Taner Topal
Co-Founder & COO at University of Cambridge
Hamburg, Germany
Summary
🤩
Rockstar🎓
Top SchoolTaner Topal is a founder and seasoned technology leader with 11 years of experience building engineering teams and shipping production-grade systems across AI, blockchain, BI, and transportation. As Co-Founder & COO of Adap and now Flower Labs, he combines product vision with hands-on backend engineering—most notably as the creator and transport-layer implementer of Flower, a widely used federated learning framework. He has repeatedly built and grown engineering departments (three so far) and led cloud-native, distributed architectures using Python, gRPC, protobufs, and Kubernetes. A Visiting Researcher at the University of Cambridge, Taner bridges academic research and industry, applying federated ML and distributed computing to real-world finance and mobility problems. Colleagues describe him as someone who hires for long-term performance and cares as much about the problem and process as the end product.
11 years of coding experience
11 years of employment as a software developer
Winter 2023 Batch, Winter 2023 Batch at Y CombinatorDropped out, Electrical Engineering Technologies/Technicians, Dropped out, Electrical Engineering Technologies/Technicians at Technische Universität Berlin
English, German, Turkish
Stackoverflow
1reputation
0reached
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Github Skills (10)
deserialization10
data-serialization10
python10
protobuffer10
protobuf10
grpc10
serialization10
develop9
tensorflow7
machine-learning6
Programming languages (10)
Github contributions (5)
adap/flower
Feb 2020 - Jan 2023
Flower: A Friendly Federated AI Framework
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 1687 reviews, 406 commits in 2 years 11 months
Contributions summary:Taner primarily focused on implementing the transport layer for the Flower framework, which involved creating protobuf definitions and associated Python code for data transfer. They also developed tools related to proto compilation and ensured that proto files were correctly generated and integrated into the project. Further contribution also includes the addition of new methods for the serialization and deserialization of NumPy ndarrays, demonstrating expertise in data handling and protobuf integration within the framework.
federated-analyticsfederated-learning-frameworkmachine-learningkeras-federated-learningflower
jaemin-shin/flower-FedBalancer-testbed
Sep 2021 - Apr 2022
"Flower - A Friendly Federated Learning Framework"-based testbed experiment implementation for FedBalancer (Jaemin Shin et al., ACM MobiSys'22)
Contributions:29 commits in 7 months
pytorchacmfederated-learning-frameworkmachine-learningtestbed
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