VIP Program at Howard University (VIPatHOWARD)

Howard University

Washington, DC 20059

VIP Coordinator: Dr. Charles Kim (CKIM@HOWARD.EDU), Professor, Electrical Engineering and Computer Science

This program was sponsored by The Leona M. and Harry B. Helmsley Charitable Trust for 3 years from 2015 as part of VIP Consortium Project  to drive systemic reform of STEM education.  During and after the major sponsorship, additional financial support was generously made by Northrop Grumman Corp. and Lockheed-Martin

   

* How to Join?:  If you want to  join one of the teams below, contact Project Advisor (via email) or the VIP Coordinator (Dr. Charles Kim) via email  ckim@howard.edu

 

 Any question can be directed to the VIP coordinator at ckim@howard.edu.  Anyone, yeah anyone, can join.

 

Project Teams

Team Contract Form: (in pdf, docx, forms)

Project Team Advisor/Contact Project Description Sponsor
Optical Metasurfaces
(From Fall 2021)
Advisor: Dr. Eric Seabron (Electrical Engineering) email: eric.seabron@howard.edu

Metasurfaces and Resonators are physical structures that are patterned into crystals to create special quantum-like behavior when it interacts with light; think about how light reflects off a flat CD/DVD disc and creates a rainbow. In this research we study Metasurfaces and Resonators in transparent and reflective crystals to enable new effects which can be used for photonic circuits, waveguides, and sensors. This work doesn’t require prior knowledge in optics but requires a desire to learn new concepts. The research tasks will include:

o   Simulations using Software

o   Data analysis and Statistics

o   Collecting microscopy and optical spectroscopy data

o   Scientific Reading and Writing



Team Members
Capital One
(From Fall 2021)
Advisor: Dr. Imtiaz Ahmed (Electrical Engineering) Algorithmic and Visualization Capabilities for Machine Learning: The objective of the project is to evaluate various algorithmic and visualization tools and insights which would generate various types of visualization to support machine learning-driven analysis of large/complex data sets.  The project utilizes open source tools and publicly available data in the evaluation study.

Team Members
Amazon Freight (From Fall 2021) Advisor: Dr. Md Sami Hasnine (Civil and Environmental Engineering) This research aims to develop advanced machine learning and econometric models to tackle current days freight optimization problems. More specifically, this project focuses on the cold chain implementation in the Amazon Freight Inbound (AFI) network. Students from both Civil and Environmental Engineering and Computer Engineering are part of this research team. The project team will help Amazon to create a web-based service for cold chain shippers. The service allows shippers to send their freight pickup requests and then builds optimized execution plans for the Amazon Freight inbound process, including freight pickup, DC cross-dock, and delivery to the destination facilities. The optimization engine generates the most cost-efficient route solutions that meet the time, temperature, capacity, and operational constraints.


Team Members
Memory Forensics (From Fall 2020) Advisor: Dr. Hassan Salmani (Computer Eng)
 hassan.salmani@howard.edu
This project aims to complete a trade study against attack methods which have become increasingly sophisticated, for the tools that provide physical memory coverage against those attacks, by conducting extensive analysis which leads to determination of the best memory forensics tools that provide the best threat intelligence coverage used in identifying and investigating cyber-attacks.

Team Members
Secure Smart Traffic (from Fall 2019) Advisor: Dr. Hassan Salmani (Computer Eng)
 hassan.salmani@howard.edu
The goal of the project is to realize secure smart traffic which is characterized: Driving cars on the road; base stations on the side of the road which gives road data to the cars; cars adjust position and speed among the cars on the road; there are possibilities that the communication between cars and car-station may be hacked; secure smart traffic shields the communication.
Team Members
Terminator (since Fall 2015) Advisor: Dr. Charles Kim (Electrical Eng)  ckim@Howard.edu





Team Terminator’s new project focuses on developing a Chess playing robot that relies on camera inputs to identify a chess board and a mechanical arm to move the chess pieces and on machine learning principles for ideal victory paths for the robot. This project aims to cover various engineering fields and expose participants to long term research in addition to applied and collaborative engineering environments. While a robot that can play a game of chess on its own is the end goal, for this academic year, we will a robot which plays the game of Tic Tac Toe.  In subsequent years, we will gradually incorporate new features to achieve the end goal of building a robot which plays chess. The project will have mechanical, electrical, and programming aspects.


Team Members


Smart Building (From Fall 2020) Advisor: Dr. Fadel Lashhab (fadel.lashhab@howard.edu)

Thermal Comfort Prediction in Smart Buildings via Machine Learning:

Heating, Ventilation, and Air Conditioning (HVAC) is very energy-consuming, accounting for 40% of total building energy consumption in USA. Building thermal control is important for providing high quality working and living environments, because occupants can only feel comfortable when the temperature and humidity of the indoor thermal condition are within the thermal comfort zone.  The key to realize this vision is to predict the accurate thermal comfort model. We will propose a machine learning based approach to learn an individual’s thermal comfort model.  We will use and investigate several algorithms for thermal comfort predictions. Algorithms like artificial neural network (ANN), support vector machine (SVM), Bayesian algorithms, regression, and random forest (RF) classifier. We will use the ASHRAE RP-884 database which is a quality-controlled database collected from field thermal comfort studies in 160 buildings around the world.

Team members
Social Sphere Machine (from Fall 2019) Advisor: Dr. Charles Kim (ckim@howard.edu) (Electrical Engineering)


The goal of this project is to develop a data analytic and machine learning (reasoning) algorithm to analyze social media data to predict social events such as opioid crisis, hate crime, and social unrest.   Related subjects such as fake information/news detection and radicalization warning are of interests of the project.  Information entropy based classification, clustering, and decision-making is applied to develop the algorithm.  Python-based coding and implementation is planned along with data analysis and visualization with R.

Team Members

The winner of VIP consortium's Northeast regional video presentation competition in Spring 2020.
Link to the pechakucha style presentation
SLAM (from Fall 2017) Advisor: Dr. Michaela E. Amoo (Computer Eng)

Contact: Dr. Michaela Amoo at mamoo@howard.edu

SlamERS: Embedded System Design

Goals: Students will integrate all system design components from previous year into a COTs based autonomous wheeled platform using sensor arrays (IR Rangers, Lidars etc), integrating circuits, sensor arrays, and motor controls, from previous year into a complete PIC-based system. Final product be stable and robust under adverse conditions.

Link to Pechakucha style presentation

Team Members
(20-21)
Deliveroid- A Delivery Robot  (from Fall 2017) Advisor: Dr. Charles Kim (ckim@howard.edu Electrical Eng)


Graduate Assistant:
The long term goal of the project is to build a delivery robot which performs errands between any two locations even in different floors of a building.  A short term objective is to build a 1st-gen robot which delivers to a location in the same floor.  Microcomputer coding, sensing, RFID or Wi-Fi and remote access, and proximity detection would be integrated for the project.  More and further more
 

Team Members (21-22)
Quantum AI (From Fall 2020) Advisors: Dr. Michaela Amoo (CpE) (mamoo@howard.edu)  and Dr. Thomas Searles (Physics) (thomas.searles@howard.edu) Quantum Applications:  This project explores quantum computing applications.  One of them includes development of quantum games for experimental test beds for hybrid classical-quantum machine learning algorithms via the IBM-HBCU Quantum Coalition.

Team Members
Solar Powered Vehicle-   (From Fall 2021) Advisor: Dr. Ahmed Rubaai (EE) (arubaai@howard.edu)

Solar arrays use sunlight as a source of energy to generate DC electricity. Due to the relatively low efficiency of modern day solar cells (~20% maximum) solar powered electronics must be energy efficient for practical use. In the field of embedded systems, some modern day microcontrollers have peripherals and functionalities designed to minimize the amount of energy that is needed to interface with and control systems, making them perfect for solar powered projects. The goal of this project is to design and build a solar powered vehicle that can efficiently maximize solar array energy to charge batteries, as well as minimizing the energy lost through microcontroller control power consumption. 

 


Team Members
AI Platform (From Spring 2021) Advisor: Dr. Saurav Aryal (CS)(saurav.aryal@howard.edu) Businesses need help sifting through mountains of documents (unstructured data), finding insights and using these to take action. Manual review is often not practical or viable.  Organizations are using NLP models to review large volumes and data and patterns and anomalies. These findings can then lead to greater insights and actions. However, many current NLP models are trained on generalized data sets and are not domain specific, making them less effective. This project will focus on proposing a method to find a way to adapt generic language models for a domain specific use case such as: healthcare, legal, financial data. This project is carried out in conjunction with Excella as an industry sponsor.

Team Members
       

 

VIP Teams of 2019-2020, 2018-2019, 2017-2018, 2016-2017, 2015-2016.

VIP at Howard Main Webpage


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