-SOH-estimation
May 13, 2025 – Present
SNN-model-for-SOH-estimation — GitHub repository
View ProjectCounterfactual-Explanation-Validation-Ontology
October 3, 2024 – April 9, 2025
This repository contains the code and supplementary materials for the paper: Counterfactual Explanation Generation for Multivariate Time Series Forecasting. The work introduces innovative methods (GENO-TOPSIS and NSGA-II) and an ontology-based validation framework (CEVO) to enhance the explainability of deep learning models.
View ProjectEnergetic-project-2
April 15, 2024 – August 26, 2024
Applaying the growing window technique to estimate the entire cuvrve of soh unitl it reach the end of life using a transformer model
View ProjectDataset-for-real-driving-cycles
February 20, 2024 – October 21, 2024
Code and models for estimating the State of Charge (SoC) and of battery cells. Utilizing advanced deep learning techniques.
View ProjectEnergitic-project-1
November 30, 2023 – October 23, 2024
This study pioneers E-LSTM and CNN-LSTM deep learning models for precise Lithium-Ion Battery State of Health (SOH) prediction. Using MIT's battery dataset, our interpretable models, enhanced by Shapley Additive exPlanations and pattern mining, offer promising results.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in the domain of battery technology and anomaly detection, which indicates a deep specialization. While this shows dedication, it suggests a potentially narrow breadth of experience outside this specific niche. The target role is 'Data Scientist', which is broad, and the candidate's profile aligns well with the technical aspects of data science, particularly in time series analysis and deep learning. However, the lack of diverse project domains or team-based projects makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a strong technical focus and ability to work on complex problems independently.