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Mihir Trivedi
Junior Machine Learning & Quant Research Engineer specializing in low-latency data and trading systems
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About
Applied ML to physical EV fleet systems at ST Labs, building a real-time CNN-LSTM fault prediction pipeline from streaming vehicle telemetry and addressing live data alignment issues via resampling/interpolation and buffered inference. Also developed a V2G/G2V energy transfer algorithm to automate charging/discharging for profit optimization, and made high-impact low-latency pipeline decisions at Astera Holdings using profiling, replay testing, and live A/B validation.
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Key Strengths
- Built real-time AI fault prediction system for EV fleets using CNN-LSTM on live sensor streams
- Solved live data misalignment by resampling to 1-second intervals with interpolation and buffered inference windows
- Latency troubleshooting and architecture decision-making under ambiguity (profiling, throughput simulation, bottleneck isolation)
- Rigorous validation approach (historical replay at 5x speed, consistency checks, live A/B testing)
- Designed V2G/G2V energy transfer algorithm to automate charge/discharge for user profit
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2 publications
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