2014 I&E Summer Scholars Projects - Systems & Enterprises

1. SMART CITY: CITY SERVICES, BUILDING, AND DISASTER PLANNING

Using an existing serious gaming platform and the Complex Systems lab environment, explore the introduction and proliferation of sensor-captured data regarding city analytics for Hoboken.  Output should be useable by city safety officers, event planners, traffic flow and analysis in real-time (using actual traffic feeds).   Flood research will also be considered, extending to modeling wind flows between buildings.  The outcomes from this development effort will generate data for further processing via data-mining and system analysis techniques, to enhance daily operations and natural disaster planning/prevention.  Programming knowledge preferable, knowledge of C# would be ideal.

Advisor: Dr. Robert Cloutier
rcloutie@stevens.edu
Ext: 5378

2. SMART CITY: HOSPITAL/HEALTHCARE DELIVERY ANALYSIS

Using an existing serious gaming platform and the Complex Systems lab environment, develop a domain for healthcare delivery analysis and adaptation.  Create visual representations of operating room activities and actors, emergency room situations, and a hospital wing devoted to patient care.  Modeling will address a mid-size metropolitan hospital.  Background support systems can also be modeled including: maintenance, food service, physical therapy, testing and imaging, etc.  Outcomes will be evaluated in terms of increased efficiencies and improved medical outcomes.  Programming knowledge preferable, knowledge of C# would be ideal.

Advisor: Dr. Robert Cloutier
rcloutie@stevens.edu
Ext: 5378

3. ENERGY BALANCE & SUSTAINABILITY DASHBOARD

Using existing time series data gathered from the Stevens entry in the Solar Decathlon, develop a programmatic dashboard to determine energy loads and balances throughout the structure, to enhance the livability of the structure and minimize the energy costs of operation.  Examination of the system dynamics should also include other support systems which can also be modeled, but the initial focus is on energy balance and sustainability.  Outcome will be evaluated in terms of increased efficiencies and reduced energy costs.  Excel skills required, knowledge of R, Python preferable.

Advisor: Prof. Eirik Hole
ehole@stevens.edu
Ext: 8308

4. DEVELOPING AN INTELLIGENT ROBOTICS PLATFORM FOR BETTERMENT OF HUMAN LIFE

This project will help develop two robotics platforms: Roy and Rob. Roy is essentially a mini-computer equipped with cameras, wheels, and actuators. It has the ability to actively interact with its users and the environment through motion, along with cameras, speakers, microphones and the screen. The project will actively develop software and help build Roy prototype 1. Rob is a stationary robot equipped with cameras, GPS, and acoustic sensors and worn on the head in the form of special spectacles. It is designed to interact through voice with vision impaired people to make them aware of their surroundings.  It is essentially Roy where the mobile platform is the vision impaired person wearing it. The project will develop vision recognition, path planning, and sound tracking algorithms to be used in both robotic platforms.

Requirements: Required skill for participating students is C++ programming. Will help if the students have taken courses in machine learning and robotics but it is not necessary.

Deliverables: At the end of the summer the students will produce software and will demonstrate the software running on a prototype robotics platform.

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

5. RECONSTRUCTION OF BID/ASK QUEUES USING ORDER FLOW

The students will use Thomson Reuters level 2 data to reconstruct and visualize the order book for any asset present in Thomson Reuters database. The project will concentrate on the commodity markets due to their simplicity from a market microstructure perspective. Secondary, the program should be designed in a modular way so that modules could be used to quickly adapt the program to any order messaging flow system.

Requirements: This is a programming project. The students will need to be familiar with C++ programming and interfacing it with R or Matlab for visualization purposes. Alternatively, one may use straight C++ and design a GUI for it.

Deliverables: The project will deliver software which will be used further for other projects. Depending on the final product quality if decided to convert to open source this may be subject to a journal article.
This project is in collaboration with Dr. Gousgounis.

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

6. DEVELOPING A TEST BED FOR HIGH FREQUENCY TRADING STRATEGIES

In this project the students will create a system where various HFT strategies may be used. The project will use Thomson Reuters Tick data and will test various trading strategies. Some will involve our developed methods (reference: http://personal.stevens.edu/~ifloresc/Research/Publications/ProjectpricevolFinalwithDragos.pdf ) some will involve existing methods such as ziggurat method and other machine learning techniques.

Requirements: Programming in C++. Experience with machine learning techniques is a plus. Some code may use parallelization techniques and the GPU cluster which is part of the research resources available to FE students.

Deliverables: The project will deliver software. Depending on the complexity of the algorithms developed the students may be involved in our ongoing research and papers.
This project is in collaboration with Dr. Bozdog.

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

7. DESIGN OF AN AUTOMATIC TRADING SIMULATOR

The project will build a market simulator. The finished design will include all aspects of high frequency trading, from submitting a trade to coding an algorithm to react to the market conditions. Initially the project will concentrate on a specific market and will gradually build capabilities. Several trader types will be designed and their interaction studied.

Requirements: The code will be written in C++. Sockets and networking communication may need to be researched. Prior knowledge of GUI design is a plus.

Deliverables: The final software will be used in class as a teaching tool as well as in research projects studying the impact of HFT on the market. Again depending on the level and the quality of the final product the project may lead to publications. This project is going to help the lab develop its own trading simulator

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

8. VISUALIZATION OF IMPLIED VOLATILITY SURFACES 

The project will create tools to visualize implied volatility surfaces of instruments other than the straight equity asset class. For example, implied volatility of swaptions, caps, etc. in fixed equity markets and other instruments will be investigated.

Requirements: Familiarity with programming in R, Matlab or other high level programming is needed.

Deliverables: The software produced will be used to demonstrate the power our students to outside industry. Credit will be given to the students working on the project. 

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

9. VISUALIZATION OF ELECTRICITY SWAP CURVE

The project will create tools to visualize the swap curve of Electricity swaps using data from ICAP.

Requirements: Familiarity with programming in R, Matlab or other high level programming is needed.

Deliverables: The software produced will be used to demonstrate the power our students to outside industry. Credit will be given to the students working on the project.

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

10. VISUALIZATION OF NATURAL GAS SWAP CURVE

The project will create tools to visualize the swap curve of Electricity swaps using data from ICAP.

Requirements: Familiarity with programming in R, Matlab or other high level programming is needed.

Deliverables: The software produced will be used to demonstrate the power our students to outside industry. Credit will be given to the students working on the project.

Advisor: Dr. Ionut Florescu
ifloresc@stevens.edu
Ext: 5452

11. ANALYTICS OF XBRL-BASED FINANCIAL DISCLOSURE INFORMATION

The project is part of the proposed XBRL infrastructure system currently in development by the Financial Engineering department. The objective of the system is to apply various analytic techniques such as statistics and data mining (numerical/text mining) on publicly available financial disclosure information (e.g. General Electric's annual report). The system provides a platform for investors to utilize our analytic results for better informed decision making, and, most importantly, for academia community to conduct financial disclosure-related research. The project will focus on the use of R (a statistical software package) in generating meaningful analytic results and connecting with the main XBRL infrastructure system through an extension plugin. Through this project, you can learn and explore the different functions available in R and subsequently apply them to various sets of financial disclosure information of interest.

Requirements: Basic knowledge of R, All majors welcome for application, Strong interest in conducting research related to the financial market stability and regulation,Strong interest in deal with complex and big data set,Intermediate to advanced Math/Statistics knowledge required,Able to work independently and to communicate effectively.

Advisor: Steven Yang
syang@stevens.edu
Ext: 3394