About Me

I'm Sajad Faghfoor Maghrebi, a second-year PhD student in the SysNet group at the University of Toronto. I have the pleasure of being supervised by Prof. Niv Dayan at ORCA Lab.

My research focuses on hardware-aware indexes. I am interested in creating efficient data systems and indexing techniques that minimize data storage and access costs while scaling effectively. My work bridges theory and practice, which I find especially rewarding. These days, I am curious about scalable vector indexes, a cornerstone of semantic retrieval in AI.

When I'm not working, I enjoy hiking, biking, and climbing. I find profound joy in the poetry of Akhavan Sales. I like reading about history and etymology.

Sajad Faghfoor Maghrebi

Publications

Sphinx: A Succinct Perfect Hash Index for x86

Sajad Faghfoor Maghrebi & Niv Dayan. VLDB 2025 — [PDF] [Code]

Education

University of Toronto

PhD, Computer Science (Sep 2023 – Present) — Grade: A+

Sharif University of Technology

B.Sc., Computer Engineering (2018 – 2023) — GPA: 3.85/4.00

Awards and Honors

Ranked 6th among over 100,000 participants in the Iranian National University Entrance Exam

Jan 2018

Work Experience

Teacher Assistant, University of Toronto

Sep 2023 – Present — Assisted in courses like Introduction to Software Engineering (CSCC01, CSC301), Design and Analysis of Data Structures (CSCB63), 2x Introduction to Databases (CSC343), Introduction to Computer Science (CSC148), Database System Technology (CSC443), and Programming on the Web (Lead-TA CSC309).

Software Engineer, Digikala.com

Jul 2022 – Dec 2022 — Digikala is the biggest e-commerce company in the middle east. First, I worked on a complicated refactoring project with more than tens of thousands of lines of monolithic code, which included complex product logic. Then, my team and I were in charge of enhancing the project to Service-oriented architecture because of the auto-scalability and maintainability it provides.

Co‑founder & CTO, GoldScan

Sep 2020 – Sep 2023 — In GoldScan, I led a team to develop an efficient back-testing engine with a strategy optimizer for automated trading, covering crypto, stock markets, and forex. Built and optimized quantitative trading strategies to support dozens of traders. Worked on crypto arbitrage for inter-exchange and intra-exchange profit and implemented an online trading execution platform.

Co-founder, Karaneh

Sep 2018 – Jan 2019 — Organized educational events at middle and high schools to teach students about the financial markets, introducing them to key concepts and mechanisms used in real-world trading and finance.

Projects

Trading Infrastructure & Strategy Optimization

Developed a scalable and containerized trading system with FastAPI, featuring custom backtesting for different markets, as well as visualization tools and statistical reports. Optimized strategies using Optuna and built a data service for diverse market data on MongoDB.

pytse-client

pytse-client is an async Python client for Tehran Stock Exchange data. I implemented fast OHLCV and order book retrieval and statistical analysis with robust testing.

Crypto Arbitrage System

Designed inter‑ and intra‑exchange arbitrage algorithms, combining order book modeling with classical AI for risk‑aware execution across multiple venues.