Jia-Lin Hau Monkie

Computer Science Ph.D candidate · University of New Hampshire · JiaLin.Hau@gmail.edu

I am currently a Ph.D candidate in Computer Science at University of New Hampshire (UNH), a member of the Reinforcement Learning and Robustness Lab (RLsquared) and my advisor is Marek Petrik. My research mainly focus on computational efficient algorithm for risk averse data driven decision making.

I am highly interested in Reinforcement Learning, Actuarial Science, Deep Learning, A.I, Machine Learning and Risk Analysis. Beside learning and coding, I enjoy traveling, scuba diving, playing computer games, and basketball.

Education

University of New Hampshire

Ph.D. in Computer Science. View Diploma
Reinforcement Learning and Robustness Lab (RLsquared)

GPA: 4.0/4.0

Jan 2023 - May 2025
M.S. in Computer Science. View Diploma

GPA: 4.0/4.0

Jan 2019 - Dec 2022
B.S. in Applied Mathematics: Economics. View Diploma
Summa Cum Laude (Dean's list)

GPA: 3.89/4.0

Sep 2015 - Sep 2018

Sabah Tshung Tsin Secondary School

Jan 2011 - May 2015

Skills

Programming Languages & Tools
AWS, Python, Matlab, Julia, Latex, R, git, Markdown, bash, C, C++, mySQL, Html, JMP, Tableau, Excel.
Coursework
Reinforcement Learning, Advance Machine Learning, Algorithms, Computer Graphics, Assembly Language, System Programming, Formal Specification, Database System (SQL), Forecasting Analysis, Numerical Methods, Linear Algebra, Differential Equation, Multi-Dimensional Calculus, Econometrics, Probability Theory, Statistical Inference, Financial Mathematics, Mathematical Optimization, cyber-security and software security analysis.

Communcational Language
Mandarin, Cantonese, English, Malay, and some other dialects (Hakka, Hokkien).

Work / Leadership Experience

Research Assistant

Reinforcement Learning and Robustness Lab
Fall 2020 - Present

AI / Data Science Summer Associate

JP Morgan Chase and Co.
  • Proposed novel deep reinforcement learning (RL) approach to find gaps in strategy rules and models.
  • Developed advanced machine learning (ML) models (i.e. Random Forest, XGBoost, LightGBM, CatBoost, Tab-transformer) and compared different encodings and imputations for fraud prediction.
  • Developed code on AWS Cloud (SageMaker, Bitbucket), and utilized PySpark, Hadoop, EMR to optimize code for big data.
Summer 2024

Teaching Assistant

Department of Computer Science at UNH
Fall & Spring 2023 , Spring 2024 Spring 2020
  • CS 520 - Assembly language programming and machine organization
  • CS 410P - Introduction to scientific programming in Python
Fall 2019
  • CS 410C - Introduction to scientific programming in C
  • CS 725 / 825 - Computer networks
Spring 2019
  • CS 410P - Introduction to scientific programming in Python
Spring 2019 - Spring 2024

Data Analyst

Boston Road Runner (BRR)
Sep 2019 - Dec 2019
  • Preprocessed (handle missing values, duplicates, and apply consistent formatting) data of participants and sponsors.
  • Developed auto-regression time series models in R to predict future trends in the number of participants for upcoming races.
  • Designed 3NF database schema using ERD and relation schema to reduce anomalies and improve data quality and integrity.
  • Created data visualizations using Tableau, which allow peers and sponsors easily interpret and understand data insights.

Junior Instructor & Summer Camp Resident Assistant

Idea Math
Jun 2018 - Aug 2019
  • Enhance elementary schoool students problem-solving skills for Mathematics competition.
  • Created study plans for the class and conducted group activities with students.
  • Structured activities and events for residential students.

Vice President

UNH International Student Organization
May 2017 - Jun 2018
  • Collaborated with other organizations to spread culture awareness.
  • Allocated tasks for volunteers and executive members based on their unique advantages.

Tutor

UNH Mathematics Center
Aug 2017 - Jun 2018
  • Clarified Mathematics concepts and assisted students with their homework.
  • Organized a study plan and helped students to catch up with class content.
  • Conducted review sessions to help students prepare for quizzes and exams.

Residential Assistant

UNH Housing & Residential Life
Aug 2016 - Jun 2017
  • Structured social activities, created safe and supportive environment for 500 residents.
  • Responsible for critical knowledge such as proper protocol involving responding to alcohol intoxication, roommate issues, and residents personal issues.
  • Communicated and related well with residents, staff, housekeepers, and maintenance personnel.

Research

Google Scholar

Publications and Preprints

Reviewing Services

  • International Conference on Learning Representation (ICLR 2025)
  • International Conference on Machine Learning (ICML 2022, 2024 and 2025)
  • Journal of Artificial Intelligence Research (JAIR 2024 and 2025)
  • Artificial Intelligence and Statistics (AISTATS 2024 and 2025)
  • Conference and workshop on Neural Information Processing Systems (NeurIPS 2021 and 2025)

Projects

Group Project

EMOAI

Developer and Use Case Finder

Shayan Amani, Chao Chi Cheng, Jia Lin Hau, Lekyang Sai
Spring 2019

Emotion recognition application to avoid depression. View Presentation (YouTube)

  • Spearheaded Deep Learning (CNN) emotion recognition project with pre-trained models to accurately classify users' facial expressions.
  • Proposed groundbreaking application of the use of facial and emotion recognition technology to identify and prevent depression.
  • Implemented active learning by allowing users to verify/update labels of their own emotion which enable personalized classification.

Robust pest management using RL

Talha Siddique, Jia Lin Hau, Shadi Atallah, Marek Petrik.
Spring 2019
RLDM 2019 Poster
  • Leveraged reinforcement learning techniques to develop a robust framework for risk-averse decision-making in pest management.
  • Applied natural splines regression model to predict pest growth and STAN Bayesian inference language to generate posterior datasets, which were used to compute the optimal Robust MDP policy.
  • Demonstrated the effectiveness of our framework by solving various domains including Cartpole (OpenAI) with limited data in Python.

CRACC

Analyst / Android Developer

Khoi Nguyễn (Danny), Chao Chi Cheng, Nicolas Câmara, Jia Lin Hau
Jan 2017 - Jan 2018
A social application that connect people to play sports together. View Apps
  • Collected data from various sources (API, Kaggle, BLS), analyzed and created data visualizations with Python.
  • Communicated effectively with the IOS team to ensure consistent UI (XML) and functionality (Java) using Android Studio.
  • Integrated with Firebase for users' data, and developed features that query weathers and navigation data based on users' location.

Class Project

Multi Arm Bandits Basic Algorithms Comparison

Jia Lin Hau
Fall 2021
Explored Multi Arm Bandits (MAB) algorithms and their performance in adversarial domain. We obtained two conclusions from the empirical results, (1) Even a little randomization provide difficulty for adversarial to exploit. (2) Decrease exploration weight over-time benefit algorithms to exploit higher reward arms. View Report

Bayesian MDP solved Cartpole with limited data

Jia Lin Hau
Fall 2019
Applied regression model with STAN Bayesian probabilistic program to handle problem with limited data. Demonstrated it with Cartpole (OpenAI gym domain). View Report

Cryptocurrency Analytics

Jia Lin Hau, Gerasimos Mouikis, Spencer Pope
Spring 2018
Predicted cryptocurrency with time series analysis method Vector Auto Regression (VAR) on the log return of the closing price. View Report

Solve Blackjack with MDPs

Jia Lin Hau, Marek Petrik
Spring 2018
Utilized MDP (Value Iteration) to solve for the optimal action (Stand, Hit, Split, Double, or Surrender) for BlackJack with R. View Slide

Awards & Certifications

Research

  • Received AISTATS 2025 Best Reviewer Award [award website]
  • Received UNH Doctoral Dissertation Year Fellowship (DYF) Scholar Award [proposal]
  • Received NeurIPS 2023 Scholar Award

Marathon

  • 1 st Place (Co-ed Relay) - 2016 Manchester City Marathon by SNHU
  • 4 th Place (division M0119) - 2015 Seacoast Half Marathon in Portsmouth

Scuba Diving

  • Certified - 2019 NAUI Open Water Scuba Diver
  • Certified - 2013 PADI Advance Open Water Diver

Actuarial Science

  • Passed - 2018 Actuarial Science Exam P: Probability

Finance

  • Certified - 2018 Bloomberg Market Concepts (BMC) Completion

Pitch

  • Semi-finalist - UNH 2017 Fall stock pitch competition ~ WTI (strong buy) [slide]
  • Semi-finalist - UNH 2019 Holloway prize competition ~ Emoai (AI facial recognition apps prevent depression) [video] Shayan Amani, Jia Lin Hau, Chao Chi Cheng, Lekyang Sai

Download

View CV

View 1-page Resume