This document provides information about computer science opportunities at Hofstra University from 2014-2015. It summarizes that over one million computer-related jobs are expected to be created by 2014, with recent Hofstra graduates finding jobs in fields such as banking, consulting, and game development. The computer science department at Hofstra offers undergraduate and graduate degrees, and has new facilities like the Big Data Lab funded by a $1 million grant to prepare students for data-related careers. Courses in the Big Data Lab utilize its resources for topics like networking, databases, and distributed computing.

1. 2014-2015

2. Job Opportunities
 Over one million computer-related jobs are expected
to be created by 2014, (U.S Department of Labor -
www.dol.gov).
 Bureau of Labor statistics indicates faster than average
job increases for computer jobs in the next decade
(http://www.bls.gov/oco).
 Many exciting careers from web and mobile to
networking and security, and game developers, big
data.

3. Job Opportunities
 Recent graduates have found jobs in:
 Banking and financial institutions (Citibank, S&P 500, Bank of
America)
 ConEdison, OpenLink, Computer Associates
 Google, Geico, Hofstra Computer Center
 Game development, mobile apps companies
 Consulting firms, small companies and start-ups.
 Started their own companies!
 Typical jobs:
 IT
 Web and mobile device developers.
 Software engineers.
 Network and database administrators
 Consultants.

4. Graduate studies
 Undergraduate students interested in graduate studies
have been accepted in MS or PhD programs at universities:
 Cornell University,
 Rensselaer University,
 Columbia University,
 University of California at Berkeley,
 Princeton University,
 Stevens Institute of Technology,
 University of Memphis,
 Stony Brook University
 Computer Science Department at Hofstra.

5. Alumni Stories
 Mike Seiman and Carlton Hickman started CPX
Interactive, a company in the on-line advertising
industry; they are now leading an international, multi-
million dollar company.
 Established an Endowed Entrepreneurship Scholarship
for Computer Science and Computer Engineering
 Tom Sanzone, a current board of trustees member at
Hofstra, has been a successful CIO for several multi-
national companies and banks and has lead projects
overseeing thousands of people.

6. School of Engineering and Applied
Science
 Started in Fall 2012.
 Major undertaking for the University, with new and
updated infrastructure facilities, new programs
 For the Computer Science Department majors it means
more resources:
 New labs, faculty
 Co-op program

7. Programs and degrees
Undergraduate:
 BS/BA in Computer Science
 BS in Computer Engineering
 5 years dual-degree BS/MS in Computer Science
 BS in Math and Computer Science
Graduate
 MS on-line and on-campus

8. Programs and degrees
Undergraduate
 Concentrations/options in:
 Entrepreneurship
 Networking and cybersecurity (new Fall 2015)
 Gaming and Graphics (new Fall 2015)
 Web and mobile engineering (new Fall 2015)
 Interdisciplinary minors:
 Cognitive Science, Computer Application and Digital Media
Design
All programs approved by New York State and
accredited by Middle States Association.

9. Faculty
7 full-time faculty, all holding PhDs with expertise in:
 Security and privacy.
 Software engineering.
 Semantic Web.
 Data mining.
 Computer vision.
 Cognitive neuroscience and artificial intelligence.
 Programming languages.
 Distributed processing.
 Computability Theory.

10. Faculty
 Faculty have been awarded research grants from
federal institutions such as National Science
Foundation, or private companies, such as Google.
 NSF research grants.
 NSF educational grant: entrepreneurship in computing.
 Undergraduates do one-on-one research with our
faculty.
 Some undergraduate research positions are paid.

11. Adjunct industry experts
 Networking and security.
 Embedded systems.
 Game development.
 Entrepreneurship.
 Bioinformatics.
 Databases.

12. Facilities
 6 student labs updated every 2-3 years.
 Linux lab for introductory and required courses.
 Systems lab for advanced electives.
 Computer architecture and Embedded Systems lab .
 Gaming and Graphics Lab
 Gaming, graphics classes
 Research and Innovation Lab
 For students working on research or entrepreneurship projects.

13. New Lab on Big Data
 The Big Data Lab was funded in 2014 by a NY State grant of $1
million.
 The goal of the new Big Data Lab is to educate students in all
aspects of large and distributed information systems:
 System development, testing, data security and privacy, data
integration, networking, cyber-security and application
development.
 And, thus to prepare them for highly-skilled jobs in emerging
and fast growing IT industries such as data analytics and data
integration, cloud computing, health-care informatics, and
finance.

14. Equipment in the Big Data Lab
The server room has a VMWARE ESXi cluster build out of 21 individual
servers. The cluster has an overall RAM of 3 TB, 420 CPU cores or 840
threads and a total hard-drive capacity of 1,000 TB.
The server room has a cooling capacity of 12 Tons (~ 12 large home AC),
a power capacity of 60 KW (~ 5 homes with 100Amps), 1/2 km of
networking cable.
Each of the 21 servers in the VMWARE ESXi Cluster consists of:
 IBM X3650 M4 Big Data model
 2 x 8 cores Xeon CPU @2.2 GHz
 128GB RAM
 9 x 4TB HDD (RAID 6)
 2 x 10GB, and 4 X 1 GB Network Cards

15. Unique Features
 All required classes and labs are taught by full-time
faculty with at most 20-25 students per class.
 Expert industry adjuncts teach some electives.
 New classes introduced regularly:
 Gaming, web and mobile application development,
network security, parallel processing.
 Students can work one-on-one on their area of interest
with a faculty in independent study/research projects.
 Internships for credit:
 local companies and Computer center at Hofstra.

16. Unique Features
 Innovative entrepreneurship programs: Concentration and
Option in Leadership and Innovation in Computinh
 New concentrations in:
 Networking and security, Web and mobile engineering, and
Gaming and graphics.
 Concentrations coming up: Data analytics, Artificial
intelligence, Health-care informatics.
 Interdisciplinary minors in:
 Computer Applications and Digital Media Design
 Cognitive Science.

17. New co-op program in Spring 2015
 Available for junior students with GPA requirements.
 6 months full-time employment at a company in the
computer industry.
 Great opportunity to apply your knowledge and learn new
skills in a real working environment.
 Very valuable experience for future job search.

18. Entrepreneurship Programs
 Innovative programs in Entrepreneurship funded by
NSF.
 Concentration and Option in Leadership and
Innovation in Computing.
 Students learn about the process of coming up with an
innovative idea, market research and marketing, basics
of finance and accounting, an internship in
entrepreneurship, and a year-long senior design project.
 Business plan competition every year.
 Judge panel from local entrepreneurs.

19. New Business Plan Competition
 A $100K awards CPX business plan competition for
CSC/Engineering and STEM students at Hofstra.
 Students need to propose an idea and build a
prototype.
 First two years first place awards were won by CS
students.

20. Entrepreneurial projects
 Queue+ = integration of multiple social network sites.
 Won $50k in the CPXi entrepreneurship competition 2014
 A 3D printer.
 Won $5ok in the CPXi entrepreneurship competition 2013
 An on-line Electronic Medical Records software.
 Won 25K in the CPXi entrepreneurship competition 2014
 A data integration and analytics site.

21. Internships
 Earn up to 6 free electives credits in internships.
 The department is actively looking for internships.
 We have an agreement with the Computer Center at
Hofstra for internships in web or mobile development,
networking and system administrations.
 CS internship/job web-site
 Potential employers submit job descriptions:
IT, web development, networking, or mobile app
development
 Recent internships with: CPX Interactive, Sandata,
PriMedia, GRQ Innovations, S&P 500.

22. Typical Class Projects
 Freshman Projects:
 Tango (Lego Robot Printer)
 Desert Duel (Alice Animation)
 Missile Launching (XNA Game Programming)
 Sophomore Projects
 Maze searching algorithm.
 Building and programming a robot to play soccer.
 Application to store information from music files.
 Junior Projects
 Cracking Slot Machine (OS, buffer overflow)
 Bomberman Game (Software Engineering)
 Senior Projects
 API Hook (key logger, network security).

23. Senior design projects
 Recent projects in:
 Malware analysis.
 Estimation of rain from satellite data using neural
networks
 Video game.
 Mobile app to help identify lost pets
 Mobile app that uses semantic ontologies to locate
places of interest.

24. Courses in the Big Data Lab
 Courses using the lab:
 Parallel and distributed computing
 Software engineering,
 Operating systems
 Semantic web
 Networking, Network security
 Secure Systems, Systems Programming

25. CSC 150: Semantic Web
Spring 2015
The Semantic Web is an evolution of the current WWW where data
is represented as meaningful knowledge. The crux of the Semantic
Web is in semantic representation and reasoning of data using
description logic ontologies, which is particularly useful for
classifying large amounts of unstructured data. Ontology reasoning
of big data requires ample storage and processing power.
The Big Data Lab contains 100TB cloud storage and 420TB of storage
in data servers that students will be using to build semantic web
applications.
Faculty: Dr. Knarig Arabshian

26. CSC 175: Computer Networking
Spring 2015
 A technical introduction to data communication. Topics include
the OSI Reference Model, layer services, protocols, LANs, packet
switching and X.25, ISDN, File transfer, virtual terminals, system
management and distributed processing.
 The Big Data Lab hosts a dedicated server and switch for teaching
students basic networking concepts, which are fundamental for big
data processing. Each student workstation contains three network
interface cards, which allow a high degree of flexibility in network
configuration. Students will engage in networking experiments
such as subnet mapping and packet tracing.
Faculty: Dr. Chuck Liang

27. CSC 112: Operating Systems
Spring 2015
 A study of the internal design of operating systems. Topics include memory management,
multiprogramming, virtual memory, paging and segmentation. Job and process scheduling;
multiprocessor systems; device and file management; thrashing, cache memory.
 Individual Project: Using a Linux Ubuntu image, students will complete a variety of OS
kernel modules, including kernel thread synchronization primitives, virtual memory paging
system, and around 10 system calls related to process management. The mini-projects
involves about 1000 to 1500 lines of C++ coding effort.
 Term Project: Using 10 Oracle Linux Images on the cloud infrastructure of the big data lab,
students will fully configure an enterprise level information system for a start-up company.
They will provide a robust and reliable network file system (NFS) and a yellow page system
where all employees can log into any of the server using the same credential. The start-up
company uses an open source web application for managing its inventory and a e-commerce
site. Students will optimize the performance of this web-store (e.g., by integrating a load
balancer and fine tuning the OS performance). All important commercial data and user
information have to be properly backed up (you can use one or two images for remote daily
backup). Student from other team will perform "demolishing" operations on your first 8
severs. You have to be able to recover your entire system within 10 minutes.
Faculty: Dr. Xiang Fu

28. CSC 190: Software Engineering
Spring 2015
 Students study the nature of the program development task when many people,
modules and versions are involved in designing, developing and maintaining a
large program or system. Issues addressed include program design, specification,
version control, cost estimation and management. Students work in small teams
on the cooperative examination and modification of existing systems. The course
has an oral communication component including group and individual
presentations.
 Mini-assignment: your team will have access to a Windows 2008 R2 Server. Using
this server, you and your colleagues will design, implement, test, deliver, and
publish a collection of web services for an educational stock exchange platform
named "Hofstra Stock Exchange" (HSE). HSE has to provide basic user
management and stock trading functions. It should provide stock history query
functions for all NYSE stocks from 1/1/1980. You have to optimize the performance
of your web services and provide a complete functional and performance testing
report at the end of the semester.
Faculty: Dr. Xiang Fu

29. CSC 125: Concurrent and Distributed
Computing
Fall 2015
 Concurrent and Distributed Computing is essential for
processing a large amount of data. The Big Data Lab contains
a 64-core AMD station, in effect a miniature super
computer. In addition, other computational resources of the
lab can be configured easily using a software called VMware
to support distributed computing platforms such as Hadoop
and MPI. Students will learn how to program using these
tools for applications including data encryption and DNA
analysis.
Faculty: Dr. Chuck Liang

30. Research Project: QuOntoAd, An Ontology-based
System for User Privacy Preservation and Accurate Ad
Targeting
 QuOntoAd is a collaborative research project between Hofstra's Computer Science and
Marketing and International Business Departments as well as Columbia University's
Computer Science Department. In this project, we are looking to create a system that
produces ontology models that quantify and represent the intersection between on-line
user behavior and targeted advertising in order to understand consumer perception of
privacy intrusion and accuracy in ad targeting. QuOntoAd creates a semi-supervised user
behavioral ontology model by integrating information from user studies as well as data
mining techniques.
 Research students will be working with a very large dataset of user-behavioral data that
will be provided to us from CPXi, a digital media holding company. We will be processing
this data with data mining algorithms and then constructing ontologies to model user
behavior. This research work requires intensive computation and hundreds of terabytes
of data storage and will be conducted in the Big Data Lab.
Faculty: Dr. Knarig Arabshian

31. Research Project funded by NSF
WISE Guys and Gals - Boys & Girls as WISEngineering STEM
Learners
WISEngineering is a web-based educational system that supports NSF-AISL
1422436 "WISE Guys and Gals - Boys & Girls as WISEngineering STEM
Learners ". The system integrates various advanced features such as user
behavior tracking and automated grading that supports an engineering
curriculum in an informal learning environment. A highly reliable data
storage system (based on HBase) is being developed to store the huge amount
of user behavior data generated by the system every day. Another automated
grading module, based on Hadoop and EDX EASE, is used to train, calibrate
an automatic grading engine that assesses student performance. The project
uses an NAS server of 10TB and runs on a cluster of 6 nodes.
Faculty: Dr. Xiang Fu, Dr. David Burghardt
Student: Tyler Buffman

32. Master Capstone Project Fall 2014
Enhancing Malware Trace Mining With Cloud Caching
Malware is progressively increasing in sophistication and in the most recent
cases, is capable of detecting its run-time environment. This poses a
significant issue for traditional analysis methods which use emulators and
virtual systems to execute the malware and observe its behavior. A new
analysis tool EVMine analyzes this new type of malware by caching large data
files on the hard disk which contain slices of traces of malware. To improve
the overall performance of the tool, core functionality of the caching
mechanism was altered to provide capabilities similar to Google BigTable with
the use of Apache HBase.
Student: John Cammarano
Faculty advisor: Dr. Xiang Fu

33. Senior Project Spring 2015
A Hadoop Based Trading Platform and Financial
Optimization System
We propose to develop an educational stock trading platform and a research
tool for optimizing the parameters of financial models. The system leverages
the distributed HBASE database for storing the vast amount of historical
trading data. A research engine is based on Hadoop, which accepts upload of
bytecode of financial models implemented using Java. By performing
reflection analysis of a financial model program, the research engine
automatically extracts its parameters and runs hundreds of parallel threads
against the historical data to find the optimized parameters.
Student: Stephen Spano
Faculty advisor: Dr. Xiang Fu