Prafull Ahire

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Prafull Ahire

Electronics and Telecommunication Engineering · University of Mumbai

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Projects

Certified

Self-directed project

Machine Learning for Automotive Safety

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

84/ 100

A ProoV case study · educational project, not employment

A verified, self-directed Perception Validation Engineer (ADAS Safety Sign-off) project — completed and passed a real industry rubric at 84/100 on ProoV.

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
  • Correctly locked the detection definition at IoU >= 0.5 and computed the worked example IoU as 0.111, classifying it as a miss.
  • Computed and interpreted the key safety metric correctly: VRU recall 0.76 and VRU false-negative rate 0.236, rather than relying on headline accuracy.
  • Produced a strong condition-sliced analysis showing night recall collapse (0.39) and worst-case night+occluded recall (0.27).
  • Wrote an internally consistent GO-WITH-CONDITIONS verdict that cites the dossier's own numbers and ties the real Uber Tempe crash to the night-time pedestrian miss.
  • Data-Driven Decision Making
  • Statistical Analysis
The work I submitted20 tasks

12 tasks · 17.6k characters · Python · 8 written answers · 845 words

  • Sensor Match553 characters
  • Task Definition378 characters
  • Example Iou Demo1.5k characters
  • Task Definition Code1.1k characters
  • Example Metrics DemoPython · 2.2k characters
  • Scored Metrics RunPython · 2.3k characters
  • Scored Metrics351 characters
  • Ttcs Example SlicePython · 1.3k characters
  • Ttcs Triage SlicePython · 1.6k characters
  • Failure Triage1.8k characters
  • Sotif Case3.2k characters
  • Ship Verdict1.3k characters
  • Sensor Match27 words
  • Task Definition42 words
  • Example Iou Demo169 words
  • Task Definition Code149 words
  • Example Metrics Demo154 words
  • Scored Metrics Run143 words
  • Scored Metrics18 words
  • Ttcs Example Slice143 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

AI / ML · June 2026

84/ 100

A ProoV case study · educational project, not employment

A verified, self-directed industry project — completed and passed a real industry rubric at 84/100 on ProoV.

Graded against

  • Exploratory Data Analysis20%
  • Feature Engineering25%
  • Model Building & Evaluation35%
  • Business Communication20%

Passed · pass mark 60/100

What stood out6
  • Combined VW and Audi data correctly with a brand indicator and explored cross-brand pricing differences.
  • Identified key pricing drivers such as age, mileage per year, and brand premium in the business summary.
  • Produced a clear executive-style recommendation tied to operational workflow and financial impact.
  • Exploratory Data Analysis
  • Feature Engineering
  • Model Evaluation
The work I submitted10 tasks

5 tasks · 6 lines · 5 written answers · 165 words

  • VW Sprint1 Complete56 characters
  • VW Sprint2 Complete61 characters
  • VW Sprint3 Complete59 characters
  • VW Business Insights1.6k characters
  • Jupyterlite Code2 lines
  • VW Sprint1 Complete1 word
  • VW Sprint2 Complete1 word
  • VW Sprint3 Complete1 word
  • VW Business Insights161 words
  • Jupyterlite Code1 word

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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