Abel Yagubyan

Senior Data Scientist at C3.ai

Hello! I'm a Senior Data Scientist at C3.ai with expertise in Deep Learning, Predictive Maintenance, and High-Performance Computing. I hold an M.S. in Computer Science from Northwestern University (Summa Cum Laude) and dual B.A. degrees in Computer Science & Applied Mathematics from UC Berkeley.

Previously, I co-founded FibonAI (UC Berkeley Skydeck), conducted research at Lawrence Berkeley National Laboratory on UPC++ performance testing, and interned at Apple. I've also reviewed 100+ papers for Elsevier's AI and Vision Computing journals.

News

Promoted to Senior Data Scientist at C3.ai in under 18 months for high-impact customer solutions

2024

Co-founded FibonAI, accepted into UC Berkeley's Skydeck Pad-13 Incubator competing against 5,000+ startups

June - Dec 2023

Graduated with M.S. in Computer Science from Northwestern University with Summa Cum Laude Honors

June 2023

Research contributor at Lawrence Berkeley National Lab's Pagoda Project on UPC++ performance testing

June 2022 - April 2023

Published "Embedding of Programming IDEs into Computer-Based Testing Software" at ACM SIGCSE '22

March 2022

Graduated from UC Berkeley with dual B.A. in Computer Science & Applied Mathematics

May 2022

Software Engineering Intern at Apple x UC Berkeley, managing CS61C projects for 4000+ HBCU students

May - Aug 2021

Research & Publications

Embedding of Programming IDEs into Computer-Based Testing Software

Abel Yagubyan, Dan Garcia

ACM SIGCSE '22 — Technical Symposium on Computer Science Education

TLDR: Published peer-reviewed paper presenting an interactive RISC-V compiler integrated into PrairieLearn for online programming education, enabling 3,000+ students to complete CS61C exams with embedded IDE functionality.

Paper ACM DL

SCALPEL: Customized Deep Neural Network Compression

Abel Yagubyan

Northwestern University — Research Project (Jan 2022 - June 2022)

TLDR: Developed Python-based DNN compression framework that reduced model sizes (AlexNet, LeNet-5) by up to 80% and achieved 3.5x speedup by customizing pruning techniques to target hardware parallelism (CPU, GPU, Microcontroller).

Report GitHub

UPC++ Performance Regression Testing & Benchmarking

Abel Yagubyan, Lawrence Berkeley National Laboratory

Pagoda Project — Research Contribution

TLDR: Developed automated performance regression testing platform for UPC++, a C++ library for distributed-memory parallel computing. Implemented distributed hashing benchmarks and compared performance against MPI and SHMEM.

LBNL Pagoda

Peer Reviewer — Elsevier Journals

Abel Yagubyan

Engineering & Applications of AI, Neural Networks, Vision Research

TLDR: Reviewed 100+ research papers for Elsevier's prestigious AI and computer vision publication journals, contributing to the peer review process for cutting-edge research in machine learning and neural networks.

Elsevier

Industry Experience

C3.ai

Senior Data Scientist

May 2024 - Present | Redwood City, CA

Lead data science initiatives in predictive maintenance and generative AI across large-scale deployments for Shell, ExxonMobil, Dow, Bloom Energy. Directed pilots delivering over $10M in value and deploying 1,000+ models per project. Developed foundational healthcare transformer model trained on 1M+ U.S. patient records. Created SpeedyREL, an internal tool reducing deployment timelines by 50%, adopted by 5+ projects. Promoted to Senior in under 18 months.

Python PyTorch Transformers XGBoost SQL Kubernetes

FibonAI

Co-Founder

June 2023 - December 2023 | San Francisco, CA

Designed and built SaaS platform providing comprehensive LLM-powered workspace for in-house corporate legal teams—integrating intake & triage, contract management, matter management, and AI Assistants. Successfully onboarded 8 General Counsels/Chief Legal Officers. Achieved 60% conversion rate during demos and 100% weekly user growth. Accepted into UC Berkeley's Skydeck Pad-13 Incubator (competing against 5,000+ startups globally).

Python Flask AWS MongoDB GPT-4 React

Apple x UC Berkeley

Software Engineering Intern

May 2021 - August 2021 | Remote

Project lead in collaboration with Apple and UC Berkeley's CS61C: Computer Architecture course. Coded and managed Computer Architecture, Algorithm, and ML-based projects for 4,000+ students simultaneously. Developed implementations using C, C++, Python, SIMD, OpenMP, and RISC-V Assembly.

C C++ Python RISC-V Assembly OpenMP

Software & Projects

FibonAIProduction

Premier legal AI-powered workspace transforming in-house legal operations with GPT-powered tools.

Private Repo Python 10+ Customers

Website

SCALPELResearch

DNN model compression achieving 80% size reduction and 3.5x speedup through hardware-aware pruning.

15 3 Python CUDA

GitHub

UPC++ Benchmarking SuiteFramework

Automated performance regression testing for UPC++ with comparison to MPI and SHMEM.

8 2 C++ Python

GitHub

PrairieLearn RISC-V CompilerTool

Interactive RISC-V compiler for online education serving 3,000+ students. Published at SIGCSE '22.

12 4 Python 3,000+ Students

GitHub

CS61ClassifyEducational

Neural network implementation in RISC-V assembly for Computer Architecture education.

24 7 Assembly Educational

GitHub

numcEducational

NumPy-like library in C achieving 20x speedup using OpenMP, SIMD, and loop unrolling optimizations.

18 5 C 20x Faster

GitHub

Education

Northwestern University

Master of Science in Computer Science

Evanston, Illinois • 2022-2023

Concentration in Deep Learning and Distributed Systems

Relevant Coursework

Deep Reinforcement Learning
Deep Learning
Deep Learning in NLP
Programming Massively Parallel Processors (CUDA)
Advanced Networking
Kernel & Low-level Software Development
Probability Theory & Stochastic Analysis

University of California, Berkeley

Bachelor of Arts in Computer Science & Applied Mathematics

Berkeley, California • 2018-2022

Relevant Coursework

Data Structures and Algorithms
Machine Learning
Artificial Intelligence
Computer Vision
Parallel Computers
Database Systems
ML in Multimedia Data