CV

Leyan Pan

Phone: +1 (470) 439-8014
Email: leyanpan@gatech.edu
Address: 6217 Providence Club Drive, Atlanta GA
GitHub: github.com/leyanpan

ACADEMIC INTEREST

• Machine Learning and Deep Learning
• Large Language Models
• Theoretical Computer Science
• Computer Security

EDUCATION

• Ph.D. Candidate in Computer Science, School of Cybersecurity and Privacy
  Georgia Institute of Technology | Atlanta, GA
  August 2023 - Now
  Advisor: Prof. Wenke Lee

• B.S/M.S in Computer Science (Concentrations: Artificial Intelligence & Theoretical Computer Science)
  Georgia Institute of Technology | Atlanta, GA
  Aug 2018 - May 2023
  GPA: 4.0/4.0
  Master’s Thesis advisor: Prof. Santosh Vempala
  Relevant Coursework: Machine Learning, Deep Learning, Robotics & Perception, Computer Vision, Natural Language Processing, Data Structure & Algorithms, Automata & Complexity, Design & Analysis of Algorithms, Advanced Algorithms & Randomness, Computational Social Science

RESEARCH

• Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay
  Jun 2022 - May 2023
  Supervised by Prof. Santosh Vempala at Algorithm and Randomness Center, Georgia Tech
  • Investigated a deep learning mathematical structure called Neural Collapse.
  • Introduced geometrically intuitive intra-class and inter-class cosine similarity measure for the phenomenon.
  • Established theoretical guarantees for the emergence of NC under the influence of last-layer BN and weight decay.
  • Performed experiments revealing a pronounced occurrence of NC in models incorporating BN and appropriate weight-decay values.
    Preprint
• Malware Analysis Using Graph Neural Networks
  January 2021 - Present
  Supervised by Prof. Wenke Lee and Dr. Yisroel Mirsky at Institute for Information Security & Privacy, Georgia Tech
  • Proposed to apply function structural information in malicious behavioral analysis.
  • Conducted experiments to compare the effectiveness of different graph autoencoder architectures, including GCN, GAT, and structure2vec, in identifying malicious functionalities using PyTorch.
  • Improved malicious functionality detection AUC from 0.84 to 0.89.
  • Currently analyzing clustering performance of extracted features for malicious functionality classification.
• Lattice-Based Cryptography in Homomorphic Encryption
  Fall 2019 - Spring 2021
  Supervised by Assoc. Prof. Vincent Mooney at Hardware/Software Codesign for Security Group, Georgia Tech
  • Applied homomorphic encryption to analyze camera image data in the encrypted domain to detect motion.
  • Designed homomorphic arithmetic operations using TFHE library in C programming language.
  • Novel attempt to design simple application-specific homomorphic encryption schemes for computationally limited hardware.
    Code & Paper

INTERNSHIPS & TEACHING EXPERIENCE

• Graduate Teaching Assistant for CS 4510 - Georgia Institute of Technology
  January 2022 - Now
  • Assisted Professor and Lecturer Prof. Zvi Galil in instructing the course Automata and Complexity.
  • Held office hours once per week for student inquiries.
  • Graded homework, exams, and projects and provided lecture notes for different materials in the theory of computation.
• Facebook Reality Labs - Silicon Security Engineering Intern
  June 2021 - August 2021
  • Assisted several teams to extract and organize security configurations and detect vulnerabilities.
  • Wrote C-based unauthorized access attacks to test firewall effectiveness.
  • Developed a firewall configuration analysis system using Python.
  • Improved configuration extraction efficiency from 30 min to 2-5 seconds.
• IBM X-force Command Center Cybersecurity Intern
  June 2020 - August 2020
  • Built a demonstrative industrial heat exchange system controlled by PLCs.
  • Demonstrated potential cyber-attacks on the system.
  • Analyzed Wireshark Packets and built Python scripts to attack the system using the Ethernet/IP Protocol.
• Intel Mobile Communications China - Technical Intern
  May 2019 - August 2019
  • Ran LTE testing on modems for iPhone.
  • Fixed connection and hardware problems and reported software bugs to developers.
  • Developed Python scripts to improve result collection efficiency.

PROJECTS

• Theoretical Analysis for Buy-Many Mechanisms for Multiple Buyers
  Spring 2022-Current
  • Surveyed recent work on theoretical bounds of buy-many mechanisms.
  • Extended results for multiple buyers from unit-demand to additive buyers.
  • Currently extending theoretical results to sub-additive and XOS buyers.
• Analyzing the Changes in Mental Health of Twitter Users Before and After the COVID-19 Pandemic
  Spring 2022
  • Utilized a word weight model to analyze language expressions on Twitter.
  • Examined the impact of coronavirus on different genders and regions.
  • Compared levels of stress and loneliness between different tweet datasets.
• Comparison of Transposed Convolutional Neural Network Architectures on Art Creation using GAN
  Fall 2021
  • Compared transposed versions of various convolutional neural network architectures as GAN decoders.
  • Developed evaluation criteria and discovered limitations of certain network designs.
• Joke Identification
  Fall 2019
  • Accomplished classification models to identify jokes using sound analysis and text.
  • Trained and compared performance of various classification algorithms.
    Code

SKILLS

• Languages: C/C++, Python
• Library & Frameworks: Pytorch
• Tools & System: LaTeX, Git, vim, IDA Pro