April 2017

Why You Should Apply (Now!) for Microsoft’s Data Science Summer School

Last summer, I was utterly starstruck in the geekiest way possible. My peers and I in the Microsoft Research Data Science Summer School (DS3) had chosen to use Airbnb data for our final project. After we made our presentation to a packed room, a couple of data scientists working at Airbnb reached out to us to express interest in our paper, and we then presented our project to them in private. At the time, I just remember thinking to myself, “This is so cool!”

This Friday, April 21st, is the deadline for this summer’s version of DS3. So, if what you read here sounds interesting and you want to be a part of DS3, there’s no time to waste. Apply today!

DS3 is the brainchild of a handful of awesome Microsoft researchers – Jake Hofman, Justin Rao, and Sharad Goel – who wanted to inspire students and help create a more diverse and accessible field of data science. The program has two parts. First, you learn the equivalent of one semester of data science compressed into four weeks. It’s intense. In the mornings – which usually start around 10AM – renowned senior Microsoft researchers will privately teach you and seven other students cutting edge data science and statistics. No specific background is required, and they always make sure everyone understands what is going on. In the afternoon, you are left to complete a mini data science project, to put into practice the lessons you’re learning.
The second part of DS3 is the final project, which is the focus of the final four weeks. You form a team and work on your project for the entire day. You use real-world datasets to come up with an entirely original research paper. Each team typically has two mentors, and those mentors are there for the entire process: brainstorming research ideas, coding, writing the actual paper, learning how to cite properly and preparing for your presentation. My team’s research paper was accepted into conferences at MIT and the ACM’s Tapia Conference for Diversity in Computer Science, and that could not have happened without the amazing guidance of our mentors. I can’t stress how unbelievably awesome it is to have renowned researchers dedicate multiple weeks to help you write your first-ever research paper. They become your teachers, advisors, recommenders and debuggers. One of them has become an almost parental figure to me, and still advises me on my college classes to this day.

I highly encourage anyone who thinks data science, big data, and artificial intelligence are interesting — you should apply to DS3! You don’t need to be a genius; you just need to be curious and willing to work hard. You will be surprised at how helpful and humble everyone at Microsoft is. To be honest, I didn’t like statistics at all and wasn’t the best at math. But in DS3, you come to realize that quantitative skills are only part of the equation, and that good data scientists must also be creative, reflective and inquisitive. I guarantee you no matter what background you have, DS3 will give you a lifetime of skills, inspiration, friends, and confidence. I’m now working as a Civic Tech Fellow on Microsoft’s Technology & Civic Innovation team – and I wouldn’t be here if I hadn’t taken the leap of faith to spend a summer in DS3.

Data science is at a historic moment because it has already begun to change the way businesses and organizations work. It is applicable to so many more fields than you think. Like how the camera gave computers sight, data science is giving computers millions of new senses to interpret the world. There is a reason Harvard Business Review published an article proclaiming “Data Science: the Sexiest Job of the 21st Century.”  I feel like I am part of something big, I have new superpowers with which to change the world, and it is all very exciting.

The deadline to apply to the Microsoft Research Data Science Summer School (DS3) is this Friday, April 21st. Any interested college student can learn more and apply here.

Using Data Science to Improve Traffic Safety

As U.S. traffic deaths continue to rise, cities across America are increasingly focused on eliminating crash-related injuries and fatalities. Data can be a powerful resource in these efforts to make streets safer.  We’re happy to support this effort, partnering with DataKind, which recently completed the Vision Zero Labs Project. This effort worked to develop valuable analytical models and tools to help the cities of New York, Seattle and New Orleans further their work to increase road safety.

In partnership with DataKind, a nonprofit that harnesses the power of data science in service of humanity, and the New York City Department of Transportation, we launched this project in August 2015, joining forces with the Seattle Department of Transportation and the City of New Orleans’ Office of Performance and Accountability in March 2016. With these cities, the Vision Zero Labs Project has become the first and largest multi-city, data-driven collaboration of its kind to drive traffic safety efforts in the U.S.

Using data science techniques, DataKind accessed open and internal city data to design several models and tools that enable cities to test the effectiveness of various street safety interventions, estimate total traffic volumes and gain additional insight into crash-related factors.

Learn more about our work with DataKind and Vision Zero:

ABOUT DATAKIND

Launched in 2011, DataKind is a global nonprofit that harnesses the power of data science, AI and machine learning in the service of humanity. Through its core programs – Labs, DataCorps and DataDives – the organization brings together leading data scientists and social sector experts to collaborate on projects to tackle some of the world’s toughest challenges. A leader in the Data for Good movement, DataKind was named one of Fast Company’s Top 10 Most Innovative Nonprofits for 2017. Headquartered in New York City, DataKind has Chapters in Bangalore, Dublin, San Francisco, Singapore, the UK and Washington, D.C. For more information visit www.datakind.org

ABOUT VISION ZERO

An initiative born in Sweden in the 1990’s, Vision Zero aims to reduce traffic-related deaths and serious injuries to zero. It has been adopted by more than a dozen U.S. cities including New York and Seattle. Vision Zero believes that crashes are predictable and preventable, which means there is great potential for data and technology to help uncover patterns of incidents so governments can take action to prevent fatalities before they occur.

Creating Safer Streets Through Data Science — A Case Study

Executive Summary

Tens of thousands of people are killed or injured in traffic collisions each year. To improve road safety and combat life-threatening crashes, many U.S. cities have adopted Vision Zero, an initiative born in Sweden in the 1990s that aims to reduce traffic-related deaths and serious injuries to zero.

While many cities have access to data about where and why serious crashes occur, the use of predictive algorithms and advanced statistical methods to determine the effectiveness of different safety initiatives is less widespread. Therefore, DataKind, Microsoft and three U.S. cities — New York, Seattle and New Orleans — came together to help demonstrate how cutting edge and scalable solutions can be developed to help tackle a complex societal issue.

Each city had specific questions that they wished to address around local priorities for increasing traffic safety, to better understand the factors contributing to crashes and the potential impacts of different types of interventions. The DataKind team, working closely with local city transportation experts, brought together a wide variety of datasets such as information on past crashes, roadway attributes (e.g. lanes, traffic signals and sidewalks), land use, demographic data, commuting patterns, parking violations and existing safety intervention placements.

These inputs were leveraged to develop models that allowed cities to examine how different street characteristics impacts the injuries that occur, to determine the extent to which roadway user behavior and street design are contributing factors in crash occurrence and severity, to assess the effectiveness of interventions for increasing safety and guide the placement of future interventions.

The DataKind team also developed a model to help cities accurately and cost-effectively estimate “exposure” or total volume of vehicles on individual streets, a key factor in safety analyses as well as broader transportation planning activities.

Today, as a result of applying these models, the cities are better positioned to determine what kind of engineering, enforcement and educational interventions are effective and how to best allocate limited available resources.

Specifically,

  • In New York, with the new exposure model capability, the city can perform initial safety project feasibility studies more efficiently. When combined with DataKind’s crash models, the new capability will help the city test the potential impact different engineering, land use and traffic scenarios would have on total injuries and fatalities in the city.
  • In Seattle, the city focused on bicycle and pedestrian safety issues in order to gain insights that could contribute to the planning for more than $300 million in anticipated Vision Zero investments. The DataKind models identified collision patterns and factors that contributed to higher levels of injury severity, including whether a motor vehicle is making a right turn or left turn and the effectiveness of crosswalks in reducing crash severity. They also identified key variables affecting the likelihood of accidents taking place on particular stretches of road, including traffic volume, land use, number of traffic lanes, street width and pedestrian concentration.
  • And in New Orleans, the DataKind team created an Impact Assessment tool that will allow the city to compare various locations that are candidates for street treatments, such as bicycle lanes, and to evaluate the impact of implemented treatments over time.

In addition to aiding the participating cities in their efforts to make streets safer, the Vision Zero Labs project showed how data science and collaboration between the public and private sector can help benefit the greater good and produce innovative and scalable solutions to address complex civic issues like traffic safety. Cities around the world can adapt the methodologies and learnings to reduce traffic-related injuries and fatalities in their own communities.

DataKind Vision Zero Initiative: Purpose, Projects and Impacts

Visualization of an early version of the exposure model that estimates traffic volume by street in Seattle. This view shows the difference between the model’s estimates and actual measurements

Tens of thousands of people are killed or injured in traffic collisions each year. To improve road safety and combat life-threatening crashes, more than 25 U.S. cities have adopted Vision Zero, an initiative born in Sweden in the 1990’s that aims to reduce traffic-related deaths and serious injuries to zero. Vision Zero is built upon the belief that crashes are predictable and preventable, though determining what kind of engineering, enforcement and educational interventions are effective can be difficult and costly for cities with limited resources.

While many cities have access to data about where and why serious crashes occur to help pinpoint streets and intersections that are trouble spots, the use of predictive algorithms and advanced statistical methods to determine the effectiveness of different safety initiatives is less widespread. Seeing the potential for data and technology to advance the Vision Zero movement in the U.S., DataKind and Microsoft wondered: How might we support cities to apply data science to reduce traffic fatalities and injuries to zero?

Three U.S. cities — New York, Seattle and New Orleans — partnered with DataKind in the first and largest multi-city, data-driven collaboration of its kind to support Vision Zero efforts within the U.S. Each city had specific questions they wished to address related to better understanding the factors contributing to crashes and what types of engineering treatments or enforcement interventions may be most effective in helping each of their local efforts and increase traffic safety for all.

To help the cities answer these questions, DataKind launched its first ever Labs project, led by DataKind data scientists Erin Akred, Michael Dowd, Jackie Weiser and Sina Kashuk. A DataDive was held in Seattle to help support the project. Dozens of volunteers participated in the event and helped fuel the work that was achieved, including volunteers from Microsoft and the University of Washington’s E-Science Institute, as well as many other Seattle data scientists.

The DataKind team also worked closely with local city officials and transportation experts to gain valuable insight and feedback on the project and access a wide variety of datasets such as information on past crashes, roadway attributes (e.g. lanes, traffic signals, and sidewalks), land use, demographic data, commuting patterns, parking violations, and existing safety intervention placements.

The cities provided information about their priority issues, expertise on their local environments, access to their data, and feedback on the models and analytic insights. Microsoft enabled the overall collaboration by providing resources, including expertise in support of the collaborative model, technical approaches, and project goals.

Overall, the work accomplished by the Vision Zero Labs team proved to be invaluable for the cities of New York, Seattle and New Orleans, equipping them with powerful insights, models and tools that can help inform future planning to prevent severe traffic collisions and keep all road users safe. With this knowledge, the cities can better determine how to best allocate resources and investments towards improvements in infrastructure and policy changes.

In addition to aiding the participating cities in their efforts to make streets safer, the project showed how data science can be effectively used to address complex civic issues like transportation safety. A particular example is the technique developed in this project around estimating road use volume even when complete data is lacking. This technique is relevant both for safety analyses and broader transportation planning activities. These are the kinds of cutting edge and scalable solutions DataKind’s Labs projects aim to deliver to achieve sector wide impact.

The project also showed how collaboration between the public and private sector and amongst partner organizations can help benefit the greater good and result in innovative and scalable solutions to address complex and critical issues like traffic safety. Cities around the world will be able to benefit from the results of the Vision Zero Labs project and can adopt the methodologies and learnings from the work to reduce traffic-related injuries and fatalities in their own communities.

Below are detailed descriptions of the specific local traffic safety questions each city asked, the data science approach and outputs the DataKind team developed, and the outcomes and impacts these analyses are providing each city.

New York: Estimating Street Volumes and Understanding How Street Design Can Reduce Injuries

Map showing street improvement projects locations and change in crashes in New York

Local Question: According to the City of New York, on average, vehicles seriously injure or kill a New Yorker every two hours, with vehicle collisions being the leading cause of injury-related death for children under 14 and the second leading cause for seniors. Looking to improve traffic safety on its streets, the city wanted to understand what existing interventions are working and where there is potential for improvement to help inform how the city can better allocate its resources to protect its residents.

Data Science Approach and Outputs: The team leveraged datasets from New York City’s Department of Transportation, NYC OpenData, New York State and other internal city data to examine the effectiveness of various street treatments to help inform the city’s future planning and investment of resources. Lacking some of the data necessary to address the actual impact of existing street treatments, the team looked to answer other crucial questions regarding traffic safety that could help benefit the city.

Before they could answer these questions, they first needed to answer a more basic one — how many cars are on the road? Knowing the total volume of road users or “exposure” is necessary to understand the true rate of crashes, but most cities don’t have this data available. To overcome this, the team designed an innovative exposure model that can accurately estimate traffic volume in streets throughout the city. The model has two main components. The first is an algorithm that propagates traffic counts on a single street segment to adjacent street segments. It assumes that traffic on one city block is very similar to traffic on adjacent blocks. This process can be run many times and allows one to widely propagate traffic count values along neighboring streets. However, some streets may not have any nearby traffic counts available, so the second component of the model is a machine learning model, with high predictive accuracy, that predicts traffic volumes on streets based on their characteristics.

The team also created a crash model for New York, allowing the city to examine individual locations and test how different street characteristics impacts the number of injuries. For example, the city may be able to look at a particular street and determine whether it is safer for the street to be a one- or two-way road.

Outcomes: The exposure model will prove to be invaluable to the City of New York, filling a crucial void in vehicle volume data that many cities face. With it, the city can now perform initial safety project feasibility studies very quickly and provide context for a variety of other safety research work that requires an “exposure” rate. The model can also be altered to estimate other defined traffic volume measures, like peak hour traffic volumes. It can also help inform future work related to traffic congestion and citywide vehicle usage.

New York can also use the crash models to test the potential impact different engineering, land use and traffic scenarios would have on total injuries and fatalities in the city. They will continue to build upon the work started by DataKind, as the models developed set the stage for future research in crash prediction, congestion relief and city safety projects.

The team was able to leverage the work started in New York City to help develop and refine the approaches for both Seattle and New Orleans.

Seattle: Understanding How Street Design, Driver Behavior and the Surrounding Environment Contribute to Crashes

This “exposure” model developed for New York and Seattle shows estimates of citywide traffic volume, a key piece of information needed for advanced analyses that most cities don’t have

Local Question: While Seattle has seen a 30 percent decline in traffic fatalities over the last decade, traffic collisions are still a leading cause of death for Seattle residents age 5 to 24. Older adults are also disproportionately affected, so this trend could grow as the population ages. To supplement the findings of the City’s Bicycle and Pedestrian Safety Analysis project and provide policy makers and engineers with actionable information for developing and implementing interventions, Seattle sought to find out what mid-block street designs are most correlative with collisions involving vulnerable roadway users and what the probability of such collisions occurring is at identified locations.

Data Science Approach and Outputs: Using Seattle’s collision, roadway traffic, exposure data and environment characteristics, the DataKind team developed models to uncover collision patterns involving pedestrians or bicyclists and determined the extent to which contributing circumstance and street design are correlated with collision rates, as well as the severity level of specific types of crashes. The team also applied the methodology developed for their work with New York to calculate exposure or total traffic volume citywide for Seattle.

By incorporating incident-specific information such as time of day, weather, lighting conditions and behavioral aspects, the team was also able to further develop a crash model to evaluate elements that may contribute to crashes at intersections and to what extent driver behavior, road conditions and street design played a role.

Outcomes: The DataKind team was able to determine several variables that had the greatest impact on mid-block collisions — traffic volume, land use, number of traffic lanes, street width and pedestrian concentration were the most demonstrative inputs associated with collisions.

For instance, it was found that the fact of whether a motor vehicle is making a right turn or left turn at a given intersection will influence the severity of the collision. Researchers were also able to identify in which months of the year incidences of crashes appeared to be better or worse. Interestingly, the number of crosswalks was found to be significant and that more crosswalks at an intersection showed reduction in the severity of crashes.

With these insights, Seattle will be able to pinpoint high risk areas and the factors that can be addressed to help reduce future crashes. The city recently passed a levy to fund multi-modal transportation improvements city-wide and the results from this project, along with additional safety studies, will help guide more than $300 million in Vision Zero investments over the next nine years. 

New Orleans: Evaluating the Effectiveness of Street Treatments

Local Question: While New Orleans hasn’t officially adopted Vision Zero, the city government and community are working together to make roads safer. In 2014, New Orleans was named a “silver” level bicycle-friendly community by the League of American Bicyclists and had the eighth highest share of bicycle commuters among major U.S. cities. New Orleans also leads Southern U.S. cities in bicycle commuting. Yet, a disproportionately high number of the state’s pedestrian crashes occur in New Orleans and the number of bicycle crashes doubled from 2010 to 2014.

To help the city protect its growing number of roadways users, New Orleans wanted to understand the impact that future installation of street treatments, such as bike lanes and traffic signage, could have on preventing traffic injuries and fatalities.

Data Science Approach and Outputs: The DataKind team created an Impact Assessment tool that could be used to test the effectiveness of installed treatments, which would then be used to better inform the placement of future street treatments, both individual interventions and groups of interventions applied simultaneously.

Specifically, the tool takes a set of treatment locations and uses different statistical methods to create sets of comparison locations. These comparison locations are used as a point of reference to gauge the impact of the treatment on traffic safety by comparing crash rates before and after the installation of interventions to similar intersections that did not receive interventions. The tool includes visualizations to examine generated comparison groups, as well as methods for using manually selected comparison groups.

As an example, New Orleans could select a treatment, such as a bike lane, and compare the crash rates before and after the bike lane was installed. The city can then compare these crash rates to other comparison sites. The comparison sites are especially important because they allow the city to prepare for outside factors, such as overall growth in population or traffic. The crash rate could actually increase at a treatment site but this may be due to other factors such as large increases in traffic. When comparing a treatment site with similar untreated sites, we can see if the crash rate increased at a lower rate, thus indicating an improvement in safety due to the treatment. 

Outcomes: New Orleans has integrated the Impact Assessment tool into their systems and will be collecting more data to maximize the tool’s potential and evaluate the effectiveness of additional street features. These findings will help inform the placement of future street treatments.

“Making streets safer for all New Orleanians is a major priority of ours,” said Oliver Wise, director for the City of New Orleans’ Office of Performance and Accountability. 

Learn More:

Fellow Profile: Louise Lai

Where are you from? I was born in Malaysia, grew up in Australia, and now live in New York. I also lived in London and Shanghai. Cue the weird accent.

School/grad year/major: Junior at New York University, double majoring in business & political economy and computer science.

Last thing you searched on Bing“How to download Microsoft Azure for Mac”

Why did you choose Microsoft’s fellowship program? It’s truly a one-of-a-kind program. I chose this over a pure software engineering role because it speaks to my diverse interests in politics, business and computer science. I was in the Microsoft data science summer school last year, and after my project presentation, John Paul Farmer, who I currently work under, came up to me and we started talking about civic tech. The rest is history.

What’s your favorite civic project in the New York? Retrofitting old payphones for WiFi. I like it for its simplicity and what it represents – scrapping the antiquated and moving onto the future.

Who is your civic tech mentor/idol? Obama. Many people don’t realize this, but he was the first president to bring in a team of techies to rebuild the digital infrastructure of Washington, which is now a permanent part of the U.S. federal government. He also created the Presidential Innovation Fellows program. Read this article ‘Obama and his geeks’ and prepare to be impressed.

What excites you about civic tech? The fact that civic tech is just in its infancy excites me. It feels like a startup that is about to take off. Traditionally, government has been resistant to big changes in technology, but now, people are truly seeing the benefit of using big data and cloud services which will only create a brighter future for all.

What’s one problem you hope civic tech will solve for cities? Creating more efficient and inclusive public engagement.

The Rise of Smart Cities, From NYC to Tel Aviv

Israel is a global leader in technology and innovation, giving rise to companies like Waze and Mobileye (acquired last week by Intel for $15B).

Last month I had the pleasure of joining 1,500+ participants in Tel Aviv at iNNOVEX2017, Israel’s premier conference on technology and innovation, at which I met with a number of impressive Israeli startups and gave a presentation on smart cities:

Slides:

Because much has been said about smart cities, I focused my presentation on three truths:

  1. The decentralization of Silicon Valley is causal to the rise of smart cities;
  2. “Smart cities” means many things beyond drones and self-driving cars;
  3. Technology is not the challenge.

Decentralization is good.

Once upon a time, you had to be in Silicon Valley to work in technology.

That is changing domestically and around the world, as resource access is increasingly democratized:

 

Number of venture-capital deals, 2012

The 12 Cities at the Forefront of Global Tech – Savills World Research, Feb 2015

This shift in regional affinity is also contributing to a shift in demographic.

It wasn’t long ago that many technologists looked like this:

Credit: http://readwrite.com/2014/05/02/soma-street-style-hbo-silicon-valley/

That stereotype is rapidly dissolving, as technologists increasingly look like this:

Credit: Gaza Sky Geeks

Credit: The Kemach Foundation in Israel

Members of the White House science, technology, and digital service organizations in 2015.

This growing diversity and decentralization lead to increased access to opportunity and reduced implicit bias in technology. As it relates to smart cities, this also means that technologists are no longer concentrated in Silicon Valley, but are located all across the country and thus more attuned to the needs of their users, resulting in services being designed with (not for) local residents. This intimate familiarity is critical to the success of smart cities, as:

  • what works in Omaha may not work with the hills and seismic activity of San Francisco;
  • what works with the single-story homes and 900+ miles of highway in Los Angeles may not work with the tall buildings and city streets of Manhattan;
  • what works with the Internet connectivity of Kenya (86% coverage of 4 Mbps broadband) may not work with the digital infrastructure of Uganda (12% coverage), despite sharing a border and having roughly similar populations.

It’s not all about drones.

“Smart cities” often elicits thoughts of autonomous vehicles: self-driving cars, delivery drones, etc.

In fact, the most impactful aspects of a city becoming “smarter” are much more fundamental to the fabric of society:

When we expand the scope of what constitutes smart cities, we ensure the application of technology in the most meaningful ways.

Technology is not the challenge.

While recent advances in technologies like machine learning, artificial intelligence, computer vision, etc. have enabled various aspects of smart cities, many of the largest hurdles to adoption are not technological in nature.

Many policy implications exist:

Ethical considerations also exist:

Further resources

There is a lot of activity around smart cities, including an interesting talk by FCC CIO David Bray at SXSW last month and various Smart City Expo events planned for 2017 globally.

Finally, don’t miss Smart Cities NYC ‘17 coming up this May 3–6 in New York!

NYC Computer Science Opportunity Fair Brings STEM to Students

Last week, we partnered with CSNYC, Computer Science for All, the Technology Education and Literacy in Schools (TEALS), and others to sponsor New York’s largest annual college and career inspiration event for CS-oriented public high school students. The fourth annual NYC Computer Science Opportunity Fair hosted over 2,000 students from 60 schools across all five boroughs as well as 90 companies, colleges, and extracurricular programs. Invited students were chosen based on their participation in TEALS, NYC CS4All, and other CS and career and technical education programs. The program’s aimed to excite students about the myriad of educational and professional opportunities that often result from a CS education. By showcasing the culture & products of leading tech companies, the fair nurtures the aspirations of blossoming young technologists.

Colleges, companies, and various extracurricular programs demonstrated the experiences of project-building in academic and workforce environments. Relevant CS departments exhibited current and past research projects and informed students about offerings within their respective programs. Our exhibit booth featured an interactive gaming station as well as the opportunity to Skype with a Microsoft engineer. Most notably popular was our Intelligent Kiosk demo, which used the suite of Cognitive Services APIs to guess students’ ages and emotion relayed via facial expression. HoloLens experiences were also offered for students who wanted to try out augmented reality.

As students perused booths, they had the option to scan their badge’s QR code by staffers. After the fair, students could then use their badge to log into the fair’s web portal and view info about each booth visited. Each check-in was worth an entry in the event’s CS raffle, which awarded prizes periodically during the event. Prizes ranged from gift cards to class visits to prominent tech companies. Microsoft submitted two Xbox One units to be raffled off. Check-ins proved to be hugely popular; By the end of the fair, students had checked into booths 8,100 times!

A very excited winner of an XBox One (photo via csfair.nyc)

Various guest speakers also came in throughout the day for a series of networking, panels, and tech talks. Participating groups included the Tech Leaders Panel, CS@College Panels, Music and Tech Panels, and Lightning Talks. Lightning talk speakers discussed entrepreneurship, data modeling/visualization, computer vision, cloud solutions, online privacy, user research, product management, and more.

Microsoft Tech Evangelist, Adina Shanholtz, demoing HoloLens (photo via csfair.nyc)

Students who wanted more hands-on activities could put their tech skills to work by contributing to one of the four maker space projects. The stations offered students the ability to connect LED diodes to lithium batteries, create electromyography drawings, build real-world Minecraft creations, or engineer CS puppet animations.

Perhaps the most exciting new program addition this year was the first-ever student showcase. Numerous students from around the NYC area submitted computer science projects to be reviewed for participation. Eight outstanding projects were selected as finalists to pitch to a judging panel comprised of notable tech leaders and Department of Ed administrators. After thorough consideration, two winning teams were chosen: CODEX, who compared A* performance using various paradigms, and Digital Dance, who used Sphero robot balls to program a mixed-media performance.

Through interactive and hands-on experience, young New Yorkers had a plethora of opportunities to begin to explore their professional interests. Hardware enthusiasts battled robots, physics fanatics learned about quantum computing, and internet of things aficionados played with wearable electronic devices. Companies and universities varied in size, allowing participants to experience differences and weigh which options might seem most appealing as they launch into postsecondary education. Most importantly, it exposes youth at an earlier age, giving them more knowledge, more options, and more resources with which to build a career.

We extend a huge thank you to all of our volunteers and partners who helped us make this event useful and fun for both students and staff. For more information about the CS Opportunity Fair, check out their website at http://csfair.nyc/.

April’s Civic Tech Events

Happy April!

This month, we’re welcoming spring with these top events in NYC.

April 3rd is the deadline for the (super quick) application for Knight Foundation funding of early stage prototypes to improve the flow of accurate information online. Learn more here.

Plus, DataKind has a special call for proposals! DataKind is working with the Omidyar Network to help bolster the efforts of organizations working to protect rights. DataKind facilitates projects between data science and social sector experts with the end goal of making the social sector organization more effective and efficient. Learn more about the opportunity and apply by April 30th. If you’re selected, you’ll be matched you with a team of data scientists to work with you on a long-term project starting in June.

April 4

April 2017 NY Tech Meetup and Afterparty

Join us for NYC’s most famous and longest running monthly tech event! You’ll see a fantastic lineup of New York tech companies presenting live demos of their products, followed by an afterparty where you can network with the community and meet our demoers and sponsors.

You’re More Powerful Than You Think: A Book Talk With Eric Liu

Join Civic Hall and Eric Liu for the release of his new book, You’re More Powerful Than You Think. Eric will discuss the core laws of power and show that every one of us can upend the usual rules of engagement around power, revamp the narrative surrounding an issue, and effectively deploy our networks and influence to harness our power and use it most effectively.

April 5

NYC BigApps 2017 Workshop: Prototype Testing (Test)

In this workshop, we will live-test our prototypes with users and subject matter experts. We will incorporate users into the design process through this co-creation session and rapidly learn how to better the product functionality and design. We will also focus on different methods for gathering feedback outside of the workshop.

Modern Nonprofit Event – New York City

Calling all New York City area NONPROFIT DECISION MAKERS – you’re invited to a FREE half day event hosted by Microsoft Philanthropies, the Microsoft Citizenship team & Tech Impact.

This is your opportunity to take advantage of the Microsoft Cloud Nonprofits Donation, including the new $5000 yearly Azure credit. Make 2017 the year that your organization lowers technology costs while improving productivity and efficiency. Learn how the Microsoft Cloud is helping nonprofits, just like yours, modernize by elevating their mission using technology.

Run Local: A Conversation with the Young New Yorkers Changing Our Politics

Join the Robert F. Kennedy Young Leaders & the UN Youth Envoy’s Not Too Young To Run campaign for an evening of lively discussion featuring young people engaged in local politics! They’ll be speaking on the importance of civic engagement, the unique power that goofy goobers bring to our democracy, and what it takes to dive in and get involved!

Author Talk: Politics Across the Hudson

YPT-NYC and TransitCenter are excited to host Dr. Phillip Mark Plotch, author of Politics Across the Hudson, for a discussion of his award-winning book chronicling the three-decade struggle to replace the aging Tappan Zee Bridge. Currently an assistant professor and director of the Saint Peter’s University MPA Program, Dr. Plotch has been involved with large infrastructure projects for years, having worked with both the Lower Manhattan Development Corporation and the MTA.

Please join us for a night of insight into what the author learned while researching the Tappan Zee Megaproject, and how some of those discoveries might be able to shed some light on the region’s various other current or proposed large-scale infrastructure projects.

April 6

WE Day New York

Mark April 6, 2017 on your calendar and join us at Radio City Music Hall for our inaugural New York City event that brings together world-renowned speakers, A-list performers, and tens of thousands of youth to celebrate a year of action that transformed communities and changed lives.

NY Hardware Start-up

We’ve got another meetup with some incredible presenters. We’ve got the head of hardware at Citibike, as well as the cofounders of The light Phone and Sunhouse. Bikes, phones and novel drumming, what more could one ask for? Hope to see you there!

Oweyaa Vet Career Connect Lunch

Join OweYaa on April 6th for our first Vet Connect Lunch. The monthly luncheons will provide civilian employment strategies and job search accountability for veterans and military spouses. You don’t want to miss out! Get informed and connected to professionals to discuss your career plan. Learn more about careers within the tech industry that fit your talents. Grow professionally with other veterans and spouses and build competitive skills to ace your next job interview.

April 7-8

Theorizing the Web

April 10

Warm Bodies: Using Data to Measure Room Level Occupancy

Join us for a discussion on measuring room-level occupancy using temperature and CO2 data to better control building operations.

April 17

Understanding Media Studies: “Media and Thermodynamics” with Tega Brain & Nicole Starosielski

Understanding Media Studies: “Media and Thermodynamics” with Tega Brain & Nicole Starosielski

Media Studies invites you to a talk with Tega Brain, Assistant Professor, SUNY Purchase; Fellow, Data & Society and Nicole Starosielski, Assistant Professor, Media, Culture, and Communication, NYU.
Tega Brain is an artist making eccentric engineering, work that intersects art, ecology & engineering. Eccentric engineering reimagines technologies to address their scope and politics, with a focus on externalities and unintended consequences. She has exhibited at Haus der Kulturen der Welt, Berlin, the Science Gallery Dublin, Eyebeam in New York City and the Australian Centre for Design, Sydney. Tega is a fellow at Data & Society NYC and is an Assistant Professor of New Media at SUNY Purchase.

April 19

NYC BigApps 2017 Workshop: Learnings & Iterations (Refine)

At this point of the workshop series, we will focus on next steps and making it real. We’ll practice storytelling to get to the “why” behind the prototype, build a business case for the product, and practice pitching concepts to our key stakeholder groups. Participants and teams will come away with a practiced pitch and evaluative framework to submit to the BigApps 2017 Challenge.

April 25

NYC Bike Future Event

CUNY Tech Meetup

The wonderful folks at Tumblr have kindly invited our CUNY Tech Meetup members to visit their beautiful NYC office space on the evening of Tuesday April 25th at 6:15pm. We will have the opportunity to see Tumblr’s cool redesigned NYC space and hear from some of their engineering team about the creative technology behind this popular microblogging site.

April 27

Urban Tech Hub Launch

New Lab and NYCEDC are thrilled to launch the Urban Tech Hub, a program that supports New York City-based innovators who are building a more sustainable, resilient, accessible and equitable city.

April 28

Digital Future of Work

On Friday, April 28th, 2017, the McKinsey Global Institute and New York University’s Stern School of Business will host the first Digital Future of Work Summit.

The Summit will bring together business executives, entrepreneurs, academics and policy makers to discuss the forces that are shaping tomorrow’s workplace: the rise of freelance, “gig,” on-demand, and other forms of non-employment labor, along with the advent of artificial intelligence and robotics-driven labor automation. We will explore what futures of work are realistic to anticipate, how fast they will emerge, and what must be done by industry and society to prepare. In-depth parallel afternoon sessions will take a deeper dive into specific topics.

April 29-30

NASA Space Apps

Space Apps is an international hackathon that occurs over 48 hours in cities around the world. Because of citizens like you, we continue to grow each year. If you haven’t already, join us to share ideas and engage with open data to address real-world problems, on Earth and in space.