Hi! I'm

DONALD
A RESEARCHER
AN AI STUDENT
AN INNOVATOR

MSc student at the University of Trento, specializing in Artificial Intelligent Systems. Currently researching VQA & Scene Graphs at Polytechnic University of Milan's AIRLab.

Find me online

About Me

Hey! I'm Donald — a software engineer and AI researcher with a passion for building intelligent systems that bridge the gap between research and real-world applications.

I'm currently pursuing my MSc at the University of Trento, where I focus on machine learning, computer vision, and NLP. My thesis work at Polytechnic University of Milan's AIRLab explores Visual Question Answering and Spatio-Temporal Scene Graphs.

Before grad school, I earned my BSc in Computer Science from Ca' Foscari University of Venice, where I worked as a Research Assistant on ML model watermarking — work that resulted in a publication at EDBT 2025.

Outside of academia, I work part-time at Cluster Reply as a backend developer, and I enjoy competitive programming on Codeforces where I've achieved the rank of Specialist.

I'm always open to research collaborations, interesting engineering challenges, and conversations about AI. Feel free to reach out!

Programming Languages

PythonC#JavaScriptTypeScriptSQLJavaC++

Areas of Interest

Computer VisionDeep LearningNLPMachine Learning

Experience

Part-Time Backend Developer

Aug 2024 — Present

Cluster Reply

  • Developed C# customizations to deliver client-requested features, reducing manual effort by 15+ hours per week through automation of key processes.
  • Resolved functional and performance bugs in test and production 30% faster than role-level expectations using debugging, logs and SQL.
  • Collaborated on 4+ D365/AX projects, focusing on Finance, Supply Chain, and Manufacturing modules, leveraging C# and SQL.
C#D365/AXSQL

Research Assistant

Feb 2024 — Jul 2024

Ca' Foscari University of Venice

  • Co-authored verifiable ownership of tree-ensemble models by implementing a trigger-set watermark with only a 2% accuracy overhead.
  • Enhanced watermark robustness against removal attacks, leading up to 25% reduction in attack success rates.
  • Established anti-forgery bounds using Z3 SMT solver; the best counterfeit achieved 14% of the genuine signal and reduced test accuracy by 30–40 percentage points.
Pythonscikit-learnNumPyPandasMatplotlibZ3 (SMT)JupyterGit

Education

Thesis Research — VQA & Spatio-Temporal Scene Graphs

Feb 2026 — Present

Polytechnic University of Milan — AIRLab

Working on Visual Question Answering and Spatio-Temporal Scene Graphs.

MSc in Computer Engineering — Artificial Intelligent Systems

Sep 2024 — Present

University of Trento

GPA: 3.8 / 4.00

Relevant Coursework

Machine LearningDeep LearningNatural Language ProcessingComputer VisionAutonomous Software AgentsFundamentals of Artificial Intelligence

BSc in Computer Science

Sep 2021 — Jul 2024

Ca' Foscari University of Venice

GPA: 3.9 / 4.00

Relevant Coursework

Data and Web MiningDatabase SystemsData Structures and AlgorithmsSoftware EngineeringOperative SystemsFormal Languages and ComputabilityObject-Oriented Programming

Projects

Selected work from research, university, and side projects.

University

Few-Shot Adaptation for Vision-Language Models

Proposed GaCoCoOp with fixed visual attribute tokens for few-shot CLIP adaptation, improving novel class accuracy by +6.31% over CoOp and +1.93% over CoCoOp on Oxford Flowers dataset.

PythonPyTorchJupyter
University

Computer Vision Liquid Height Measurement

Achieved ±3mm accuracy in non-contact liquid measurement using pixel-to-metric ratio calibration and OpenCV checkerboard pattern detection for real-world dimension extraction.

PythonOpenCVNumPy
University

DeliverooAgents

Built two autonomous agents for a grid-based parcel-delivery simulation game using an event-driven client and BDI architecture.

JavaScript
Research

Watermarking Decision Tree Ensembles

Co-authored a novel approach to verifiable ownership of tree-ensemble models through trigger-set watermarking with minimal accuracy overhead. Published at EDBT 2025.

Pythonscikit-learnZ3 SMTNumPy

Publications

Watermarking Decision Tree Ensembles

EDBT 2025

Stefano Calzavara, Lorenzo Cazzaro, Donald Gera, Salvatore Orlando

28th International Conference on Extending Database Technology (EDBT 2025)Barcelona, Spain — Mar 25–28, 2025

A novel approach to verifiable ownership of tree-ensemble models through trigger-set watermarking.

Get in Touch

I'm always open to interesting conversations, research collaborations, and new opportunities. Feel free to reach out through any of the channels below.

Italy, Milan