NGUYEN VU ANH TRUNG (TRISTAN NGUYEN)
HCMC (Saigon), Vietnam | +84918378804 | [email protected] linkedin.com/in/anhtrung-nguyenvu | github.com/manolaz
PROFILE
An accomplished Software Architect and Academic Lecturer with over eight years of experience architecting high-compliance, data-intensive systems for bioinformatics and AI. Seeking to leverage a deep background in privacy-preserving technologies and large-scale machine learning to pursue doctoral research at the intersection of misinformation forensics and secure, cloud-native health information systems. Aims to develop novel computational frameworks to ensure the integrity and trustworthiness of digital information in critical domains.
ACADEMIC EXPERIENCE
Computer Science Lecturer | Swinburne University of Technology (HCMC) & Greenwich University | Sep 2023 – Present
As a core academic member of Swinburne’s HCMC campus, I have contributed extensively to curriculum delivery, student mentorship, and capstone leadership within the Bachelor of Computer Science program. My teaching has consistently aligned with Swinburne’s emphasis on industry relevance, innovation, and English-medium instruction.
🎓 Teaching Portfolio
  • Language of instruction: All lectures, tutorials, assessments, and student communications conducted in English.
  • Capstone leadership: Convenor of the Computing Technology Innovation Project, guiding students through real-world software engineering challenges with a focus on ethical practice and industry standards.
  • Approved to teach a diverse suite of units across undergraduate computing programs at Swinburne University of Technology: foundational programming (COS10003, COS10004, COS10005, COS10009, COS10022), inquiry and design (COS10026, COS20001), object-oriented and concurrent programming (COS20007, COS40003), cloud and big data technologies (COS20019, COS20028), database and data visualisation (COS20031, COS30045), web and mobile development (COS30008, COS30019, COS30043), software architecture and embedded systems (SWE30003, SWE30010), applied machine learning and distributed computing (COS30082, COS30015), as well as industry-facing projects and capstones (COS30049, COS40005, COS40006, COS40007, ICT30001) and software evolution (SWE40006).
RESEARCH INTERESTS
Federated and Privacy-Preserving ML
Investigating federated learning and differential privacy techniques to enable collaborative analysis of sensitive genomic datasets without compromising patient confidentiality.
Adversarial Robustness in Misinformation Detection
Designing and evaluating the resilience of multi-modal misinformation detection models against sophisticated adversarial attacks.
Causal Inference in Knowledge Graphs
Applying causal inference methodologies to graph-based data structures to understand the propagation dynamics and impact of digital information.
Research Papers:
with Dr.Loi Luu:
"Classifier model and generative dataset Simulating and Detecting Klinefelter Syndrome Variants in Non-Invasive Prenatal Testing (NIPT) Data."
(Manuscript in Preparation ,Anticipated Submission Aug 2025)
  • Contribution: This research addresses the critical challenge of accurately detecting rare sex chromosome aneuploidies, such as Klinefelter syndrome (XXY, XXXY, and mosaic forms), from low-coverage NIPT data.
  • Collaboration: In partnership with Dr. Loi Luu at the Institute for Applied Research in Health Sciences and Aging (ARiHA) - Thong Nhat Hospital, HCMC.
  • Methodology:
  • Developed a high-fidelity in silico simulation pipeline to generate realistic NIPT datasets reflecting variable fetal fractions, sequencing depths, and specific Klinefelter variants.
  • Conducting a rigorous comparative analysis of statistical (Z-score, normalized chromosome value) and machine learning-based algorithms for aneuploidy detection.
  • Systematically evaluating the impact of key biological and technical variables on detection sensitivity and specificity to establish optimal classification parameters.
  • Role: Led the design and end-to-end implementation of the AI model training, testing, and computational pipeline, including the data simulation framework, algorithm development, and performance evaluation.
KEY QUALIFICATIONS
High-Compliance Systems Architecture
Proven expertise in designing and deploying multi-cloud systems (AWS, Azure, GCP) compliant with stringent regulatory frameworks, including HIPAA and GDPR, for sensitive genomic and patient data.
Applied Machine Learning & Predictive Analytics
Extensive experience in developing and deploying end-to-end machine learning models for predictive maintenance, investment analysis, and bioinformatics, utilizing frameworks such as TensorFlow and PyTorch.
Large-Scale Data Engineering
Architected and orchestrated complex data pipelines using Apache Airflow, achieving up to 70% reduction in data processing latency for terabyte-scale datasets.
Graph-Based Data Modeling & Analysis
Utilized Neo4j graph databases to model complex relationships in large datasets, enabling deeper analytical insights into information propagation and system dependencies.
Academic Leadership & Mentorship
Demonstrated success in developing university-level curricula and mentoring over 60 students in advanced computing topics, guiding capstone projects from ideation to deployment.
ENGINEERING EXPERIENCE
1
Bioinformatics Cloud Engineer | DNA Nexus + DataXight
Oct 2023 – Aug 2024
  • Led the architecture of a multi-cloud (AWS/Azure/GCP) infrastructure for the UK Biobank, enabling reproducible, large-scale bioinformatics research while ensuring strict HIPAA and GDPR compliance.
  • Engineered scalable genomic data pipelines with Apache Airflow, automating the processing and analysis of complex DNA sequencing and phenotypic data, thereby accelerating research cycles.
  • Developed user-facing analytics dashboards, providing key insights into cloud resource utilization and research data, which directly supported data-driven decision-making for financial and scientific stakeholders.
2
AI/Data Engineer (VC Platform) | Vertex Growth
May 2020 – Jan 2021
  • Pioneered the development of a proprietary ML-driven platform for venture capital investment analysis, significantly enhancing the firm's deal sourcing and due diligence capabilities.
  • Architected robust data pipelines that reduced manual data handling by 60% and deployed predictive models that empowered data-driven investment strategies.
3
Data Engineer | SYSTUM Inc.
Nov 2019 – May 2020
  • Re-architected data integration workflows using Apache Airflow, achieving a 70% reduction in data processing latency and enhancing data availability for downstream analysis.
  • Leveraged Neo4j graph databases to model and analyze complex system dependencies, uncovering critical insights that led to improvement in overall system maintainability.
4
Full Stack Developer (IoT & Predictive Maintenance) | Smartec + Elek
Sep 18 – Oct 2019
  • Developed and deployed novel machine learning models (MXNet, TensorFlow) for an IoT analytics platform that accurately predicted equipment failures, reducing unplanned downtime by 25%.
  • The implemented solution led to a 20% reduction in energy consumption for monitored systems, demonstrating a direct real-world impact.
EDUCATION
M.Sc. in Computer Science | Bordeaux University, France | 2019 – 2021
  • Thesis: Investment Data Analytics for Venture Capital
  • Developed a novel, full-stack data platform to analyze investment opportunities, employing machine learning models to identify and rank high-potential startups from complex financial and alternative data sources.
Bachelor in Information Technology (DUT) | Bordeaux University, IUT, France | 2013 – 2016
AWARDS & HONORS
  • Honors: Mention Assez Bien (Equivalent to cum laude), Master of Science, Bordeaux University, 2021
TECHNICAL SKILLS
AI & Data Science:
  • Python (PyTorch, TensorFlow, Scikit-learn)
  • Neo4j
  • Apache Airflow
  • Tableau
  • Orange
  • RapidMiner
Software & Systems Engineering:
  • Rust
  • Node.js
  • C++
  • AWS, GCP, Azure
  • Docker, Kubernetes, Helm
  • Serverless
  • CI/CD (GitLab, Jenkins)
Security & Compliance:
  • HIPAA
  • GDPR
  • Multi-Factor Authentication (MFA)
  • Intrusion Detection Systems (IDS)
LANGUAGES
  • English: Fluent (Professional)
  • French: Fluent (Professional)
  • German: Basic (Reading)
REFERENCES
Dr. Truong Nguyen
Director, Swinburne University of Technology, Vietnam (HCMC)
Tuan Nguyen
CEO, DataXight
Tri Le
Manager, DataXight
Vu Nguyen
Bioinformatician, DNA Nexus
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