Daniel Svonava

Superlinked

superlinked.com makes it easier to turn data into vector embeddings

Co-Founder & CEO

creable.io

creable.com is the world's biggest influencer database (300M creators)

Advisory Board Member

Tater Games

tatergames.com is a data-driven game studio

Board Member

Primeflow

primeflow.com built tools for super-connectors and their network-driven business

Founder & CTO

Google

2016 - 2018
Tech-lead for YouTube Reservation Ads forecasting (Can a reservation be booked or not?) and pricing (How much should we charge for it?).

2015
Tech-lead for YouTube Video Ads traffic prediction and cross-Google Ads reach prediction, enabling ad buying in Adwords and DBM.
Focus on making Google Ads useful for Brand advertisers.

2013 - 2014
Within YouTube monetization I'm constantly switching between being an analyst who organizes and makes sense of data, builds prototype visualizations and spreads around the insights to help decision making and product design and being an engineer who uses these insights to build useful production systems.

Senior Software Engineer

47pixels

We were a software startup in the Story-telling space. Major products:
47posters - B2B SaaS for Print Service Providers launched in 7 countries
memoarc - B2C storytelling photogallery
dofsome - B2C minimalistic, high-quality photo hosting.
Reach out to me for a complete portfolio.

Co-Founder

Exploratory large-scale information mining from unstructured data. Patent granted.

Software Engineering Intern

IBM Research

Joined the Information analytics group within the Mathematics and Computer Science department again to continue my work on matrix reordering and co-clustering remotely via IBM SK.

Research Internship

Joined the Information analytics group within the Mathematics and Computer Science department. Co-authored a research paper involving graph theory, clustering and visualization. Worked on a web-based marketing intelligence tool employing data-mining techniques and back-end infrastructure optimization.

"Great Minds" Research Internship

Slovak University of Technology

The course is called Development of effective algorithms and programs. I prepared problem statements and solutions for assignments and competitions. I also set problems for ProFIIT, national programming competition for High school students.

Teaching assistant

Vector Compute @ Superlinked | xYouTube

➡️ Building a compute framework for turning data into vector embeddings.
🤗 Connect your data infrastructure to your vector database with Superlinked.

Join our product preview:
📋 Try it out in a Python notebook with no dependencies.
↗️ Design the perfect vectors for your retrieval use-case.
🔧 Mix and match streaming, batch, structured and unstructured data.
🚀 Launch to production with your favorite Vector Database.

➡️ Let's sort out information retrieval across your organization!
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Previous:

Daniel is a Senior Software Engineer at Google, where he tech-leads, designs and builds forecasting & pricing systems for ads worth billions of dollars. These are distributed systems that run on thousands of machines, process terabytes of data per query and combine Machine Learning modeling with game-like simulation of tens of thousands ad campaigns - all happening in real-time to enable thousands of concurrent users of buying tools like AdWords and DBM.

Daniel wields a rare combination of deep technical skills, a user-centric drive and an ability to align multiple teams towards a common goal - launching and landing high quality cutting edge products.

Daniel co-founded a tech startup that brought machine vision to the consumer photo space 10 years ago, he was an invited speaker at an ML dev conference in Zurich and speaks at startup events regularly. He holds multiple patents with Google, is published in a peer-reviewed ML journal from his time at IBM Research and is a Google Code Jam on-site finalist.

On weekends he flies, climbs, skis and bikes in the Alps, see: http://instagram.com/mountain.supo

Data Science Dojo

Leading a passionate team aspiring to build the best data science and generative AI company.

Founder and CEO

Stanford University

Learned necessary lessons as first time entrepreneur, sometimes the hard way.

Entrepreneur

Microsoft Corporation - AdCenter Ads Relevance Team

•	Feature Engineering for improving relevance in Bing Ads.
•	Worked on adding new semantic, user and advertiser features.
•	Added new data to training pipeline based on the user and advertiser DSATs.

Software Development Engineer

•	Solid understanding of paid search advertising marketplace.
•	Performed thorough analyses to understand any shifts in user or advertiser behavior in the marketplace.
•	Worked on delivering RAIS (Rich Ads in Search) feature.  Developed a deep understanding of selection, relevance, click prediction, online auctions and delivery mechanism of ads in paid search.

Applied Researcher / Data Scientist

•	Worked as a software engineer and data analyst for Bing data mining team.
•	Gained deep experience in web analytics, big data, ETL, online experimentation and Microsoft proprietary tools for mining large scale data.
•	Performed business critical analyses and investigations for live site issues
•	Defined, implemented and validated metrics for online experimentation.
•	Regularly worked with the feature and partner teams in designing, running and evaluating online experiments.
•	Conducted a series of machine learning tutorials for beginners. The tutorials have been a recommended resources for new employees at Microsoft Online Services Division
•	Conducted tutorials on online experimentation, A/B testing and R programming.
•	Regular presenter at Bing new employees’ boot camp. 
•	Managed an intern who worked on an automatic anomaly detection tool.

Software Development Engineer / Data Analyst

Tulane University

Selected Projects
•	Cost-Sensitive Learning: Worked on cost sensitive and importance weighted learning approaches for robust classification. These methods provide robust classification performance in situations when the cost of misclassification is highly non uniform. Possible domains of application include credit card fraud detection, direct marketing, automatic target recognition etc.

•	Classifier Fusion: Proposed a novel classifier fusion technique based on AdaBoost. The approach was validated in various domains such as texture classification, face detection and DNA molecule classification.

•	Fuzzy Classifiers for Object Detection: Proposed a strategy that uses AdaBoost to perform selection of a large number of fuzzy classifiers combined with a component based approach for robust object detection. The work received honorable mention at NAFIPS 2005.

Graduate Research Assistant

ATI Research

Computer Vision, GPGPU, C, Matlab, Image Processing.

Intern Researcher

Transmeta

Perl, Verilog, Tcl/Tk, Formal Verification

Intern Software Engineer

University of Central Florida

•	Taught an undergraduate level course in C Programming (~120 students, 3 credit hours)
•	Managed three teaching assistants who were helping in grading quizzes and exams
•	Prepared lesson plans, quizzes, labs and exams

Lecturer

FedEx Services

Intel Corporation

JPEG2000, Image Processing, Image Compression, Huffman Coding, Wavelet Transform

Experienced data scientist and entrepreneur. 
Founder and lead instructor at Data Science Dojo. 10,000 aspiring data science professionals from 3000+ companies trained globally, and growing.

taplio

The Battle

Daniel Svonava

Raja Iqbal

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