Topic: Artificial Intelligence Security
Vanderbilt University, Nashville, TN
+ Notable courses taken:
- Advanced Machine Learning
Profile
Education
Experience
Publications
Projects
Languages
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Profile
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.
Education
PhD Student, Computer Science GPA: 4.00/4.00
Expected May 2028
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
Experience
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
2017-2019
- 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
2015-2016
- 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.
We identify which components in the unsupervised training process can improve the robust supervised loss.
Under review.
We enhance SimCLR by minimizing loss sharpness and improving the practical positive-pair distribution.
Under review.
We leverage Sharpness-Aware Minimization to enhance model generalization ability in multi-task learning.
Under review.
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.
Projects
HopSkipJumpAttack Reimplementation
Sun-Asterisk Inc., Hanoi, Vietnam
https://github.com/ngoctnq/hopskipjumpattack
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
https://sun-asterisk.ai/poc-demo/music-separation
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
https://sun-asterisk.ai/poc-demo/audio-steganography
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
https://github.com/ngoctnq/cryptographic-filematcher
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
https://github.com/ngoctnq/Oral-Comps-Assigning-Tool
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.
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.
Languages
- 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)