Curriculum Vitae

Education

• Ph.D. in Engineering Science, Simon Fraser University, 2027 (expected)
• M.S. in Applied Computing, University of Toronto, 2015
• B.E. in Networks and Communications, Universidad Tecnológica del Centro (Venezuela), 2007

Work experience

• Fall 2015: Research Assistant, Simon Fraser University
  • Research in information theory, learning theory, and machine learning
  • Supervisor: Professor Ivan Bajic
• 2017-2021: Senior Data Scientist, Wattpad
  • Researched deep learning models to learn disentangled latent representations from unsupervised long-form text
  • Developed language models for affect analysis that incorporate knowledge graph information using attention mechanisms
  • Researched multilingual models to encode sentences into syntactic representations
  • Researched reinforcement learning models to elicit user preferences
  • Developed a Bayesian optimization engine to improve content discovery
• 2015-2017: Research Engineer, VerticalScope
  • Researched and developed algorithms to quantify and predict the performance of hundreds of social networks
  • Researched neural networks and probabilistic graphical models in semi-supervised scenarios for language processing tasks
• 2015: Data Scientist, Terapeak
  • Developed information theory algorithms to learn ontology representations from structured descriptions of products
  • Created a probabilistic model to learn synonym relationships between product terms
• 2014: Research Intern, BlackBerry
  • Researched predictive models for intrusion detection and multi-factor authentication
  • Developed temporal generative models and for outlier detection
• 2009-2010: Software Engineer, TDA
  • Developed data collection and statistical analysis platforms to derive insights
• 2004–2013: Software Engineer – Co-Founder, Web Lab
  • Solved problems in content management, real estate, e-learning, human resources, messaging and e-commerce

Skills

• High-performance scientific computing: Python, PyTorch, Numba, JAX
• Data engineering: Scala, Apache Spark, Apache Cassandra, Apache Kafka, Elasticsearch, SQL
• Backend development: Go, ZeroMQ, gRPC, Kubernetes

Awards

• Mitacs Accelerate Fellowship
• Simon Fraser University Graduate Dean’s Entrance Scholarship
• NSERC Canada Graduate Scholarship – Doctoral

Publications

Rate-distortion theory in coding for machines and its applications

Alon Harell, Yalda Foroutan, Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo, Anderson de Andrade, & Ivan V. Bajic. (2025). "Rate-distortion theory in coding for machines and its applications." IEEE TPAMI.

Towards task-compatible compressible representations

Anderson de Andrade, & Ivan Bajić. (2024). "Towards task-compatible compressible representations. ICME Workshop on Coding for Machines." ICME Workshop on Coding for Machines.

Conditional and residual methods in scalable coding for humans and machines

Anderson de Andrade, Alon Harell, & Ivan Bajić. (2023). "Conditional and residual methods in scalable coding for humans and machines." ICME Workshop on Coding for Machines.

An architecture for accelerated large-scale inference of transformer-based language models

Amir Ganiev, Colt Chapin, Anderson de Andrade, & Chen Liu. (2021). "An architecture for accelerated large-scale inference of transformer-based language models." NAACL Conference on Human Language Technologies: Industry Papers.

Graph representation learning network via adaptive sampling

Anderson de Andrade, & Chen Liu. (2020). "Graph representation learning network via adaptive sampling." arXiv:2006.04637.

Exploring multilingual syntactic sentence representations

Chen Liu, Anderson de Andrade, & Muhammad Osama. (2019). "Exploring multilingual syntactic sentence representations." EMNLP Workshop on Noisy User-Generated Text.

Best practices for convolutional neural networks applied to object recognition in images

Anderson de Andrade. (2014). "Best practices for convolutional neural networks applied to object recognition in images." arXiv:1910.13029.

A comparison of neural network training methods for text classification

Anderson de Andrade. (2013). "A comparison of neural network training methods for text classification." arXiv:1910.12674.

Talks

A machine learning research toolkit

March 25, 2025

Tutorial at School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada

Towards task-compatible compressible representations

July 15, 2024

Conference proceedings talk at Niagara Falls Marriott on the Falls, Niagara Falls, ON, Canada

Teaching

Teaching assistant: Introduction to engineering analysis (ENSC 180)