feat: ajouter des tailles et des améliorations de style aux composants Skills, Stats, StatusPage, Education et Experiences

content/contact.json

@@ -2,7 +2,7 @@
   "body": [
     {
       "id": "personal-email",
-      "name": "Email Personnel",
+      "name": "Personal Email",
       "category": "communication",
       "icon": "i-ph-envelope-simple-duotone",
       "value": "https://go.arthurdanjou.fr/mail-perso",
@@ -10,7 +10,7 @@
     },
     {
       "id": "professional-email",
-      "name": "Email Professionnel",
+      "name": "Professional Email",
       "category": "communication",
       "icon": "i-ph-envelope-simple-duotone",
       "value": "https://go.arthurdanjou.fr/mail-pro",
@@ -51,7 +51,7 @@
     },
     {
       "id": "personal-website",
-      "name": "Site Personnel",
+      "name": "Portfolio",
       "category": "web",
       "icon": "i-ph:globe-duotone",
       "value": "https://arthurdanjou.fr",
@@ -59,7 +59,7 @@
     },
     {
       "id": "status-page",
-      "name": "Statut des Services",
+      "name": "Status Page",
       "category": "infrastructure",
       "icon": "i-ph:fire-duotone",
       "value": "https://go.arthurdanjou.fr/status",

content/education/doctorate.md

@@ -1,10 +1,10 @@
 ---
-title: PhD Candidate: AI Safety & Mathematical Robustness
+title: "PhD Candidate: AI Safety & Mathematical Robustness"
 degree: Doctorate
 institution: Academic Labs
 location: Paris / International
 startDate: 2026-10
-endDate: undefined
+endDate: null
 duration: 3 years
 description: I am actively seeking a PhD position starting in Fall 2026. My research interest lies at the intersection of Applied Mathematics and Deep Learning, specifically focusing on AI Safety, Adversarial Robustness, and Formal Verification. I aim to contribute to developing mathematically grounded methods to ensure the reliability and alignment of modern AI systems.
 tags: