
Researcher at UTS Robotics Institute
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Technology Sydney
Data Scientist
June 27, 2026 – Present
robot-learning-human-trust
January 21, 2024 – July 17, 2025
Codebase of paper "Improving Trust Estimation in Human-Robot Collaboration Using Beta Reputation at Fine-grained Timescales" published at RA-L 2025 📝
View ProjectDL-computer-vision
March 11, 2023 – April 27, 2023
Solutions for Assignments of EECS 498-007/598-005 Deep Learning for Computer Vision (Fall 2020) course from the University of Michigan 📖
View Projectself-improving-RL
July 1, 2022 – July 13, 2023
Codebase of paper "Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms" published at ICRA 2023 📝
View Projectoffline-rl-minigrid-env
May 2, 2022 – June 3, 2022
Implementation of Offline Reinforcement Learning in Gym Mini-Grid Environment :key:
View Projectdaily-paper-reading
March 19, 2022 – Present
Just recording papers I read everyday :books:
View ProjectDeFIX
March 1, 2022 – November 2, 2022
Codebase of paper "DeFIX: Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous Driving" published at ITSC 2022 📝
View Projectcarla-imitation-learning
November 25, 2021 – January 8, 2022
Imitation Learning Model Training in Carla with DAgger 🚔
View Projectscenario-based-rl
November 23, 2021 – March 7, 2025
Implementation of Deep Reinforcement Learning Methods on Carla Simulation with Trainings Based on Scenarios 💥
View Projectmulti-agent-evolutionary-rl
October 9, 2021 – December 1, 2021
Implementation of Evolutionary Strategies with Multi-Agent Deep Reinforcement Learning in PettingZoo Environments 🦘
View Projectpettingzoo-environments
September 8, 2021 – September 25, 2021
Simple Training and Evaluation of Multi-Agent Environments with Deep Reinforcement Algorithms 🐨
View ProjectCultural Fit Analysis
The candidate's projects are highly specialized in Reinforcement Learning and autonomous systems, which aligns well with a research-heavy Data Scientist role. The consistent focus on academic publications and personal projects demonstrates initiative and a passion for the field. However, the lack of diversity in project types (almost exclusively RL/autonomous driving) and the absence of team-based or production-oriented projects might indicate a narrower scope of experience for broader data science roles. The candidate's current role as 'Data Scientist' at a university further supports a research-oriented fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong focus on research and problem-solving within the domain of Reinforcement Learning. The publication record suggests diligence and a structured approach to complex technical challenges. However, without psychometric test results or interview data, it is difficult to assess specific soft skills like teamwork, communication, or stress handling.