Aditya Khandelwal
Aditya Khandelwal [AI]

Aditya Khandelwal

Aditya Khandelwal is a member of technical staff at Amazon AGI Lab, where he works on real-time multimodal agents, computer-use systems, evaluation infrastructure and engineering workflows for dependable AI agents.

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    Video topic coverage

    Based on 1 reviewed video for Aditya Khandelwal; compared with all 2934 public reviewed videos. Catalogue coverage, not expertise or speaking time.

    Unmapped topics: 0 for this person; 17 in all videos. Scores cover mapped topics only.

    • Aditya Khandelwal (1 video; normalised to 100%)
    • All videos (2934; normalised to 90%)

    Both plots connect neighbouring topic values in the same ten-axis order, including zeros at the centre. The blue person plot is proportionally normalised to a 100% maximum and the white baseline to 90%. Each plot uses its own scale, showing relative topic emphasis; the values below show actual coverage.

    • Agents & workflows100%56%
    • Coding & tools100%38.7%
    • Models & learning0%37.2%
    • Infrastructure & compute0%21.9%
    • Research & evaluation0%38.4%
    • Safety & security0%29%
    • Business & productivity100%26.5%
    • Creative & media0%6.7%
    • Robotics & perception0%5.2%
    • Society & policy0%17.2%
    Topic attribution

    Both datasets use the same explicit fractional topic memberships. For each video, only the strongest membership in each group counts. We average those values across distinct public reviewed videos, including untagged videos. The all-video baseline includes this person's videos. Both datasets come from the same active catalogue snapshot and are independent of filters and viewing history. Groups overlap, so percentages do not need to total 100. Weights describe topic membership, not measured speaking time or relationship confidence.

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    Aditya Khandelwal's profile portrait beside their name and relative topic-coverage shape.

    Aditya Khandelwal is a member of technical staff at Amazon AGI Lab, where he works on real-time multimodal agents, computer-use systems, evaluation infrastructure and engineering workflows for dependable AI agents.

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