Ngoc Ngo Quang Tran

hi [at] ngoc [dot] io







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Computer Science PhD student at Vanderbilt University. Adversarial machine learning researcher. Curious about everything. Skillful at team-working and collaborating. Creative and persistent. Keen on self-learning. Passionate about sharing knowledge. CTF enthusiast.
PhD Student, Computer Science GPA: 4.00/4.00
Expected May 2028

Topic: Artificial Intelligence Security

Vanderbilt University, Nashville, TN

+  Notable courses taken:

  • Advanced Machine Learning
Master of Science, Computer Science GPA: 4.00/4.00
May 2021

Topic: Adversarial Machine Learning

Rensselaer Polytechnic Institute, Troy, NY

+  Notable courses taken:

  • Machine Learning from Data
  • Cryptography and Network Security I
  • Computer Operating Systems
  • Analysis of Algorithms
  • Large Scale Matrix Computation and Machine Learning
  • Computational Finance
  • Programming Languages
B.A. Pure/Computational Mathematics GPA: 3.74/4.00
May 2017

Minor(s): Computer Science

Summa Cum Laude

Wabash College, Crawfordsville, IN

+  Notable courses taken:

  • Linear Algebra
  • Abstract Algebra
  • Numerical Analysis
  • Real Analysis
  • Elementary and Partial Differential Equations
  • Complex Analysis
  • Computer Algebra
  • Combinatorics
  • Operations Research
  • Theory of Numbers

Teaching Assistant, Computer Science Department

Vanderbilt University, Nashville, TN

2023 - Present
  • Teaching Assistant for CS 3270: Programming Languages
    • Held office hours, answered forum questions, graded assignments

Research Resident, AI Residency Program

VinAI Research, Hanoi, Vietnam

2021 - 2023
  • Conducted research in the field of Machine Learning
  • Participated in weekly meetings of the Machine Learning reading group
  • Supported as speaker at various AI-centric events
  • Developed internal projects for VinFast and VinHomes
  • Attended courses relevant to research interests

AI Research Team Lead, R&D Department

Sun-Asterisk Inc., Hanoi, Vietnam

2019 - 2021
  • Research Lead: Managed research team, organized internal knowledge sharing seminars, submitted conference papers, supported other product teams. Lead a team of 10.
  • Project Lead: Stabo - an internal meeting room scheduler bot. Lead a team of 5.
  • Teacher/Lecturer: Taught the Machine Learning Fundamentals course, a joint project of Sun* Inc. and AOTS, Japan. Held seminars at universities and venues.

Grad Teaching & Learning Assistant, Advising & Learning Assistance Center

Rensselaer Polytechnic Institute, Troy, NY

Spring 2019
  • Held office hours and exam review sessions for assigned classes
    • CSCI-1100: Introduction to Computer Science
    • CSCI-1200: Data Structures

Teaching Assistant, Computer Science Department

Rensselaer Polytechnic Institute, Troy, NY

  • Head Teaching Assistant for CSCI-1100: Introduction to Computer Science
    • Taught lab sessions, held office hours, answered forum questions, graded assignments
  • Grading for CSCI-2500: Computational Organization and CSCI-4210: Operating Systems

Research Assistant, Computer Science Department

Rensselaer Polytechnic Institute, Troy, NY

Summer 2018
  • Reviewed existing literature over matrix completion from limited observations
  • Worked on matrix sketching conditions under the supervision of Dr. Alex Gittens

Research Assistant, Mathematics Department

Coe College, Cedar Rapids, IA

Summer 2016
  • Researched on the patterns of ABC Endview puzzles
  • Discovered a Fibonacci-like pattern in minimal-clue conditions

Helpdesk Intern, IT Service

Wabash College, Crawfordsville, IN

  • Managed installation and maintenance of Wabash College's facility
  • Troubleshot and resolved technical problems from faculty and students

Junior Dev Intern, FPT Software

FPT Corporation, Hanoi, Vietnam

Summer 2014
  • Java Trainee: prepared for the OCJP test, a mandatory requirement for the employees
  • Learned the outsourcing and workload aspects from the DIRECTV project
Publications   Asterisk (*) denotes equal contribution.

Robust Contrastive Learning With Theory Guarantee

Ngoc N. Tran*, Tung Lam Tran*, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Phung, Trung Le

Preprint  |  Code
We identify which components in the unsupervised training process can improve the robust supervised loss. Under review.

Sharpness & Shift-Aware Self-Supervised Learning

Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Phung, Trung Le

Preprint  |  Code
We enhance SimCLR by minimizing loss sharpness and improving the practical positive-pair distribution. Under review.

Improving Multi-task Learning via Seeking Task-based Flat Regions

Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Phung, Trung Le

Preprint  |  Code
We leverage Sharpness-Aware Minimization to enhance model generalization ability in multi-task learning. Under review.

Multiple Perturbation Attack: Attack Pixelwise Under Mixed Lp-norms For Better Adversarial Performance

Ngoc N. Tran, Anh Bui, Dinh Phung, Trung Le

Preprint  |  Code  |  Poster
We propose combining perturbations under different norms for a more effective yet imperceptible attack. Under review.

Anti-DreamBooth: Protecting Users From Personalized Text-to-Image Synthesis

Thanh Van Le*, Hao Phung*, Thuan Hoang Nguyen*, Quan Dao*, Ngoc N. Tran, Anh Tran

Preprint  |  Proceedings  |  Code  |  Website
We propose adding imperceptible patterns to public images to void them from fine-tuning diffusion models. ICCV 2023.

Stochastic Multiple Target Sampling Gradient Descent

Hoang Viet Phan, Ngoc N. Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung

Preprint  |  Proceedings  |  Code  |  Poster
We propose MT-SGD, allowing us to sample from the joint high-likelihood of multiple target distributions. NeurIPS 2022.

ReINTEL Challenge 2020: A Comparative Study of Hybrid Deep Neural Network for Reliable Intelligence Identification on Vietnamese SNSs

Hoang Viet Trinh, Tung Tien Bui, Tam Minh Nguyen, Huy Quang Dao, Quang Huu Pham, Ngoc N. Tran, Ta Minh Thanh

Preprint  |  Proceedings
We propose a multimodal model leveraging both tabular metadata and text content for fake news detection. VLSP 2020.

Efficient Low-Latency Dynamic Licensing for Deep Neural Network Deployment on Edge Devices

Toan Pham Van, Ngoc N. Tran, Hoang Pham Minh, Tam Nguyen Minh, Thanh Ta Minh

Preprint  |  Proceedings  |  Slides
We proposed an efficient system for model version management and licensing for edge-device deployment. CIIS 2020.

From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection

Quang Huu Pham, Viet Anh Nguyen, Linh Bao Doan, Ngoc N. Tran, Thanh Ta Minh

Preprint  |  Proceedings  |  Slides
We fine-tuned PhoBERT for Hate Speech Detection using various training techniques. Best Paper Award, IEEE KSE 2020.

Interpreting the Latent Space of Generative Adversarial Networks using Supervised Learning

Toan Pham Van, Tam Minh Nguyen, Ngoc N. Tran, Hoai Viet Nguyen, Linh Bao Doan, Huy Quang Dao, Thanh Ta Minh

Preprint  |  Proceedings  |  Slides  |  Presentation
We used orthogonality constraints as regularization to enforce independent and interpretable embeddings. ACOMP 2020.

Efficient Palm-Line Segmentation with U-Net Context Fusion Module

Toan Pham Van, Son Trung Nguyen, Linh Bao Doan, Ngoc N. Tran, Ta Minh Thanh

Preprint  |  Proceedings  |  Slides
We built a U-Net model with our custom Context Fusion Module to extract palm lines from hand images. ACOMP 2020.

Deep Learning Approach for Singer Voice Classification of Vietnamese Popular Music

Toan Pham Van, Ngoc Tran Ngo Quang, Ta Minh Thanh

Preprint  |  Proceedings  |  Slides
We applied vocal segment detection, extraction, and a classifier to the singer voice classification problem. SoICT 2019.

Deep Neural Networks Based Invisible Steganography for Audio-into-Image Algorithm

Quang Pham Huu, Thoi Hoang Dinh, Ngoc N. Tran, Toan Pham Van, Thanh Ta Minh

Preprint  |  Proceedings  |  Slides
We proposed a new approach of employing deep learning in hide secret audio in a cover image. IEEE GCCE 2019.

HopSkipJumpAttack Reimplementation

Sun-Asterisk Inc., Hanoi, Vietnam
June 2020
This project is a reimplementation of Chen et. al black-box decision-based attack on deep learning models. Wrote a post explaining the paper. Created a related AI-centered CTF challenge.

voxtrac - vocal extractor

Sun-Asterisk Inc., Hanoi, Vietnam
Fall 2019
This project implements an experimental deep model for extracting the vocal track from a master track. Incorporated into our SoICT 2019 paper.

Audio Steganography

Sun-Asterisk Inc., Hanoi, Vietnam
Summer 2019
This project is composed of deep learning models that are trained to embed a secret voice audio onto a cover image, or recover one from an image carrier, respectively. Results from our IEEE GCCE 2019 paper.

Cryptographic Filematcher

Rensselaer Polytechnic Institute, Troy, NY
Fall 2017
This project implements a secure method of matching two people's lists of files and finding the ones they have in common without exposing any details about the rest, using the Paillier Cryptosystem and a secure hash function.

Oral Comprehensive Assigning Tool

Wabash College, Crawfordsville, IN
Spring 2017
This project models the problem of assigning date/time, location, and board of professor for each senior student as a massive quasilinear programming problem, then solve it using AMPL/CPLEX.

ABC Endview

Coe College, Cedar Rapids, IA
Spring 2016
This project does natural deductions on given puzzles and bruteforce all solutions when needed. The user can try different initial states of the board and get the corresponding possible solutions, aiding the research.
  • Programming Languages: Python, C/C++, Go, Haskell, Java, Scala, Prolog, Racket/Scheme, Matlab
  • Libraries/Modules: PyTorch, JAX, Keras, TensorFlow, NumPy/SciPy, pandas, matplotlib, seaborn, cvxpy
  • Language Proficiency: English (fluent), Vietnamese (native), German (elementary)