Workshop: Achieving Optimized Trading Analytics & Execution Quality (New York) 
Start Date: October 01, 2019
Start Date: October 01, 2019

Fast, Scalable, and State-of-the-Art:
Achieving Optimized Trading Analytics and Execution Quality

NOTE: If the registration form to the right fails to load for any reason, please email your contact details to to register. We will process your registration manually.

This full day workshop is designed for people who want to make full use of their data environments in trading analytics applications. It’s tailored for traders, quants, IT engineers and developers, and compliance people who wish to learn most efficient ways to manage and move trading data, and analyze it down to the nanosecond level.

Workshop Details

When: Tuesday, October 1, 2019 from 9:00am-6:00pm

Where: Nasdaq MarketSite, 10th Floor, 4 Times Square, New York, NY 10036


  • Registration and breakfast: 8:00am-9:00am
  • Morning Workshop Sessions 9:00am to 12:30pm
  • Lunch with special guest speaker Xuyang (Bill) Lin, Senior Data Scientist,
    NASDAQ Machine Intelligence Lab
    Topic: Reinforcement Learning on Alternative Data: 12:30pm to 1:30pm
  • Afternoon Workshop Sessions 1:30pm to 5:00pm
  • Reception 5:00pm to 6:00pm

Cost: Free to qualified attendees

Trade execution is critical to competitive advantage, so how do you optimize it? What are the primary challenges to building trading analytics solutions? How do you select the right technologies for your firm based on your unique requirements?

Experts from NASDAQ, AquaQ Analytics, MemSQL, Confluent, and Altair will explore new approaches to the challenges to optimizing execution, and the role new technologies can play in improving your analytics capabilities for trading and market data. We will examine best practices for building your own unique trading analytics user interfaces focused on best execution, market activity, and client flow, and discuss new technologies and developments that may be incorporated into the stack for even better decision making and execution going forward.

Attend to learn about:

  • Recent advances in database technology, and how to optimize the use of time series data
  • Building visual analytics and stream processing applications that provide clear, comprehensive views of trading activity
  • Challenges to success
  • Best practices for selecting, implementing, and integrating the tools you need to create an efficient and cost-effective technology stack

Who should attend:

  • Heads of trading
  • Traders
  • Quants
  • Compliance officers and managers
  • Trading system architects and engineers

Detailed Agenda

  • 8:00am to 9:00am: Registration and Breakfast
  • 9:00am to 9:15am: Introductions
  • 9:15am to 10:00am: Analytics in the real world: Building a scalable real-time & time series data infrastructure (hands-on training)
  • 10:00am to 10:45am: Maximizing your kdb+ investment using visual analytics and event processing(hands-on training)
  • 10:45am to 11:00am: Break
  • 11:00am to 12:30pm: Build trading analytics dashboards with proactive alerting (hands-on training)
  • 12:30pm to 1:30pm Lunch – with special guest speaker:
    Xuyang (Bill) Lin, Senior Data Scientist, NASDAQ Machine Intelligence Lab
    Topic: Reinforcement Learning on Alternative Data
  • 1:30pm to 2:30pm: Build stream processing applications without coding
    (hands-on training)
  • 2:30pm to 3:00pm: Panopticon product development roadmap
  • 3:00pm to 3:15pm: Break
  • 3:15pm to 4:45pm: Panel Discussion: Do’s and don’ts of building effective trading analytics systems
  • 4:45pm to 5:00pm: Summary and how to get more information
  • 5:00pm to 6:00pm: Reception

Our Special Guest Speaker

Xuyang (Bill) Lin
Senior Data Scientist
NASDAQ Machine Intelligence Lab

Xuyang (Bill) Lin is a Senior Data Scientist at NASDAQ’s Machine Intelligence Lab, a group dedicated to the development of Artificial Intelligence, Large Scale Optimization, Stochastic Simulation and other advanced computational solutions for financial market ecosystems. His research interests center around applying cutting-edge machine learning techniques in the fields of derivatives, alternative data exploration, portfolio construction, and model surveillance. Xuyang holds a Masters of Finance degree from the Massachusetts Institute of Technology and a Bachelors in Mathematics from Renmin University of China.

Our Faculty

Ludvig Sandman
SVP Product Engineering

Ludvig Sandman is the head of development and chief architect for Altair Panopticon. Ludvig was the co-founder of Panopticon Software AB and has been the product’s Chief Architect since 2002. Ludvig drives technical architecture, product innovation, strategy, development process and platform, and systems integration, and leads the development and QA teams in Stockholm and Delhi. Prior to Panopticon, Ludvig was a Senior Developer for Brunswick Direct, an emerging markets brokerage. Before that he worked in software consultancy roles in the financial and telecommunications sectors for Elit Logik. Ludvig studied Computer Science and Information Systems at the Royal Institute of Technology (KTH) in Stockholm.

Bruce Zulu
Field Engineering Lead

Bruce Zulu leads the team of engineers who work directly with client organizations to implement Altair Panopticon Steaming Analytics. Bruce has extensive experience in capital markets and IT infrastructure engineering and has been working with the Panopticon platform since 2013. He was also business development director for Kx Systems for several years and held positions at Barclays Capital and Morgan Stanley. Bruce holds a Bachelor of Science degree in Multimedia Computing and Computer Science from the University of Wales.

Mark Lochbihler
Director, Technical Alliances

Mark has 30 years of experience working with advanced analytics, distributed computing, and data platforms. He works at MemSQL as the Director of Technical Alliances, focused on helping customers leverage modern operational and analytic capabilities to achieve a competitive advantage. Mark has a Bachelor of Science degree in Computer Science from North Carolina State University and holds a Six Sigma Black Belt.

Andrew Barrow
Vice President
AquaQ Analytics

Andrew is a kdb+ developer at AquaQ Analytics. He has worked as a consultant in some of the world’s largest financial institutions and has extensive experience in the design and implementation of global software and data solutions. He has delivered talks and presentations on various aspects of kdb+ and combining kdb+ with Panopticon, and most recently spoke at an annual AquaQ user conference in London. Andrew holds a Master of Science degree in Applied Mathematics and Physics with First Class Honors from Queen’s University Belfast.

Fotios Filacouris
Senior Systems Engineer

Foti has spent the better part of his career focusing on Open Source technology, with experience varying from NoSQL, Big Data and traditional RDBMS technologies. Recently Foti has focused on Distributed Systems, with knowledge and expertise Architecting for Fortune 500 organizations. Foti has experience speaking to some of the largest Java Groups in the world, as well as Open Source Meetup groups all over the United States. Foti is based in New York. He helps people understand complex concepts in distributed technology, from microservice-oriented architectures to decoupling services to more traditional monolith migrations.

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