Getting into Gear: Team Gear Shifters of Columbia University Present as Finalists in UNICC Data for Good Hackathon

The UNICC Data for Good: Global Hackathon demonstrated a dedication to the organization’s partnerships with academic institutions, including competitive universities where bright minds of today gather to solve tomorrow’s problems. 

This was true for Columbia University students Archit Matta, Plaksha Kapoor, Saloni Gupta Ajay Kumar, Tushar Agrawal and Yosha Singh Tomar, who are studying for Master’s degrees in Data Science and Business Analytics. The six students knew one another through university courses and had participated in hackathons in the past, including ones geared towards relevant social issues such as the COVID-19 pandemic. 

Driven by the prospect of building models from actual data representing the realities of people around the globe – and to develop solutions towards the UN mandate – the students entered the UNICC Global Hackathon, with the team name Gear Shifters.

UNICC’s Global Hackathon: Data for Good took place on Tuesday, 16 February 2021 with an introduction from the organization’s executive leadership, with a global audience of UNICC and other UN organization staff members, university representatives and over 140 students.

Following introductory remarks from UNICC’s Director Sameer Chauhan and Ninna Roco, Chief of Digital Business Solutions, Anusha Dandapani, Chief of Data Analytics, introduced the three challenges of the hackathon: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualisation Challenge.

Team Gear Shifters opted for Challenge 2: Refugee Crisis: Predict Forced Displacement to build a solution for their final presentation. They began by introducing their data sources: World Bank Group and UNHCR quantitative data on factors such as countries’ currency exchange rates, crisis- related deaths, population densities, life expectancies, GDP per capita – as well as news outlets such as the New York Times for qualitative data on the usage of words in articles written in the last 20 years pertaining to forced displacement and refugee crises. 

With their data, the team developed several visualisations to tie key factors into a model for building out challenge solution. As an example, heat maps demonstrated correlations between Afghanistan’s and Iraq’s input factors on forced displacement. As shown below, the team presented several insights, such as a positive correlation between crisis-related deaths, asylum seekers and internally displaced people (IDPs) for Afghanistan as well as a negative correlation between exchange rates with internal displacement, asylum seekers and refugees for Iraq. 

Chart, treemap chart

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Photo: UNICC

For their final model, Gear Shifters presented two different approaches: a multiple time series forecasting using an XGBOOST regressor and a time series model using exponential smoothing. From both modelling approaches, the team compared their performance based on each key factor’s R^2 value, which measures how well the dependent variable variance is accounted for, to discover that their model using exponential smoothing and random forest regressor was the most effective.

To further solidify their findings, the team evaluated their time series forecasting and stock prediction evaluation with favorable results by calculating the Mean Absolute Percentage Error (MAPE).

Photo: UNICC

Gear Shifter solutions determined, based off their sample model using data from Afghanistan and Iraq, that the key characteristics that determine a country’s prediction of forced migration are mortality rate, life expectancy, population density and battle related deaths. 

The team’s findings aligned with UNHCR’s recent report that the current upward trends in violence in Afghanistan is one of the major causes of forced refugee migration. To demonstrate the effectivity of the model, the team conducted a thorough case study of Syria: they began with a timeline of the Syrian conflict that measured the total number of Syrian refugees, asylum seekers and IDPs. 

The team then cross-examined the course of the conflict and the output of their predictive migration model which reiterated the validity and reliability of their final model solution.

Timeline

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Photo: UNICC

The extensive process of posing correct questions, researching data sets, cleaning the data, building the final model and evaluating its effectiveness came paid off when the team’s presentation was selected as one of the six finalist teams to present in front of esteemed UN judges. 

Following the Gear Shifter presentation, many of the judges were impressed at the comprehensive structure and depth of the solution and posed many questions regarding ways to take their research further, such as how to take natural disasters into consideration in the forced displacement predictions.

In an interview after the Hackathon, the team noted that though there were challenges in gathering “real” data to construct a sophisticated model within the limited time frame, the opportunity to participate in contributing a tool that deals with one of the world’s greatest social causes was invaluable. 

“We want to thank the mentors and their feedback as we corrected and refined our presentation. Participating in the Global Hackathon: Data for Good was unique and inspiring on many levels but most significantly because we, both as a team and as a data-backed community for the UN mission, rise by lifting others.”

Team Gear Shifters

Team Gear Shifter involvement in the UNICC Global Hackathon supports the 2030 Agenda for Sustainable Development, particularly SDG 4: Quality Education, and SDG 9: Industry, Innovation and Infrastructure.

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This article is part of a series of stories from the first UNICC Global Hackathon: Data for Good that took place in February 2021. The hackathon drew registrations from a total of 140 students from 54 universities located in 13 countries around the globe, all of whom came together to tackle three major UN related challenges: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualisation Challenge. To learn more about this successful event and its wonderful finalists, please refer to this article here.

Finalists of Firsts: Team Trojan Army for the COVID-19 Open Challenge

2021 so far has held several ‘firsts’ for UNICC, one being the organization’s first Global Hackathon: Data for Good, where international engagement of ambitious students was a rich and valuable experience for all staff, mentors, students, teams and judges involved. 

In the spirit of ‘firsts,’ one participating team for the first challenge of the Hackathon, the COVID-19 Open Challenge, particularly shared in this sentiment: Team Trojan Army of PSG College of Technology, India, who, in their first year of university embarked on their first data analytics study, entered and became a finalist in their first hackathon.

Asvika M., Narini A., Nithiya Shri S. and Shri Vignesh S. of PSG College of Technology, after a few months of attending their first year of their undergraduate studies, received from their professor a link to register for the Global Hackathon. The four students, who knew each other from their university classes, signed up and entered under the name Team Trojan Army. For the next few days, the students successfully developed a solution that got them into the final.

UNICC’s Global Hackathon: Data for Good launched on Tuesday, 16 February 2021 with an introduction from the organization’s executive leadership to a global audience of UNICC and other UN organizations’ staff members, university representatives and over 140 students. Following the introductory remarks from UNICC’s Director Sameer Chauhan and Chief of Digital Business Solutions Ninna Roco, Anusha Dandapani, Chief of Data Analytics, introduced the three challenges of the hackathon: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualization Challenge.

From the start of the Hackathon, Team Trojan Army faced several obstacles. Notably, though all students were eager to tackle these challenges and learn more about data analytics, none of them had formally studied it; Asvika, Narini and Nithiya are pursuing degrees in Cybersecurity, and Shri in Engineering. 

We split up the work into four different parts, but the first day of the Hackathon was pure learning. We didn’t know how to read the data, how to create the graphs– everything was completely new.

Shri Vignesh S., Team Trojan Army, PSG College of Technology

However, through publicly available instructions on how to effectively navigate data analytics software, the guidance of the mentors and the like-minded tenacity to build the best possible presentation within the fixed time frame, Team Trojan Army delivered and presented as finalists their solution to the COVID Open Challenge.

To build their solution, the students approached the challenge holistically. By using Pandas, Excel and Power BI, they manipulated the data and constructed visualisations of global and national rates of COVID-19 transmission and deaths in the U.S. and in Europe. In addition to data visualisations of trends in the virus itself, the team also provided graphs measuring the economic impact of the international handling of the global pandemic, comprehensively tying in key factors such as a nation’s GDP, unemployment and currency inflation rate. 

Lastly, Team Trojan Army proposed several innovative solutions to the eradication of the COVID-19 pandemic. One of these included the construction of an international facility to oversee the global COVID-19 vaccine distribution as encouraged by the World Health Organization and UN Secretary-General António Guterres

The students also included other suggested solutions to the pandemic such as entrepreneurial economic models and an increase in federal spending to jumpstart job markets, in addition to the creation of a mobile app to facilitate location-based vaccine and virus tracking to curb the prolonging of the pandemic. 

Credit: UNICC

In an interview following the Hackathon, the team commented on how much they take away from the experience. “In one of the mentor sessions,” Asvika recalled, “we learned that the data has a narrative, and we need to create that.” 

The students also mentioned how influential the Hackathon has been to their future plans in the field of data science, learning from the solutions of other finalists and winners. The students came to see first-hand in their research more about the UN and the extent of its work through the data sets provided. “We went from a point of knowing little to nothing to presenting our solutions in front of UN representatives. That in itself was a major achievement for us, nothing short of astonishing.” This was their final first… and just the beginning of a learning journey.

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This article is part of a series of stories from the first UNICC Global Hackathon: Data for Good that took place in February 2021. The hackathon drew registrations from a total of 140 students from 54 universities located in 13 countries around the globe, all of whom came together to tackle three major UN related challenges: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualization Challenge. To learn more about this successful event and its wonderful finalists, please refer to this article here.

SDG 5: Gender Equality in Action: Award Winning Data Visualisation by All-Women Team in UNICC’s Global Hackathon

2020 marked the 75-year anniversary of the United Nations as it continues to speak for international peace and security, deliver humanitarian assistance to those in need, protect human rights and uphold international law. The year also marked the 50th anniversary of UNICC and the five-year anniversary of the launch of the 17 Sustainable Development Goals, a framework for all UN entities and related NGO partner organizations to follow and work collaboratively. 

As a UN organization, UNICC aligns with these goals in its delivery of projects and services to its 70+ Clients and Partner Organizations, particularly in its ability to meld technology with mission. UN Secretary General Antonio Guterres aptly explains this necessary occurrence: “For the UN to deliver better on our mandate in the digital age, we need to embrace technologies that can help accelerate the achievement of the SDGs.”

UNICC’s 2021 Global Hackathon: Data for Good provided an excellent use case for technology for good, including the victory of Team QC Data Oriented, winner of the UN75 Visualisation Challenge. Encouraged by professors Dr. Sophia Catsambis and Dr. Yin Zhou, City University of New York, Masters students Rachel Ramphal, Habiba Aziz, Esther Jenaro Rabadan registered for the Hackathon under as an all-woman team, right away supporting SDGs 5 for gender equality.

Credit: UNICC

UNICC’s Global Hackathon: Data for Good launched on Tuesday, 16 February 2021 with an introduction from the organization’s executive leadership to a global audience of UNICC and other UN organizations’ staff members, university representatives and over 140 students. Following the introductory remarks from UNICC’s Director Sameer Chauhan and Chief of Digital Business Solutions Ninna Roco, Anusha Dandapani, Chief of Data Analytics, introduced the three challenges of the hackathon: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualisation Challenge.

From the beginning of the hackathon, team QC Data Oriented knew that they wanted to specifically create a solution around data visualisation – with this in mind, the all-female team centered their research and graphs around SDG 5 (gender equality). Rachel, Habiba and Esther joined forces to dig through UN data sets related to gender parity, such as data on UN organizations’ monetary expenses and investments by year towards combatting the issue of gender inequality. 

Credit: UNICC

The team also shared a visualisation on the percentage of women in international migration, showing data from 1990 and 2017 and compared the number of female migrants from varying countries with increases or decreases in movement. The visualisation served as a powerful reminder of the interdisciplinary nature of sustainable development and how a single Global Goal, SDG 5 (gender equality), can apply to issues such as international migration.

The panel of esteemed UN judges asked about a specific visualization: the prioritization of gender parity across the UN ecosystem. Qualitative data from surveys reveal the general attitude towards prioritizing issues of gender parity: there is quite a large gap between believing accomplishing SDG 5 today is essential and believing it to become a priority in the next 25 years. 

This discrepancy interested the judges, as it belies an organization’s development in attitude towards discrete SDGs. By presenting this data, the team successfully highlighted the contrast in organizational priorities as to where progress is necessary.

Credit: UNICC

The victory of team QC Data Oriented in the UN75 Visualisation Challenge speaks to a greater message that extends beyond the context of the Data for Good: Global Hackathon. As all-female team winners in a hackathon in a field infamous for the lack of gender parity, Rachel, Habiba and Esther defy the constraints of the very goal on which they successfully presented. 

“My team went into the competition very nervous about our skills measuring up to our peers around the world, but we wanted to participate and try our best. If we had decided to give up, we would not have reached the finals and won our challenge. So, I will take away from this to continue working hard and believing in my capabilities – I hope to take away that no challenge is too big for me.”

Rachel Ramphal, Team QC Data Oriented

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This article is part of a series of stories from the first UNICC Global Hackathon: Data for Good that took place in February 2021. The hackathon drew registrations from a total of 140 students from 54 universities located in 13 countries around the globe, all of whom came together to tackle three major UN related challenges: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualisation Challenge. To learn more about this successful event and its wonderful finalists, please refer to this article here.

Heel of the Boot: University of Salento Team Wins Global Challenge on Predicting Refugee Forced Displacement

In February, two professors at the University of Salento received notice of UNICC’s Global Hackathon: Data for Good. As professors at a university proudly supporting the United Nations Sustainable Development Goals, Antonella Longo, Professor of Data Management & Big Data Management for Decision Making, and Gianluca Elia, Professor of Digital Business, came together to encourage a group of students spanning hundreds of miles, from Italy to Austria, to participate as a data hackathon team.

The students – Enrico Coluccia, Francesco Russo, Riccardo Caro, Giulia Caso, Gianmarco Girardo, Marco Greco and Chiara Rucco – may not have known each other, but they demonstrated a common interest in data science in the context of international humanitarian crises. The students registered as ‘Heel of the Boot,’ referring to the location of Salento University in Italy, and, within several days, successfully constructed the winning solution to the Hackathon challenge on Refugee Crisis: Predict Forced Displacement.

The team we created is characterised by an interdisciplinary profile with vertical and complementary skills such as machine learning, data modelling, data visualisation and innovation management. Beyond this, remarkable empathy flew among us: a creative working group was born.

Team Heel of the Boot

UNICC’s Global Hackathon: Data for Good took place on Tuesday, 16 February 2021, with a global audience of UNICC and other UN organizations’ staff members, university representatives and over 140 students. 

Following the introductory remarks from UNICC’s Director Sameer Chauhan and Chief of Digital Business Solutions Ninna Roco, Anusha Dandapani, Chief of Data Analytics, introduced the three challenges of the hackathon: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement and the UN75 Visualisation Challenge.

Heel of the Boot chose the Refugee Crisis: Predict Forced Displacement challenge and wasted no time in launching their data pipeline. The team began to build their solution by discussing which questions would bear answers that were most pertinent to the challenge. 

Amidst the obstacles of virtual engagement and time restrictions, team members sought the meaning of potential models’ features in regard to the related correlations and trends. It was during this data pre-processing phase, “the most complicated and time consuming in order to avoid the ‘garbage in, garbage out’ effect,” that the team developed a synergy to carry through their time together. 

The different and complementary skills of each team member were precious, and each team members’ comments allowed us to adequately investigate the diverse aspects and issues related to the challenge.

Team Heel of the Boot

Following the selection of the features of their model, Heel of the Boot could integrate data sources into a final data set. With the use of one hot-encoding technique among other efforts to ensure the quality of their data, the team’s final data set consisted of about 300 data entries, each representing a specific year, an origin country and a destination country.

They next analysed their data by adopting various machine learning models for multiple regression, using 80% of the data for training the model and 20% for testing. Through this process, the team chose Random Forest Regressor to illustrate and prioritise a level of interpretability in their findings. In addition, the team came up with supplemental predictive data models and other data analyses to contextualise potential causal outcomes. 

Credit: UNICC

Team Heel of the Boot’s final presentation, which married their models’ findings and background analyses, produced impressive results. Out of various concluding predictions, one most notable findings were predictions of Sudan, Sweden, Afghanistan and Ukraine as the primary countries of origin for refugees by 2024. Their presentation brought questions from the judges on the inclusion of Sweden as an outlier result. To these inquiries, team member Francesco Russo explained that “this seemingly reliable model we built is pointing towards some other influence, apart from the main factor of political instability that is shown in the other examples, that has the power to change the course of future predictions.” 

“If a model only reflects what we already know from the past, then it is not a model.”

Francesco Russo, Team Heel of the Boot

Team Heel of the Boot described their Hackathon experience as a surprising experience for not only the cohesiveness and coherence of a disparate team that yielded impressive results, but also the underlying philosophy in using skills in data for the betterment of lives on an international scale.

The students hope to expand upon their research by incorporating more data to build more sophisticated predictive models in future Hackathons and other educational endeavors.

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This article is part of a series of stories from the first UNICC Global Hackathon: Data for Good that took place in February 2021. The hackathon drew registrations from a total of 140 students from 54 universities located in 13 countries around the globe, all of whom came together to tackle three major UN related challenges: Covid-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualisation Challenge. To learn more about this successful event and its wonderful finalists, please refer to this article here.

Abraca-Data: A Team of Young Talent, Forged by Chance, Fortified by Data

Several days before the start of the UNICC Global Hackathon: Data for Good, five students from five different universities in India received an email from UNICC informing them they would be participating in the hackathon together as a team. Himanshu Bajpai, Birla Institute of Technology and Science in Pilani; Aanisha Bhattacharyya, Institute of Engineering and Management in Kolkata; Foridur Rahman, Savitribai Phule Pune University in Pune; Swaraj Priyadarshan Dash, Silicon Institute of Technology in Bhubaneswar all registered individually without knowing each other or what to expect. 

Our team consisted of students from India with an enthusiasm for data science… Our participation as a team was entirely a stroke of luck.

Himanshu Bajpai, Birla Institute of Technology and Science, Pilani, India 

UNICC’s Global Hackathon: Data for Good launched on Tuesday, 16 February 2021 with an introduction from the organization’s executive leadership to a global audience of UNICC and other UN organizations’ staff members, university representatives and over 140 students. Following the introductory remarks from UNICC’s Director Sameer Chauhan and Chief of Digital Business Solutions Ninna Roco, Anusha Dandapani, Chief of Data Analytics, introduced the three challenges of the hackathon: COVID-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualization Challenge. 

Himanshu, Aanisha, Foridur and Swaraj registered under the name Team Abraca-Data and opted for the Covid-19 Open Challenge. The challenge called for measuring the socioeconomic impact of the pandemic, identifying key stakeholders in managing the outbreak and forecasting the impact of phased vaccination cycles.  

The team began by breaking apart the segments of the challenge and delegating the analytic workstreams to members of the team: Swaraj focused on government measures implemented in developing countries, Aanisha investigated the global vaccination drive, Foridur observed the socio-economic impact of Covid-19 and Himanshu found trends in overall transmission of the virus. All of the students brought their individual fortes in data analysis, statistics and interpretation to approach their respective areas of research.  

Despite their varying approaches, all students on the team collectively agreed upon one thing: to look for trends not already known. Instead, the students focused on finding new insights, particularly how the Covid-19 virus is transmitted among children, the resulting behavioral changes in societies and patterns in the vaccination drive with other key international factors. They looked into data sets from the European Centre for Disease Prevention and Control, Johns Hopkins University, New York Times, The Covid Tracking Project, and UN data sets such as OCHA Coronavirus (Covid-19) Vaccinations, all of them open source. 

They found that the number of children testing positive was actually in regard to the number of cases identified as positive in Italy. The team presented that on average, 1/12 of all positive Covid-19 cases in Italy were children less than 15 years old, effectively marking a correlation between the number of cases among children and the general population that has the potential to guide future policy decisions in the pandemic. 

Credit: UNICC
Credit: UNICC

Additionally, the team presented a word cloud visualisation that was built from various data sets, including the ACAPS COVID-19 Government Measures Dataset which consists of related intel across sources from governments, media, the United Nations and other organisations. By building this visualisation, team members offered insight on shifts in public opinion through the observation of common verbiage, such as “Violence” and “Alcohol” pertaining to individual behavior and “Sanitation” and “Unemployment” related to government response. 

One thing that we were clear about though, was that we won’t try to find trends and patterns that we were already aware of. Instead, we’d try to discover new insights. 

Team Abraca-Data 

The final section of their presentation focused on the global vaccination drive, where they started by looking for correlations between countries that are leading the vaccination drive, such as Israel, Chile, United Kingdom and Serbia, and their ranking in GDP per capita. They also focused on other trends such as data concerning the overall rate of vaccination and the return rate for the second dose for Moderna and Pfizer/BioNTech vaccines. 

The team’s meticulous research and valuable data insights won them first place in the UNICC Global Hackathon Challenge 1: Covid-19 Open Challenge, where they were competing against four other teams. Furthermore, their award-winning project allowed for the development of their data skills capabilities and provided data-driven insights, addressing two of UNICC’s data strategy goals in alignment with the UN Secretary-General Data Strategy

When recounting their Hackathon experience, Abraca-data members expressed an overwhelming appreciation and an enriching experience. They thanked their mentors, whose dedicated attention and helpful feedback “only motivated us to push harder.”  

Team members aim to continue their collaboration and build upon their research, such as incorporating more data on vaccinations, for future presentations and publication. 

This article is part of a series of stories from the first UNICC Global Hackathon: Data for Good that took place in February 2021. The hackathon drew registrations from a total of 140 students from 54 universities located in 13 countries around the globe, all of whom came together to tackle three major UN related challenges: Covid-19 Open Challenge, Refugee Crisis: Predict Forced Displacement, and the UN75 Visualization Challenge. To learn more about this successful event and its wonderful finalists, please refer to this article here.