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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

PRO

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

Detroit, United States

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

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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.