Muhammad Wali

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Muhammad Wali

Robotics, Computer Science · Beaconhouse College

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Projects

Certified

Self-directed project

AI-Assisted Code Modernization with IBM

Junior Software Engineer · Software Engineering · August 2026

84/ 100

Based on a public IBM case study · not affiliated with IBM

Built a solid modernization pass for a legacy fleet-maintenance service: fixed the wear calculation so nearly-worn cars are flagged, handled missing service readings safely, corrected the nightly report’s average and crash behavior, and repaired a hidden mileage-conversion bug in the helpers. Also documented the review process in NOTES.md and described a data-driven breakdown-risk analysis that prioritizes km-since-service and driving intensity over total mileage.

Graded against

  • Fix and extend the repo with the agent35%
  • Diagnose the bug20%
  • Direct and audit the AI agent25%
  • Explain it like an engineer20%

Passed · pass mark 60/100

What stood out6
  • Correctly identified the floor-division bug at the exact wear calculation line and explained the consequence for a nearly-worn car.
  • Caught the quiet helper-module mileage conversion bug that no test directly covered, which is strong evidence of a real codebase sweep.
  • Wrote a detailed NOTES.md describing what the agent got wrong and how they verified the fixes with acceptance checks.
  • Kept the service interval and warning threshold unchanged while fixing the surrounding logic.
  • Leakage-Free Feature Engineering
  • Honest Model Evaluation

The deliverable

View the codemrmuhammadwali189-cmyk / proov-km-waechter-fix
The work I submitted18 tasks

10 tasks · 1.8k characters · JavaScript · 8 written answers · 181 words

  • Division Predict72 characters
  • Diagnose Line130 characters
  • Diagnose Why82 characters
  • Scope Prompt66 characters
  • Bob Trial Click74 characters
  • Bob Ready60 characters
  • Template Repo Click82 characters
  • Exec PitchJavaScript · 986 characters
  • Bob Bonus148 characters
  • Repo URL63 characters
  • Division Predict1 word
  • Diagnose Line10 words
  • Diagnose Why15 words
  • Scope Prompt1 word
  • Bob Trial Click1 word
  • Bob Ready1 word
  • Template Repo Click1 word
  • Exec Pitch151 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

Machine Learning for Automotive Safety

Perception Validation Engineer (ADAS Safety Sign-off) · AI / ML · August 2026

84/ 100

A ProoV case study · educational project, not employment

Built a perception-validation analysis that correctly defined detection matching with IoU, computed aggregate precision/recall plus the safety-critical VRU false-negative rate, and then stress-tested performance by condition. The work surfaced a sharp night-and-occlusion recall collapse and translated it into a clear risk signal for vulnerable road users.

Graded against

  • Detection metrics correctness (precision, recall, VRU false-negative rate)30%
  • Failure-mode analysis & per-condition rigour25%
  • SOTIF safety case quality (ISO 21448 reasoning)25%
  • Ship verdict — evidence-based & internally consistent20%

Passed · pass mark 60/100

What stood out6
  • Computed IoU on a worked box pair and applied the 0.5 match threshold correctly.
  • Derived aggregate precision, recall, and VRU false-negative rate from the synthetic scored table with correct formulas.
  • Sliced VRU recall by lighting, visibility, and rarity, revealing the severe night and occluded performance drop.
  • Identified the worst combined slice (night + occluded) and quantified its recall collapse clearly.
  • Leakage-Free Detection Definition
  • Honest Metric Evaluation
The work I submitted10 tasks

5 tasks · 8.9k characters · Python · 5 written answers · 721 words

  • Example Iou Demo1.5k characters
  • Example Metrics DemoPython · 2.2k characters
  • Scored Metrics RunPython · 2.3k characters
  • Ttcs Example SlicePython · 1.3k characters
  • Ttcs Triage SlicePython · 1.6k characters
  • Example Iou Demo169 words
  • Example Metrics Demo154 words
  • Scored Metrics Run143 words
  • Ttcs Example Slice143 words
  • Ttcs Triage Slice112 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
2Projects completed
2Verified certificates
84Average score
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