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Built an ML pipeline to predict peptide toxicity from amino-acid sequences using 438 engineered features (AAC, DPC, physicochemical properties) and evaluated 8 classifiers
A hardware-aware, autonomous LLM inference runtime that uses learned policies to optimize model configuration (pruning/quantization) for latency and perplexity
Python
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