Curriculum Vitae
Education
Ph.D. in Software Engineering, Minor in ECE
University of Arizona
Advisors: Prof. Bo Liu (RL Turing Award Lab) and Prof. Janet Roveda (BME).
Research focus: AI Safety, Alignment, Reinforcement Learning, Agentic AI, AI for Science & Healthcare.
University of Arizona
Advisors: Prof. Bo Liu (RL Turing Award Lab) and Prof. Janet Roveda (BME).
Research focus: AI Safety, Alignment, Reinforcement Learning, Agentic AI, AI for Science & Healthcare.
M.S. in Economics and Computer Science; Master of
Management Studies
Duke University
GPA: 3.8/4.0 (Top 10% Fuqua Scholar)
Duke University
GPA: 3.8/4.0 (Top 10% Fuqua Scholar)
Bachelor of Science (Hons)
Oxford Brookes University
Oxford Brookes University
Work Experience
Aug 2025 – Present
AI Engineer III,
OPPO US Research Center
- Led AI evaluation research for large language model and multimodal agents, designing benchmarking frameworks and end-to-end evaluation pipelines across text, image, video, and audio generation tasks, while researching long-horizon memory, context engineering, and agent workflow optimization.
- Optimized LLM inference infrastructure for Qwen models with vLLM and Kubernetes, applying quantization, tensor and pipeline parallelism, and advanced serving techniques to improve GPU utilization, throughput, and end-to-end latency at production scale.
- Researched AI agent safety and reliability through systematic red teaming, adversarial testing, and edge-case evaluation, and developed guardrails, runtime monitoring, and risk assessment frameworks that turn findings into trustworthy production safeguards.
Aug 2024 – Jul 2025
Head of Research Engineer,
Anyidea Inc
- Designed and shipped retrieval-augmented (RAG) AI agent workflows in Python with Flask/FastAPI and LLM APIs, integrating retrieval pipelines, tool use, and backend services to automate multi-step SaaS business processes for enterprise applications.
- Built AI system monitoring and analytics infrastructure with dashboards, structured logging, and alerting pipelines to track agent performance, workflow execution, latency, and reliability metrics across services.
Aug 2024 – May 2025
Strategist,
Perplexity
- Promoted Perplexity's AI agent products through technical demos and community outreach, showcasing Deep Research, multi-model capabilities, Spaces, and the Comet AI browser for AI-powered research and productivity workflows.
Jun 2024 – Aug 2024
Research Intern,
Frost & Sullivan – LeadLeo Research
Institute
- Researched LLM evaluation methodologies and built automated benchmarking pipelines to measure model capability, robustness, and reliability across finance and healthcare domains, surfacing systematic failure modes.
- Developed RLHF-based reward modeling and alignment frameworks to optimize LLM behavior toward safe, reliable, and domain-appropriate responses for real-world deployment.
Mar 2018 – Jun 2021
Lead Research Engineer,
Srlon
- Built large-scale data infrastructure with Kafka-based telemetry pipelines for AI-powered e-commerce applications, enabling reliable user data ingestion, real-time analytics, and downstream machine learning workflows.
- Developed cloud data platforms using Datastream (CDC) and BigQuery to analyze customer monetization data and power KPI dashboards that guided product and business decisions.
Selected Publications & Projects
Publications
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Projects
Improved Regularization for Convolutional Neural Networks
GitHub
Mentor: Professor Hai Li
Symbolic Knowledge Distillation
GitHub
Mentor: Professor Bhuwan Dhingra
Technical Skills
- AI Technical Skills: Post-training, alignment, reinforcement learning, supervised fine-tuning, reasoning, multimodal, evaluation
- Programming & Development: Expert in Python, Java, JavaScript/TypeScript, HTML/CSS, SQL; Proficient in Flask, FastAPI, Node.js, React.js, RESTful, Swagger
- Database & Cloud Platforms: Skilled in PostgreSQL, MySQL, MongoDB, Hadoop/Hive, DynamoDB, Redis, VectorDB; Experienced with AWS (S3, EC2, EMR, Lambda, EKS, SQS, SNS), GCP (Compute Engine, App Engine), Azure
- Big Data & DevOps Tools: PySpark, Kafka, PyTorch; Containerization with Docker/Kubernetes; CI/CD with Jenkins/Git; Infrastructure as Code with Terraform; Test & Monitor with JUnit/Postman/Grafana/Prometheus
Miscellaneous
Hobbies: Golf, Yoga, Pilates, Nutrition, and Trying all kinds of food
Teaching Experience
Summer 2023
Main Teaching Assistant,
Duke University — Quantitative Business
Analysis
- Led weekend review sessions and guided students on probability, statistics, and AI/Deep Learning applications; designed and graded exams and quizzes, and provided support for TA sessions.
Spring 2022
Teaching Assistant,
Duke University — Applied Probability
and Statistics