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Hi, I'm Dung Vo, a PhD candidate in Computer Science at Wayne State University in Detroit. My research focuses on multi-agent systems, natural language processing, and AI-driven production systems, with an emphasis on applying theory to real-world problems. I enjoy building scalable ML pipelines and translating research insights into practical solutions. I have industry experience as a Data Scientist and AI researcher across Singapore and Vietnam, where I developed dynamic pricing systems, real-time data pipelines, and ML deployment processes. I’m driven by collaborations across disciplines and a hands-on approach to turning ideas into impactful products.…Hi, I'm Dung Vo, a PhD candidate in Computer Science at Wayne State University in Detroit. My research focuses on multi-agent systems, natural language processing, and AI-driven production systems, with an emphasis on applying theory to real-world problems. I enjoy building scalable ML pipelines and translating research insights into practical solutions. I have industry experience as a Data Scientist and AI researcher across Singapore and Vietnam, where I developed dynamic pricing systems, real-time data pipelines, and ML deployment processes. I’m driven by collaborations across disciplines and a hands-on approach to turning ideas into impactful products.

Dung Vo

Data Scientist, AI Engineer, AI Developer, +2

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Hi, I'm Dung Vo, a PhD candidate in Computer Science at Wayne State University in Detroit. My research focuses on multi-agent systems, natural language processing, and AI-driven production systems, with an emphasis on applying theory to real-world problems. I enjoy building scalable ML pipelines and translating research insights into practical solutions. I have industry experience as a Data Scientist and AI researcher across Singapore and Vietnam, where I developed dynamic pricing systems, real-time data pipelines, and ML deployment processes. I’m driven by collaborations across disciplines and a hands-on approach to turning ideas into impactful products.…Hi, I'm Dung Vo, a PhD candidate in Computer Science at Wayne State University in Detroit. My research focuses on multi-agent systems, natural language processing, and AI-driven production systems, with an emphasis on applying theory to real-world problems. I enjoy building scalable ML pipelines and translating research insights into practical solutions. I have industry experience as a Data Scientist and AI researcher across Singapore and Vietnam, where I developed dynamic pricing systems, real-time data pipelines, and ML deployment processes. I’m driven by collaborations across disciplines and a hands-on approach to turning ideas into impactful products.

Available to hire

Hi, I’m Dung Vo, a PhD candidate in Computer Science at Wayne State University in Detroit. My research focuses on multi-agent systems, natural language processing, and AI-driven production systems, with an emphasis on applying theory to real-world problems. I enjoy building scalable ML pipelines and translating research insights into practical solutions.

I have industry experience as a Data Scientist and AI researcher across Singapore and Vietnam, where I developed dynamic pricing systems, real-time data pipelines, and ML deployment processes. I’m driven by collaborations across disciplines and a hands-on approach to turning ideas into impactful products.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Research Engineer at Singapore Management University

March 1, 2024 - January 31, 2025

Research on multi-agent systems, leveraging large language models with instruction tuning and fine-tuning; exploring discovery of intents through supervised/unsupervised learning and investigating new formats for intention understanding in NLP.

Data Scientist at Be Group JSC

November 1, 2022 - March 31, 2024

Dynamic pricing system development to balance demand and supply in major Vietnamese cities. Achieved GMV growth of over 10%, improved service conversion from 10% to 25%, and enhanced trip completion rates from 5% to 40% depending on time and weather. Replaced ELK with a near real-time Debezium–Pub/Sub data pipeline to reduce delay by 15x and improved production search completion rate by over 7%. Designed ML training, versioning, and deployment workflows, and implemented an identity/eligibility verification system to reduce unauthorized drivers and manual workload.

AI Research Resident at FPT Software

May 1, 2021 - June 30, 2022

Applied Graph Neural Diffusion to discrete forms of neural differential equations; experimented with stochastic terms to address over-smoothing in GRAND; contributed to research on neural network generalization and related theory.