All talents specialized in Computer Vision

• Strongest stack as developer: Node/Javascript, MongoDB • Glad to have made your Spotify next song recommendation a bit faster • Most of my experience is 60% engineering, 40% researching. I am inclining towards roles with more researching. • I am intrigued by the recent rise of multi-modal AI like the newly introduced Google Gemini, and would love to join related R&D endeavor

A programmer with a passion for development, always ready for challenging tasks, and systems that need high performance and optimization. By this time, I'm looking for other opportunities with new challenges and willing to learn new things.

❖ With 7 years of experience in the field, I am a multifaceted professional who excels as an engineer, researcher, and educator. ❖ My engineering background includes hands-on involvement in various machine learning and AI projects across diverse domains, such as healthcare, defense, and fintech. ❖ As a researcher, I have a solid track record of publishing A/A* papers on cutting-edge topics, including Trustworthy Machine Learning and Generative AI, and I co-organize the Monash GenAI Reading Group to foster collaboration and knowledge sharing. ❖ In my role as an educator, I serve as the Head Teaching Associate at Monash and as a lecturer at VietAI, where I passionately engage students in the intricacies of ML/AI. ❖ I also contribute to the field through my ML/AI blog. ❖ Driven by a strong work ethic, I strive to balance these multiple roles while continuously seeking to enhance my productivity and impact.

❖ Versatile Skill Set: 12+ years in Machine Learning and NLP technologies. ❖ Experienced Leader: 4+ years leading impactful ML projects in insurance and e‑commerce. ❖ Team Building Experience: Built and mentored teams from recruitment to onboarding, providing coaching and mentorship. ❖ Innovation at Google: Lead team in the GEO Machine Learning Intelligence project at Google EU, using AI for Google Maps. ❖ Cross‑functional Collaboration: Managed cross‑functional AI teams, emphasizing communication and col‑ laboration. ❖ Cloud Experience: Expertise in AWS, Kubeflow, and Airflow for AI development and deployment. ❖ Research Excellence: Ph.D. in Machine Learning, recognized for work in Semi‑Supervised Learning. ❖ Continuous Learner: Certified in SAFe, with additional skills in PySpark, Data Warehousing, and healthcare data analysis.

- I am a passionate and experienced AI professional with a focus on Machine Learning and Computer Vision. I am dedicated to automating everyday tasks and bringing AI solutions to reality. - My primary research direction involves optimizing AI solutions for edge devices such as cameras and Al Boxes. I have extensive experience in developing AI/ML projects from scratch using Chainer and TensorFlow, overcoming challenges related to technology, research, computational hardware, and limited support from the development community and open-source projects. - I have a strong background in various algorithms, including CNN, RNN, Clustering, GAN, Tree-based algorithms, and XGBoost. - I have worked with various data types, such as image, speech, ECG signal, test case data, and time-series data and contributed to the development of various AI applications, such as image classification, object detection, air quality forecasting, object matching, speaker identification and diarization, and pix2pix image generation.