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General Information

Name Fiza Husain
Location Bangalore, India
Focus Speech AI, applied machine learning, model serving and evaluation

Experience

  • Founding Machine Learning Engineer Stimuler
    2025 — present
    • Own the production speech stack end to end — automatic speech recognition, text-to-speech, and speech-to-speech — for a conversational English-fluency platform serving learners across India, Indonesia, and Latin America.
    • First author of the INTERSPEECH 2026 paper introducing entity- and disfluency-aware evaluation for accented conversational ASR, raising entity recall from 53–55% to 80–85% and filler recall from under 5% to 76–86%.
    • Fine-tuned and deployed region-specific LoRA adapters on audio language models for non-native English speech, served through vLLM at sub-second P95 latency.
    • Built and scaled a low-latency streaming text-to-speech service on Ray Serve and Anyscale, including multi-model GPU partitioning and autoscaling.
    • Designed the evaluation systems behind the stack — LLM-as-judge pipelines validated against human labels, error taxonomies, and metric hierarchies for conversational quality.
  • Research Fellow M365 Research, Microsoft
    2023 — 2025
    • Published research on intelligent monitoring and cloud operations, including first-author work at FSE Industry 2026 and co-authored papers at FSE 2024 and ICSE-SEIP 2024.
    • Developed foundation-model approaches to monitor configuration and incident prediction over large-scale operational telemetry.
    • Built statistical frameworks used to identify faulty, redundant, and misconfigured monitors across production cloud services.
  • Analyst Goldman Sachs
    2022 — 2023
    • Optimised a real-time graph pricer with market data subscription capabilities, improving data-driven pricing behaviour.
    • Worked on the Halo pricing model for rapid response to underlyer price changes in securitized derivatives.
  • Undergraduate Researcher Machine Learning Lab, IIIT Hyderabad
    2020 — 2022
    • Research student with Prof. Praveen Paruchuri and Prof. Sujit Gujar on privacy and generalization in deep reinforcement learning.
    • Developed a Privacy-Aware Inverse Reinforcement Learning analysis framework, published at AAAI 2022.

Education

  • B.Tech (Honours), Computer Science and Engineering International Institute of Information Technology, Hyderabad
    2018 — 2022
    • GPA 8.8 / 10.0

Selected Publications

  • Beyond WER: Entity and Disfluency Recall in Accented Conversational ASR. INTERSPEECH 2026 · first author
  • Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems. FSE Industry 2026 · first author
  • X-lifecycle Learning for Cloud Incident Management using LLMs. FSE 2024
  • Intelligent Monitoring Framework for Cloud Services. ICSE-SEIP 2024
  • How Private Is Your RL Policy? An Inverse RL Based Analysis Framework. AAAI 2022
  • Full list with links on the publications page.

Patents

  • Monitor class recommendation framework. United States patent application 18/593,338, 2025
    Anjaly Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan, Pooja Srinivas, Fiza Husain

Technical Skills

  • Machine learning
    • LLM and audio-model fine-tuning (LoRA, DPO)
    • Speech AI — ASR, TTS, speech-to-speech
    • Evaluation systems and LLM-as-judge
    • Reinforcement learning
  • Serving and infrastructure
    • Ray Serve, Anyscale, vLLM, SGLang, Modal
    • Streaming and distributed inference
    • Docker, Kubernetes, AWS, GCP, BigQuery
  • Frameworks
    • PyTorch, Transformers, PEFT, Hugging Face
    • Weights & Biases
  • Languages
    • Python, C++, SQL