Giacomo Domeniconi
AI Leader Principal Research Scientist And Manager SVP at U.S. Bank
Miami, Florida, United States
Summary
🤩
Rockstar🎓
Top SchoolGiacomo Domeniconi is an AI leader and Principal Research Scientist with seven years of professional experience, currently leading researchers in the AI Center of Excellence at U.S. Bank as an SVP. He blends deep academic roots—a PhD in Computer Science and postdoctoral work on cross-domain classification—with industry research at IBM focused on accelerating large-scale ML and DL systems. At U.S. Bank he bridges long-range AI research (3–5 year horizons) with applied data science and executive stakeholder management, translating future capabilities into near-term use cases. He has taught high-performance machine learning at NYU and co-founded a startup applying churn and segmentation models to marketing, showing a rare mix of hands-on algorithm design, product intuition, and team leadership. Based in Miami, he is comfortable navigating both low-level optimization (SGD/ASGD, distributed ML) and strategic AI adoption across enterprise contexts.
7 years of coding experience
5 years of employment as a software developer
ITI "Blaise Pascal" CesenaDoctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at Alma Mater Studiorum – Università di Bologna
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (14)
deep-learning8
gpu8
machine-learning8
python8
dax7
neural-network6
tensorflow6
numpy5
graph4
acceleration3
gpu-acceleration3
graph-convolutional-networks3
tensor3
autograd2
Programming languages (1)
Github contributions (5)
giacomo-domeniconi/Project_CodeNet
May 2021 - May 2021
This repository is to support contributions for tools for the Project CodeNet dataset hosted in DAX
Contributions:1 push in 1 day
hosteddaxdataset
IBM/EvolveGCN
Nov 2019 - Nov 2019
Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Contributions:3 pushes in 1 day
graph-convolutional-networksconvolutionalconvolutional-networksdynamic-graphsgraph-neural-networks
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