Benchmarking and mining social media data for medical device and diagnostics company

• Develop text analytics tool for generating routine monthly social media report for Ortho's data and Ortho's peer data
• Perform benchmarking analysis on Ortho and peers in terms of how we use social media to monitor product quality and engage customers

Social Media

• Supported the social media chair with various charters including social media postings, scientific reporting, blog writing, event planning, analytics, and other activities supporting the NYSCC's membership and events.
• Mentor: Andrea Gafford, Webmaster & Social Media Chair 
• Students: Estelle Gu, Deanna Smith, Charles Xu, Kelly Patraju, Manessa Lormejuste, Britney Yates, Jiayi Yuan, Clarisse Aoanon

Developing Self-Service Analytics for Recording and Trending of Biological Product Deviation Data

• Students built a database to integrate multiple data sources and a user interface for data entry using R Shiny app for analytics, and predictive models/text mining to better manage the BPD reporting process.
• Mentors: Hui Liu and Feng Zeng

HTS Quality Control & Data Correction

• Using R, MBS students created an automatic quality control and data correction program to integrate into WuXi’s HTS analysis process.
• Mentor(s): Christine Brideau
• Students: Harshinder Kohli, Anusha Sarma, Regina Taurino

Corporate Outreach (Funding and Partnerships)

• Students supported the efforts of the Sepsis Alliance in prioritizing their corporate outreach by identifying relevant companies for possible funding and partnerships. Students generated a database of all companies that might be in this space. Students also recommended database tools/apps/etc and implemented them.
• Mentors: Thomas Heymann, Lisa Anderson

Strategies to Monetize CGI’s TOO Test

• Students performed a market research analysis of the oncology diagnostics industry to identify the best commercialization path for CGI’s TOO Test. Students provided a Business Case document including an industry map, PEST, SWOT, Porter’s 5 forces, top line 5-year financials, and a Business Model canvas among other relevant market research analysis tools.
• Mentors: Kishor Bhatia
• Students: Haewon Park, Sebastian Pesantez, Alysse Vindeed, Estelle Ruolan Gu

Data Cleaning & Merging

• Students performed data cleaning and merging of the following data: GIS data, maintenance description data, and operational numeric data.
• Mentors: Jacob Fenno
• Students: Prateek Jain, Kartheek Reddy, Jon McGuire

Project 1

• Students set up an ETL pipeline from scratch using public APIs. Students extracted Twitter data around music artists, and set up a pipeline to make this into a database of tweets and relevant attributes. After an ETL pipeline has been setup, a secondary and different workflow was established to confirm its accuracy. This was done in Python, and used Amazon Web Service (AWS) EC2 & S3.

Project 2

• Analyze on Video Virality, exploring the creation of additional "UGC" videos (third-party generated content on YouTube's network, using R and Amazon Web Services (AWS) EC2.

Project Management Initiative

• Students learned how to conduct an end-to-end project. Project management included: agency analysis, team composition and resource analysis, best practices recommendations, business process and suggested optimization, E-PMO tools, change management, and more. 
• Mentors: Sean Cuttler
• Students: Vandit Narula, Sakina Presswala

Brand Name Growth

• NFBD & VlogU sought MBS students for an interdisciplinary team including IT, social media, data analytics, and UXD. Students conducted social media analysis, usability feedback, creating a survey and apps, SWOT analysis, and more.
• Students: Manish Kakati, Jhanani Ramesh, Alice Chiu, Jose Collantes, Casey Huckel

Associate Analyst Function

• As an associate analyst working for a financial institution, bootcamp educated students on investment banking, fixed income, credit, private equity, and bond rating. Students conducted industry-level analysis and company-level analysis focusing on the chemical industry, including financial forecasting and application of a credit rating methodology and scorecard.
• Mentor: Ben  Nelson

Residence Hall Demographic Analysis

• Students conducted a longitudinal trends examination of student demographic characteristics in the residence halls at Rutgers University-New Brunswick and determined whether there are patterns of self-segregation. Students used data analytics skills and tools to analyze a dataset that spanned 8 academic years with information regarding, campus, building, room number, gender, etc.

Collegiate Recreation Participation on Academic Success

• The goal of this project was to understand the student demographic characteristics of students who utilize the Recreation facilities at Rutgers University-New Brunswick and whether there is a relationship with academic success.  Students used data analytics and visualization to reach this goal.
• Mentors: Dr. Karen Bemis, Dr. Christie Nelson
• Students: Arya Mohandas, Ridhi Tatineni, Kartheek Reddy, Karthik Keertipati, Siddhartha Pachhai

Stadium Research

• Students partnered with a Dept. of Homeland Security research group, Rutgers Police, and other major stadium venues to collect data on the performance of walk-through metal detectors used at stadium venues. The project involved: experimental design, hardware performance testing, data collection, data analysis, site visits, and more.
• Students: Ivan Mera and Aditya Mittal

• Student volunteers helped the NYSCC to build and execute a social media strategy. They attended and reported on NYSCC events and scientific board meetings. They created content that increased member interaction and fostered meaningful connections. Their work included competitive research, platform determination, benchmarking, social media messaging, and audience engagement.
• Company Mentor: Andrea Gafford
• Students: Deanna Smith, Clarisse Aoanan, Estelle Gu, Kelly Patraju, Manessa Lormejuste, Brittany Yates, and Jiayi (Joy) Yuan

Exploratory Data Analysis

• Students were given several railroad related datasets including maintenance and operational data. Text mining was done on datasets, exploratory data analysis was performed, text data was scraped and cleaned and datasets were merged.
• Mentors: Dr. Trefor Williams, Dr. John Betak
• Students: Prateek Jain, Jonathan McGuire, Kartheek Reddy Mondeddu, Glenn Lautenbach

Ballistics Data Analysis (Continued)

• Finalized data visualizations and presented results.
• Hosted by the NJ Ballistics Community of Interest Group who meet quarterly to discuss firearms evidence and processes to present their findings in May 2018
• Presented results in February 2018 to over 50 law enforcement professionals representing multiple agencies including the Bureau of ATF (Alcohol, Tobacco, Firearms and Explosives) from New Jersey and Washington DC, a NJ Prosecutor's Office, several NJ State Police offices, ballistics experts, Rutgers Centers on Policing, CCICADA and the Police Foundation from Washington DC, and others gathered to hear the results of an analysis of New Jersey ballistics data at Rutgers University.
• Mentors: Major Geoffrey Noble, Robyn Johnston, Dr. Christie Nelson
• Students: Aishwarya Gunde, Ingrid Wijaya, U. Saifi

Electronic Medical Records App

• VillageMED is a nonprofit organization which provides healthcare services to children in Haiti. VillageMED has been providing mobile clinics in Haiti, and recorded patient information through paper files. We are working to develop a mobile friendly web app to store patient details electronically. The first phase of the project involved data collection, research, and interviews.
• Mentor: Dr. Sunyoung Kim
• Student: Damini Bhatt

Mergers & Acquisition Financial Case Study

• Build and execute social media strategy through competitive research, platform determination, benchmarking, messaging and audience identification. Set up and optimize company pages within each platform to increase the visibility of company’s social content. Create relevant scientific content for our technical audiences and engage with our membership on an educational level to further the advancement of cosmetic science.
• Mentor: Andrea Gafford
• Students: Kelly Patraju, Estelle Gu, Clarisse Aoanon, Charles Xu, Britney Yates, Deanna Smith, Jiayi (Joy) Yuan

WiDS Datathon

• Dr. Christie Nelson was an official WiDS Ambassador, and Dr. Nelson along with the MBS department hosted a livestream of the WiDS conference as well.
• From their website: The inaugural WiDS Datathon was a joint effort between the Institute for Computational & Mathematical Engineering (ICME) at Stanford, Kaggle, Intuit, West Big Data Innovation Hub, and InterMedia, a grant recipient of the Bill & Melinda Gates foundation, in their Financial Services for the Poor program. The data was collected by InterMedia to alleviate global poverty by learning how to help the world’s poorest people take advantage of widely available mobile phones and other digital technology to access financial tools and participate more fully in their local economies.
• To find out more about the competition, go to www.widsconference.org/datathon.html
• Mentor: Dr. Christie Nelson
• Students: Regina Taurino, Gilat Mandelbaum, Sakina Presswala, Jeffrey Cooperhouse, Bao Chen, Jhanani Ramesh, Chunyu Huang

Stadium Security Data Analysis

• Exploratory data analysis and visualization was performed on hardware testing of walk-through metal detectors which were used in stadium venues.
• Students: Aditya Gandhi, Ivan Mera

Mergers & Acquisition Financial Case Study

• Participated in a boot camp to understand how corporate credit rating works, focused specifically on mergers and acquisitions.
• Mentor: Ben Nelson, Vice President & Senior Credit Officer at Moody’s Investors Service
• Students: Subhadra Akella, Advait Deodikar, Mengxi Liu, Vincent Omolo and Kevin Rupert

Analysis of MIMIC Medical ER Data

• Students first completed CITI training for handling sensitive data and then worked with a medical doctor to analyze hospital ERs and ICU department admissions. This was performed on data from the MIMIC medical database.
• Mentors: Dr. Saqib Baig, Pulmonary & Critical Care Fellow; Dr. Christie Nelson, Assistant Research Professor; and Dr. Karen Bemis, Research Associate
• Students: Siddhant Garg and Denis Ngyuen

Ballistics Data Analysis

• Data science project exploring several ballistic forensic research questions, utilizing data from GUN-OPS and NIBIN.
• Students: Aishwarya Gunde, Usama N. Saifi, and Ingrid Wijaya

Human Rights and The Supply Chain

• 7 in 10 corporate procurement professionals believe forced labor may be in their supply chains. The UK Modern Slavery Act and the Dodd Frank Conflict Minerals disclosure have been regulatory responses to this problem. Students examined this topic, and focused on corporate disclosures on forced labor and conflict minerals in the electronic industry as relating to human rights and the supply chain. A comparative analysis of public disclosures related to the UK Modern Slavery Act and public disclosures related to conflict materials was performed.
• Mentor: Jocelyn Azada
• Student: Jay Patel

Impact Sourcing

• Impact sourcing is an innovative sourcing practice with a mission to eradicate poverty through procurement. This research provided support in the development of resources that would be useful to Nielsen as well as other large companies who are implementing impact sourcing as part of the Global Impact Sourcing Coalition. An analysis of impact sourcing for large corporations was performed, emphasizing success case studies for impact sourcing. The student also created a directory of major impact sourcing companies.
• Mentor: Jocelyn Azada
• Student: Subhadra Akella

Social Label Consumer Data Point

• In recognition of the rise of conscious consumers in the U.S., the goal of this project for Nielsen was to evaluate current data points on forced labor and human trafficking in global supply chains and recommend a consumer-friendly easy-to-use “data point” that could quickly and meaningfully communicate to consumers what the risk of forced labor/human trafficking is for a particular consumer-packaged goods product.
• Mentor: Jocelyn Azada
• Student: Yue Liu

High Dimensional Data Project

• Developed a code and computed the intrinsic dimension of various real datasets (LIDAR data, simulated random data, etc.), comparing different algorithms. Research leveraged work from “Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis” by F. Patricia Medina, Linda Ness, Melanie Weber, and Karamatou Yacoubou Djima.
• Mentor: Dr. Linda Ness, Research Scientist
• Students: Michael Albuquerque, Kafung Mok, Ranvir Singh, and Narendran Sundara Mahalingam

Drone Detection Experiments at a Large Stadium Venue

• Created and implemented an experimental design to understand drone detection software, and then analyzed performance.
• Mentor: Dr. Christie Nelson, Assistant Research Professor
• Students: Yue Liu and Ivan Mera

Social science project involving reviewing literature on the behaviors of violent extremists and then creating recommendations for a government hotline

• Social science project which involved a literature review into behaviors of violent extremists and then creating recommendations for a government hotline number.
• Mentor: Dr. Christie Nelson, Assistant Research Professor
• Student: Ivan Mera

Analysis of a Large Sports Team’s Social Media

• Performed statistical analysis and machine learning modeling on Twitter and Instagram social media data of a major sports team to understand implications for stadium security.
• Mentor: Christie Nelson, Assistant Research Professor
• Students: Ketan Walia and Ivan Mera

Paint & Coatings Financial Case Study

• Participated in a summer long boot camp to understand how corporate credit rating worked and learned to model like a Wall Street analyst. Led by a Wall Street professional. Student groups modeled five of the major paint and coatings companies, identifying relevant financial indicators and key drivers of future financial performance. Students learned to break down global business models, forecast financial performance, identify and analyze key financial metrics, apply real-world analytical methodologies, and compare conclusions to market trading prices for stocks and bonds.
• Mentor: Ben Nelson, Vice President & Senior Credit Officer at Moody’s Investors Service
• Students: Advait Deodikar, Ankita Gupta, Isha Majmudar, Ivan Mera, Vincent Omolo, Daniel Pittaro, Stephen Taras and Jingwei Zhang

Data Visualization & Logistic Regression Modeling of MIMIC ER Data

• Students first completed CITI training for handling sensitive data, next performed a background literature review to learn about the topic of medical ICU waiting rooms, and finally worked with a medical doctor to come up with a project goal that may be useful to hospital ERs and ICU departments while utilizing data available in the MIMIC database. Students extracted patients’ medical ICU data from a large SQL database. Once the students had the data in a usable form (after extracting and cleaning the data), they performed exploratory data analysis on certain data fields of interest, and finally built a logistic regression model to predict if ICU patients were at risk for mortality.
• Mentors: Dr. Saqib Baig, Pulmonary & Critical Care Fellow; Dr. Christie Nelson, Assistant Research Professor; and Dr. Karen Bemis, Research Associate
• Students: Supreet Kaur, Sri Harsha Reddy Devireddy, Karthik Keertipati, Kartheek Reddy Mondeddu and Siddhant Garg

Packaging Project

• Participated in an MBS educational project sponsored by Johnson & Johnson to enhance the consumer experience of an OTC drug delivery system
  • Attended discussions with J&J R&D on the “insights generation to prototype development” process
  • Conducted consumer discussions to uncover insights to drive increased satisfaction with the product usage experience
  • Utilized online category landscape data and consumer insights to generate ideas to improve the primary packaging design
  • Presented lead package design sketches to J&J R&D team for consideration and further development
• Students: Subhadra Akella, Maria Calderon, Princia Contin, Ria Khetan, Isha Majmudar, Vaishnavi Nanjundaswamy, Sebastian Pesantez, and Constantine Siozopoulos

Diverse Learning Survey Analysis

• Analyzed early results from the Diverse Learning Environments Survey to aid Rutgers to understand the campus climate. Preprocessed and analyzed survey data in R and SPSS to understand the question response rate, missing values, and responses. Clustering analysis was also performed.
• Students: Arshi Goyal, Aswani Katari, Shobha Thomas and Hangyu Zhu

Certificate in Intelligence and National Security

• Learned the basics of intelligence analysis and national security and explored current topics in intelligence and national security. Participated in scenario based simulation exercises with guidance from experienced facilitators from NJOHSP.
• Student: Ivan Mera

Inferring Spatio-Temporal Distributional Summaries of Agent Data

• Examined the flow of agents through a large building with respect to spatio-temporal probability distributions. Analyzed entry/exit points for these agents. Determined spatio-temporal distribution of agents (using binary trees). Calculated average paths for agents using same building entry and exit combinations.
• Students: Usama N. Saifi, Ranvir Singh, Narendram Sundara Mahalingam

Learn to Use SAS

• Some students were interested in learning SAS, so they came up with various topics to explore in order to prepare for a SAS Certification.
• Mentor: Dr. Karen Bemis, Research Associate
• Students: Hammad Khan and Sujith Thokala

Professional Sports Team Data Analysis

• Analyzed a patron satisfaction survey with respect to stadium security, and compared with the team’s patron ticket scan data to discover insights when visualized. Scraped social media data relating to the team for one season.
• Students: Winston James, Hammad Khan, Aapta Paresh and Yue Liu