Hardik Srivastava

About Hardik Srivastava

An MS in Data Science student at the University of Washington, pursuing advanced research in Natural Language Processing (NLP), advised by Prof. Zaid Harchaoui. Currently working as a Graduate Research Assistant at the Paul G. Allen School of Computer Science & Engineering, engaging in building Transformer-based NLP systems using attribution-guided modeling for interpretable text generation. Research focuses developing an inference-time multi-agent orchestration framework for controllable text style transfer to anonymise text authorship to protect user privacy by leveraging parameter-efficient adaptation methods like LoRA.Formerly an Applied Scientist 2 at JPMorgan Chase, contributed to developing scalable, production-grade machine learning systems for fraud prevention, including contrastive learning for text correction, autoregressive Transformer-based OCR models, Graph Neural Networks, and explainability pipelines. Published work in ACL, and other venues, with research spanning NLP, joint-representational learning, human-centered AI, HCI, and fairness-aware AI.Skills: C++, Java, Python, SQL, ML, Quantization, Big Data, Spark, Kafka, PyTorch, TensorFlow, Caffe, MLFlow, Generative Ai, Large Language Models, RAG, TFX, AWS, Kubernetes, Kubeflow, Jenkins, Unit Testing.

Experience

1. Graduate Research Assistant

   Paul G. Allen School Of Computer Science & Engineering

   Sep 2025 — Present · Seattle, WA, US

   Advised by Prof. Zaid Harchaoui in the WAIL (Washington AI Lab) group- Researching on how LLMs make decisions in text generation and developing advanced methods using attribution-guided modeling to steer outputs toward desired behavior- Developing methods for enhancing user privacy in text by fine-tuning LoRA adapters and using constrained decoding techniques to obfuscate text authorship while preserving meaning, style, and user control.

Education

• SRM IST Chennai

  Bachelor of Technology - BTech, Computer Science Engineering with specialization in Big Data Analytics

  2019 — 2023

• University of Washington

  Master of Science - MS, Data Science