CV
Curriculum vitae of Abanoub E. Abdelmalak, ECE PhD Researcher at Georgia Tech working on hardware-aware machine learning and quantum error correction, and former Principal Product Architect at Siemens EDA.
Contact Information
| Name | Abanoub E. Abdelmalak |
| Professional Title | ECE PhD Researcher & Machine Learning Researcher |
| abanoub_abdelmalak@gatech.edu |
Professional Summary
ECE PhD Researcher at Georgia Institute of Technology, working on hardware-aware machine learning and quantum error correction. Ex-Siemens EDA Principal Product Architect and IC Design Consultant, with eight years building OPC, RET, and physical verification automation.
Experience
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2022 - 2025 Cairo, Egypt | Shanghai, China
Principal Product Architect
Siemens Digital Industries Software (EDA)
Architected AI and image processing automation for chip verification and design rule development.
- Architected an SVRF Copilot (a domain specific coding language) to automate design rule deck development. Pipeline involved LLM, LangChain, and an MCP protocol with tool-aware reasoning. Published as first author at IEEE ICLAD 2025, where AST-guided fine-tuning improved code generation accuracy by up to 40% over text-based fine-tuning on a 741-example DRC benchmark; reduced rule development time by ~40% in deployment.
- Designed an AI and image processing tool that utilizes Scanning Electron Microscope (SEM) images to automate process modeling, replacing manual image categorization with trained classifiers.
- Led global delivery across China, Europe, and the US. Orchestrated an Agile infrastructure transition for major Chinese fab, transforming an initial one-month engagement into a 6-year partnership.
- Drove RET/OPC automation (pattern generation, metrology recipe creation) integrated with Calibre/LSF.
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2017 - 2022 Shanghai, China
IC Design Consultant
Siemens Digital Industries Software (EDA)
Designed and automated optical proximity correction (OPC) model building and resolution enhancement techniques.
- Developed an OPC model-building automation system covering test-pattern creation, data filtering and prep, SEM metrology recipe development, and OPC verification, removing manual steps from the calibration cycle.
- Interfaced with physical metrology tools to auto-generate measurement; defined spatial pattern “uniqueness” via the mathematical entropy of extracted features.
- Architected a web-based recipe/version management platform with role-based access, improving security, tractability, and collaboration across teams.
- Implemented RET automation (pattern-coverage checks, DRM management) using C/C++ LAPI and ML-based feature extraction.
- Built computational models and test masks for technology ramps, meeting strict physical accuracy targets for hardware nodes from 90nm KrF to 5nm ArF.
Education
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2025 - Present Atlanta, GA, United States
PhD
Georgia Institute of Technology
Electrical & Computer Engineering
- Advised by Prof. Ali Adibi.
- Developing an AI-driven framework for hardware-aware QEC.
- Training explicit surrogate noise models on simulated and empirical hardware data to replace idealized i.i.d. noise assumptions with physical reality.
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2021 - 2024 Atlanta, GA, United States
MSc
Georgia Institute of Technology
Computer Science (Machine Learning Specialization)
- Specialized in advanced machine learning algorithms through graduate research and coursework in Deep Learning, NLP, information security, and algorithmic design.
- Headed the Shanghai student chapter, supporting new students in the program and arranging meetings accordingly.
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2012 - 2017 Cairo, Egypt
BSc
Ain Shams University
Communication Systems Engineering (Optics Specialization)
- Ranked first in the Optics track and seventh overall.
- {“Graduation Project”=>”Low power phase locked loops for internet of things applications.”}
Awards
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2024 Consultant Excellence
Siemens DI SW EDA
Awarded for outstanding professional contribution.
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2022 Consultant Excellence
Siemens DI SW EDA
Awarded for outstanding professional contribution.
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2020 Consultant Excellence
Siemens DI SW EDA
Awarded for outstanding professional contribution.
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2015 Student Exchange Program
DAAD Organization
DAAD-sponsored student exchange.
Skills
Languages
Certificates
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Quantum Information and Computation - IBM Quantum Curriculum (2025) -
Introduction to Psychology - Yale University, Coursera (2023) -
Project Initiation - Starting a Successful Project - Google, Coursera (2023) - Foundations of Project Management - Google, Coursera (2023)
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Fundamentals of Quantum Mechanics - University of Colorado Boulder, Coursera (2023) -
Agile Project Leadership - LinkedIn Learning (2023) -
Machine Learning - Stanford University, Coursera (2018)
Projects
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Domain Specific Language Copilot
Minimal viable product that automatically generates Standard Verification Rule Format (SVRF) language code from natural-language descriptions.
- Integrated a chat interface using LangChain and connected the model to a language server for contextual suggestions.
- Integrated the system with Model Context Protocol (MCP) for agentic custom function execution.
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Agent Solutions for EDA & Pattern-less PDK Verification
AI agentic flow to automate EDA verification tasks, orchestrating design checks, simulation, and optimization.
- Developed a pattern-less framework for verifying Process Design Kit (PDK) rules and multiple MCP functions.
- Integrated agents into existing workflows enabling continuous validation of PDKs.
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SEM Image Deep Learning Cleaning
Deep neural network system that automatically classifies physical SEM images by quality and structural feature type.
- Created a cross-platform QT interface to visualize and review large datasets.
- Automated generation of modeling files from cleaned data, reducing manual effort.
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Big Data Quantum Mechanics
Vertically Integrated Project at Georgia Tech.
- Conducted quantum mechanical simulations using Quantum Espresso.
- Benchmarked the Equiformer_v2 graph GNN model.
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Reinforcement Learning for Stock Trading
Research Project at Georgia Tech.
- Architected a reinforcement learning system focusing on dynamic environment adaptation.
- Designed custom reward functions and non-stationary exploration policies.
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AI Kernel
Design study for an AI-first OS: a polyglot microkernel with a Rust core and Python orchestration. Specified and partially scaffolded, not built.
- Specified a minimal, memory-safe kernel core for hardware abstraction, IPC, and task scheduling.
- Designed a Python orchestration layer for AI workload pipelines, model loading, and GPU resource allocation.
- Proposed a scheduler targeting the bursty, GPU-heavy compute patterns of deep learning.
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OPC & Inverse Lithography Automation
Automated software system for optical proximity correction and wafer print simulation using Calibre and LSF.
- Drove RET/OPC automation (pattern generation, metrology recipe creation) integrated with Calibre/LSF.
- Developed computational models and test masks for technology ramps, meeting strict physical accuracy targets for nodes from 90nm KrF to 5nm ArF.
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ML TCAD Process Modeling
Machine learning-driven physical process simulator using Fourier Neural Operators and image processing algorithms.
- Designed an AI and image processing tool utilizing CD-SEM images to automate process modeling.
- Interfaced with physical metrology tools to auto-generate measurements; defined spatial pattern uniqueness via mathematical entropy of features.
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Analog IC Design
Design and optimization of high-performance analog and mixed-signal circuits using advanced semiconductor nodes.
- Designed low-power Phase Locked Loops (PLL) for Internet of Things (IoT) applications (ranked 1st in Optics track).
- Modeled and optimized two-stage Miller Operational Transconductance Amplifiers (OTA) across multiple process variations.
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Tennis Match Winner Predictions
ML-driven winner prediction platform for professional men’s tennis matches.
- Engineered robust data processing pipeline scaling from 182k raw records to 16k cleaned data points.
- Evaluated multiple models including decision trees, boosting, and neural networks; selected Gradient Boosting.
- Developed an interactive web application using Dash and Plotly showing player head-to-head metrics.
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Randomized Optimization & Clustering Benchmarks
Comparative analysis of randomized search heuristics and unsupervised grouping techniques on high-dimensional data.
- Benchmarked RHC, Simulated Annealing, GA, and MIMIC on constraint satisfaction and neural net tuning.
- Combined K-Means and Expectation Maximization clustering with PCA/ICA to generate features for classification.
- Benchmarked ICA- and PCA-derived feature spaces against the raw features; the study returned a negative result for the randomized-search heuristics against gradient descent.
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Online Fake News Detection
Deep learning natural language processing framework using hybrid Transformer-CNN architectures to detect online misinformation.
- Proposed a comparison of transformer and convolutional architectures for misinformation detection, for the CS7643 Deep Learning team project. Proposal stage; no models were trained.