Assistant Professor, Tenure-Track Department of Computer Science, University of San Francisco

posted Aug 31, 2017, 8:38 AM by Rosa Maria Garay   [ updated Aug 31, 2017, 8:41 AM ]

The Department of Computer Science at the University of San Francisco is accepting applications for two tenure-track Assistant Professor positions starting in August 2018.  This search seeks candidates from the field of Computer Science or a closely-related field.

The Department of Computer Science is a diverse and growing community with 10 full-time faculty members, over 200 undergraduate CS majors, and over 70 masters students. While we are growing, the CS department maintains small class sizes with 30 or fewer students, project-based learning, and a high degree of student-teacher interaction.

The department is highly collaborative both within and outside the department. In addition to an undergraduate CS major and a masters program in CS, the department also supports a new interdisciplinary undergraduate major in Data Science as well as a masters program in Analytics. Several faculty members are NSF funded and collaborate with industry in Silicon Valley and the San Francisco Bay Area. 

The University of San Francisco is located in the heart of one of the world’s most innovative and diverse cities, and is home to a vibrant academic community of students and faculty who achieve excellence in their fields. Its diverse student body enjoys direct access to faculty, small classes and outstanding opportunities in the city itself. USF is San Francisco’s first university, and its Jesuit mission helps ignite a student’s passion for social justice and a desire to “Change the World From Here.” For more information, visit USF has been recognized as a top 20 entrepreneurial research university (Forbes 2015).

Job Responsibilities:  The successful candidates will be expected to teach both undergraduate and graduate courses, maintain an active research program that involves students, and perform service duties to the CS department and university.  The standard teaching load for this position at USF is two 4-unit courses per semester with an additional third course every fourth semester (2-2-2-3 over two years). 


Minimum Qualifications:  Applicants must have a Ph.D. in Computer Science or a closely-related field  completed prior to August 2018.  Strong applicants from all CS sub-disciplines will be considered. Applicants must demonstrate both exceptional teaching ability  and a strong potential for independent and collaborative research.   In addition, an understanding of and commitment to support the mission of the University of San Francisco are required.

To apply, please submit a CV, teaching statement, diversity statement, research statement, cover letter, and three letters of reference to To receive full consideration application must be complete and submitted by January 2, 2018. Please send questions regarding this position to

The University of San Francisco is an Equal Opportunity and Affirmative Action Employer.  The university does not discriminate in employment, educational services, or academic programs on the basis of an individual’s race, color, religion, religious creed, ancestry, national origin, age (except minors), sex, gender identity, sexual orientation, marital status, medical condition (cancer-related and genetic-related), disability, or other bases prohibited by law, and will provide reasonable accommodations to individuals with disabilities upon request.  We particularly encourage minority and women applicants for all positions.

USF CS Night 2016: Student Projects

posted Dec 8, 2016, 10:34 AM by Rosa Maria Garay   [ updated Dec 13, 2016, 12:05 PM ]

Following are some of the student projects presented at USF CS Night 2016. Projects were presented from
the Masters and Senior Project courses, the Bioinformatics course, and from some faculty-sponsored projects

Using Animation to Alleviate Overdraw in Multi-class Scatterplot Matrices

Presenter:                 Helen Chen (

Faculty Advisors:      Profs.Sophie Engle and Alark Joshi

Scatterplots are a widely-used technique for visualizing multivariate datasets. Even though scatterplots play an important role in data visualization,
they have known issues with overdraw. Overdraw occurs when points or glyphs are drawn on top of each other and obscure the underlying data.
Overdraw affects the ability of viewers to correctly understand the data distribution and discern relationships among subgroups of the data.
There are a variety of techniques for alleviating overdraw, none of which involve animation. Our research aims to use animation to visualize
multidimensional data for multi class scatterplot matrices and compare its efficacy in alleviating overdraw against that of other techniques.   

Student Record Verification App - A Decentralized Application

Presenters:                Mayank Thirani 
                                     Ryan Zhu
                                     Jakob Tarnow

Sponsor:                     Jim Huang

Faculty Advisors:     CS 690 Master's Project, Prof. Olga Karpenko

The Student Record Verification App will utilize the characteristics of Blockchain to solve the trust problem between recruiters from human resource
departments around the world needing to verify the applicants' claim of authenticity of their education degree without relying on intermediary third party
making that verification. Each transaction in the Blockchain is verified by consensus of a majority of the participants in the network. The Blockchain contains
all verifiable student records and past transactions. Allowing a recruiter to validate that a student’s educational background matches that of it’s respective
registrar via Blockchain, removes the need for a central entity and leads to faster attestation of student records.

Ten-X Hackday Tool

Presenters:               Jeremiad Raymond
                                    Teng Hu
                                    Yi Xiao

Sponsor:                   Jon Rahoi
Faculty Advisor:        CS490 Senior Project, Prof. Jeffrey Johnson

Ten-X Hackday Tool is an online web application designed as a platform to our sponsor company (Ten-X) for an annual programming competition
called “Hackday”. This platform will be used to collect, store, and process data entered by participants and graders. The purpose of this project is to
provide a better platform for Hackday organizers to control the flow of Hackday by handling the most repetitive tasks.

Presenter:              Dominic Mortlock
Sponsor:                The client would be students interested in learning more about unix and scripting concepts. Also, the game aims to be a fun
                                 challenge that people can practice both their unix knowledge and their problem solving skills.

Faculty Advisor:    Prof. David Wolber

Sudokil is a hacking/scripting themed puzzle game about using Unix-like commands on a terminal to control computers, robots, and various other devices.
Progress through levels and get access to different puzzle elements while collecting more scripts, permissions and tools.
Customer Ticket Classification Engine - Applying Machine Learning Algorithms to SnapLogic Metadata

Presenters:              Min Chen
                                   Shiyi Tan

Sponsor:                  Prof. Gregory Benson

Faculty Advisor:     CS690 Master's Project, Prof. Karpenko

SnapLogic customer service team needs to prioritize customer tickets and measure customer satisfaction, which was previously done manually and
was very time consuming. To automate this process, we built two engines, one for prioritizing tickets and one for the sentiment analysis of customer
comments. We first analyzed the ticket data and fit the two models, then used the models to predict the ticket priority and the sentiment of the comment
(“neutral” vs “negative”). If the ticket is labeled as “high priority” or contains a negative comment, our system sends an alert to the customer support team.
That allows the team to handle interactions with customers more wisely and saves their time.

Snap Recommendation Engine

Presenter:               Thanawut Ananpiriyakul

Sponsor:                 Prof. Gregory Benson

Faculty Advisor:     CS690 Master's Project, Prof. Karpenko

SnapLogic has been providing data integration services for years. A snap is a pre-built component that performs an operation on data. A pipeline is a
graph (DAG) of snaps which executes a specific task. In order to successfully build a pipeline, the user needs to select the right snap and connect it correctly
to the previous snap. For this project, we built the engine that recommends the most likely next snaps to users. We achieved 88% hit rate in the final prototype
implemented in Python. It means that 88% of time "deciding on the type of snap + searching for it among 100 types of snaps + dragging and dropping it to
canvas" will be reduced to "1 click.”

My Smart Financial Advisor - A Mobile Application for Mutual Fund Investment Management

Presenters:                Richard Wang
                                     Chen-Ning Chi
                                     Kaynat Quayyum

Sponsor:                    Stephen Y. Pak, The Core Group

Faculty Advisor:         CS690 Master's Project, Prof. Olga Karpenko

Mutual fund investment currently makes up a vast proportion of the retirement assets for Americans. At the same time, as mobile devices attain increasing
capabilities and popularity, more people switch from PC to mobile devices such as tablet computers and smartphones. We provide a platform to buy and sell
mutual fund shares on both iOS and Android devices. This enables users to manage mutual fund investment anywhere and anytime. Our application is
implemented in C# using Xamarin that allows us to build iOS and Android apps from a single shared codebase. Our app provides a good user experience
with high level of security.

An Exploration of Single Nucleotide Polymorphisms on Type 2 Diabetes Outcome

Presenters:                Michael Totagrande
                                     Irina Popova

Sponsor:                    Sean Kimbro, North Carolina Central University and La Creis Kidd from University of Louisville

Faculty Advisor:         CS640 Bioinformatics, Professor Patricia Francis-Lyon

Type 2 Diabetes (T2D) affects millions and is characterized by the inability to produce enough insulin, resulting in improper glucose regulation. With
numerous direct risk factors, including increased body mass index (BMI), race, high blood pressure, and the presence or absence of certain single
nucleotide polymorphisms (SNPs), T2D is a complicated disease. Herein, we explore over 600,000 SNP frequencies for more than 2000 individuals
in order to determine their impact on T2D outcome.
Using Face Tracking for Computationally-Efficient Visualization of Large Vector Data

Presenter:                Thanawut Ananpiriyakul

Faculty Advisor:       Prof. Alark Joshi

Visualizing large vector data is computationally expensive. Given that human beings can only visualize a certain region of a screen at a time, we have developed
a novel face tracking-based technique for visualization of large vector data. This focus+context visualization of vector fields reduces visual clutter and helps the
user visualize features of interest. We chose to use streamline and glyph-based methods to represent the vector data. Users can interact with the data in real time,
choosing regions of interest through a mouse, a touch interface, or their face. The presented visualization technique results in frame rate that is almost 5 times
higher than the full detail visualization of vector data.

Exploring Leap Motion for Intuitive Interaction of Scientific Data

Presenter:                Shiyi Tan

Faculty Advisor:     Directed Study, Prof. Alark Joshi

We explore use of the Leap Motion with intuitive interaction of medical data, trying to help practitioners interact with large, high-resolution datasets.
We use VTK for the visualization pipeline that includes data processing, surface extraction/volume rendering, and basic user interaction. We facilitate
freeform interaction without the use of a mouse and keyboard using the Leap Motion. With the Leap Motion controller, users can explore the 3D data
and perform basic interaction such as rotation, translation, and zooming in. 

Computational Enzymology

Presenters:                Stephanie Martin
                                     Meriam Vejiga
                                     Adrian Ramirez

Sponsor:                    Distributed Bio is a an antibody discovery, engineering, informatics and services company focused on
                                     producing next generation antibody libraries and revolutionary vaccines.

Faculty Advisor:         CS640 Bioinformatics, Professor Patricia Francis-Lyon

Enzymes are the original organic chemists (OCC), capable of catalyzing a wide variety of reactions that have great therapeutic potential. Many enzymes
have been cataloged and annotated using the Gene Ontology, a gene annotator's reference, and categorized by the Enzyme Commission, a database that
classifies enzymes based on the nature of their enzymatic activity. We took advantage of these two databases to mine for homology groups with similar
enzymatic activity, but different substrates. We characterized these enzyme groups by sequence variability and enzymatic variability. This work provides a
foundation for the creation of a new class of enzyme replacement therapy and for the creation of a new generalized synthesis technology.

Mechanistic Indicators of Childhood Asthma

Presenter:                Stephanie Styx

Sponsor:                   Dr. ClarLynda Williams-DeVane from North Carolina Central University sponsored the mechanistic indicators of childhood asthma project.
                                    Her objective for this project is to identify key environmental exposure contributors to asthma subtypes of varying severity.

Faculty Advisor:        CS640 Bioinformatics, Professor Patricia Francis-Lyon

Understanding the relationship between environmental factors and their affect on asthmatic children. Through principal component analysis, we looked at the
correlation of how much variance there is when asthmatic children are exposed to similar or different environmental factors. The cohort of patients analyzed in
this project were asthmatic African American children from Detroit, Michigan.

Computational Enzymology

Presenters:                Stephanie Martin
                                     Meriam Vejiga
                                     Adrian Ramirez

Sponsor:                   Dr. Jacob Glanville, former Principal Scientist at Pfizer, PhD in Computational and Systems Immunology at Stanford University School of Medicine
                                    and current Chief Science Officer of Distributed Bio.

Faculty Advisor:         CS640 Bioinformatics, Professor Patricia Francis-Lyon

Knowing the three dimensional structure of proteins is essential to understanding how the protein functions. Currently protein structures are determined
through x-ray crystallography, which can be difficult and laborious for some projects. Dr. Jake Glanville, CSO of Distributed Bio, created a coding package to
predict the structure of B cell and T cell receptors. This code draws on probabilistic alignment and hidden markov modeling and uses Hmmr3.0 and the
NCBI BLAST toolkit to identify potential templates for homology modeling then generates a model using UCSF’s Modeller. We tested the potential of the script to accurately produce models by using an input, self-models=0, to remove any template with more than 95% identity to the query sequence,
ensuring the program didn’t fetch the known crystal structure of the query for homology modeling. After generating hundreds of models, we used another script,, to calculate the root mean squared deviation (RMSD) of the generated model superimposed on the published structure to validate whether
this package has the potential to accurately predict the variable regions of antibodies.
Ozone exposure causes differential expression of genes involved in cell growth and DNA binding

Presenter:                 Chelsea Yee,
                                    Amrita Rishi

Sponsor:                    Dr. Mehrdad Arjomandi

Faculty Advisor:        CS640 Bioinformatics, Professor Patricia Francis-Lyon

Ozone - a gas with high oxidation potential is a major component of air pollution and has been found to damage the respiratory tissues in humans.
To our knowledge, no one has yet published the results of an exacerbation study utilizing ozone as a model for the impact of air pollutants. An ongoing
study by Dr. Mehrdad Arjomandi and associates at UCSF aims to establish the impact of ozone-induced injury and inflammation in asthma and other
lung diseases. Currently, this study aims to determine the differentially expressed genes (DEGs) in subjects, both with and without asthma, that were
exposed to medium (100ppm) and ambient (200ppm) levels of ozone. Gene expression levels for 18 subjects were determined by Affymetrix microarray
in an ozone-exacerbation study performed by Dr. Arjomandi’s team at UCSF. In partnership with Dr. Arjomandi and Prof. Francis-Lyon(USF), our team
performed statistical analysis of the Affymetrix microarray data in R using the limma package to identify DEGs in airway epithelial tissues in response to
ozone exposure. A total of 68 DEGs was determined from the Affymetrix microarray data for all 18 patients. Among the 68 DEGs, 4 were more frequently
differentially expressed (adjusted p-value < 0.1): MAPRE3, HKR1, MOB3B and ZFR. Genes MAPRE3 and HKR1 were up-regulated whereas MOB3B and
ZFR were down-regulated. Further studies providing new knowledge of the function and downstream effects of these genes can lead to the possibility of
new gene therapy and pharmacological targets.

Muse Mobile App

Presenter:                MD Naseem Ashraf

Faculty Advisor:       CS640 Bioinformatics, Professor Patricia Francis-Lyon

An Android app that leverages Muse headbands to record and transmit eegs from mobile devices easily and quickly.

AI for Princes of California

Presenters:                Kyle Baker
                                     Austin Bushree
                                    Cole Howard

Sponsors:                Jon Rahoi and Justin Sher. Noo Games

Faculty Advisor:        CS490 Senior Project, Prof. Jeffrey Johnson

Princes of California is a strategic board game that is similar to a hybrid of Monopoly and Poker. A single turn consists of playing a tile on the board and
buying up to three shares of any companies that have been built from the tiles on the board. The current built-in opponent makes random moves and is
easily defeated by human players. Our project seeks to use multiple techniques to build a competitive AI opponent for this game.
We will be implementing a heuristic algorithm based on the strategies we have developed while playing the game. We will also be fine-tuning a neural
network using TensorFlow, an open source machine learning package. The network will be trained by playing against random bots. The gameplay tactics
change based on the number of players, so our AI will be trained separately for 2, 3, 4, 5, and 6 player games. The ultimate goal of our project is to build an
AI that strategically places tiles and buys shares of companies to create an entertaining opponent for online players.
Fitness App for Vue Smart Glasses

Presenters:                Scott Zhu
                                     Ji Lu
                                     Shengcai Cheng

Sponsor:                    Jason Gui, Vigo Technologies

Faculty Advisor:        CS690 Master's Project, Prof. Olga Karpenko

Vue is a wearable device, a pair of “smart” glasses designed for everyday use. Our team developed the companion app for Vue on iOS and Android.
The app provides fitness features such as step tracking, calorie counting and inactivity alert that help people lead healthier and more active lives. It
also provides some additional features such as finding the device using the app, and delivering notifications.

Visualization of Hierarchical Time-Series Data Using the Sunburst Technique

Presenters:                Joey Estella,
                                      Marissa Masangcay,
                                      Lyndon Ong Yiu,
                                      Mohammad Bazarbay

Sponsors:                  Profs. Sophie Engle and Alark Joshi

Advisor:                      CS490 Senior Project, Prof. Jeffrey Johnson

The Visualizing Time Series Data project addresses the need to visualize new ways to aggregate large time series data. Often times, data becomes
too large when in its raw form. Then the problem becomes how to aggregate that data, i.e., what kind of metrics (mean, median etc.) and levels (days,
hours, etc.) need to be used to summarize and see patterns and trends from this data.
Our visualization tool attempts to address this problem. Our tool features an interactive dashboard where users are able to view organized data in a
sunburst visualization that displays the data in a meaningful way. Included in the interactive dashboard is an interactive sunburst visualization with a
complementary line chart that corresponds to data in the sunburst. This tool gives added context to otherwise ‘normal’ looking data in order for the user
to gain meaningful and significant conclusions about the data at hand. This tool also features a non-interactive dashboard where various static sunburst
visualizations are displayed in a grid for easy comparisons. These static visualizations feature multiple metrics (mean, median, etc.) across different levels
(days, hours, etc.).

Real Estate Recommendation Engine

Presenters:                Rob Reeves,
                                     Simon Kwong,
                                     Zhe Xu

Sponsor:                    Jon Rahoi, Ten-X

Faculty Advisor:        CS690 Master's Project, Prof. Olga Karpenko

Buying or selling a property is not something most of us do every day. But when the time comes, searching for a new home or office is exhausting. It's stressful,
agitating, and searchers often find themselves settling for less. We developed a recommendation engine for a Ten-X real estate marketplace, that will assist in
alleviating some of that stress. The engine recommends available properties based on past user activity. It uses a graph-based recommendation algorithm that
combines collaborative and content-based filtering.The goal is to maximize the likelihood a user will interact with the recommended properties embedded in the ad.

CyberSecurity at Gap Inc.

posted Nov 9, 2016, 10:34 AM by Rosa Maria Garay   [ updated Nov 9, 2016, 10:38 AM ]

Date: Thu., November 10th, 2016
Time: 11:45am-12:45pm
Location: Harney Science Center (Room 235)

We are delighted to announce a special Cybersecurity event tomorrow sponsored by the local ACM chapter. Richard Noguera (CISO) from Gap Inc. will give an 
overview of information security in general and how they protect customers and data at Gap. John Gearhart (Senior Security Engineer) will walk through some hacker techniques (aka “The Mind of the Adversary”). Andrew Yueng (internship coordinator) will be available to discuss technical internships at Gap. 

John Gearhart, is a Senior Security Engineer with GapTech and leads the Cyber Defense Center – Attack and Penetration Testing team (Red Team). John has over 15 years of hands on information security experience. During that time, he has engineered secure networks, provided malware analysis, incident response, and penetration testing for various industries; including financial, biotech, and retail.

Rich Noguera is Chief Information Security Officer at Gap Inc. His scope of responsibility includes Enterprise Security Architecture, Security Engineering & Operations, Product Security, Strategy, Risk & Compliance, and Cyber Defense. Working across GapTech and the Brands/Business Units, the Information Security team is focused on protecting Gap Customer Data and Sensitive Information from abuse or exposure by unauthorized parties. Prior to Gap Inc., Rich was a leader in Enteprise Risk & Security Strategy at Accenture, Security Governance at Yahoo!, Security Engineering at Symantec, Risk Management at McAfee-Intel, and Enterprise Risk Management at Deloitte & Touche LLP. Rich has spent nearly his entire career within the Information Security industry. Within the community, he is a Founding Board member of the Retail Cyber Information Sharing Center (R-CISC), worked with the Information Security Working Group of the Bay Area Council, worked with the APT group of the Bay Area CISO Council, and supports the Hispanic IT Executive Council. And Rich is an alum of the University of Southern California and holds a Bachelor of Science in Business Administration.

CS Night 2016

posted Nov 7, 2016, 12:18 PM by Rosa Maria Garay   [ updated Nov 7, 2016, 12:19 PM ]


You are cordially invited to attend the 15th Annual USF Computer Science Night!
This year we are pleased to announce a keynote talk by Sarah Clatterbuck: Director of Engineering at LinkedIn and USF alum!

Thursday, December 8, 2016

Lo Schiavo Center for Science and Innovation - room 307 and 3rd floor breakout area 
Harney Science Center - room 232

Parking will be available in the Koret lot at the corner of Turk and Parker

Schedule of Events
  • 6:30 - Posters and demonstrations of student work, food and drink - Lo Schiavo Science 307 and 3rd floor breakout area
  • 7:30 - CS Highlights and Announcement of Top Projects - Harney 232
  • 7:45 - Keynote talk by Sarah Clatterbuck - Harney 232
Please RSVP, or by emailing

Assistant Professor Full-time Renewable

posted Oct 17, 2016, 10:11 AM by Rosa Maria Garay

The Department of Computer Science at the University of San Francisco is accepting applications for a full-time, renewable, non-tenure track Assistant Professor position starting in August 2017. Applicants must have a Ph.D. in Computer Science or a closely-related field. Strong applicants from all CS sub-disciplines will be considered.

Applicants must demonstrate exceptional teaching ability. Applicants will be expected to teach both undergraduate and graduate courses and to perform service duties to the CS department and university.

See for the full job description and application instructions. To receive full consideration applications must be complete and received by January 2, 2017.

Assistant Professor Tenure Track

posted Oct 17, 2016, 10:08 AM by Rosa Maria Garay   [ updated Oct 17, 2016, 10:10 AM ]

The Department of Computer Science at the University of San Francisco is accepting applications for a tenure-track Assistant Professor position starting in August 2017.  Applicants must have a Ph.D. in Computer Science or a closely-related field. Strong applicants from all CS sub-disciplines will be considered.

Applicants must demonstrate both exceptional teaching ability and a strong potential for independent and collaborative research in computer science. Applicants will be expected to teach both undergraduate and graduate courses, maintain an active research program that involves students and perform service duties to the CS department and university.

 See for the full job description and application instructions. To receive full consideration applications must be complete and submitted by January 2, 2017.


posted Sep 13, 2016, 9:20 AM by Rosa Maria Garay

Introduction to Fast Exploratory Data Analysis Experience with R and Visualization

Date: September 15th 
Time: 11:45am-12:45pm
Location: Harney Science Center (Room 235)

R is arguably the best analytics platform in the world that is open-source with more than 9000 packages and is growing rapidly. But it’s hard to start and be productive if you are not programmers. Exploratory ( is a desktop app that provides a simple and easy to use interactive data exploration environment where users can quickly access R’s analytic power and visualization to explore various data ranging from files, databases, to NoSQL, and find valuable insights in a reproducible and collaborative way. 

Kan Nishida (@KanAugust), co-founder/CEO of Exploratory. Prior to Exploratory, Kan has 20 years of experience in building products and solutions in Big Data, Analytics, BI, and Data Visualization fields, at Oracle.

Full-time Faculty Position for 2016-2017

posted May 31, 2016, 1:04 PM by Dave Wolber

The Department of Computer Science at the University of San Francisco invites applications for a one-year full-time faculty position for the 2016-17 academic year (beginning this August!) The position is for a non-tenure-track faculty member whose primary responsibility is teaching, and will include a teaching load of three courses per semester. Though the position is for one year, there is potential for a longer-term.

Applicants must have a Ph.D. or M.S. degree in Computer Science or a related field. For additional information and to apply, please email Department Chair David Wolber at Applications should be submitted electronically and include a cover letter, current CV and teaching statement. You may also submit up to three letters of recommendation 

Note that our review of applications will begin immediately and will continue until the positions are filled. Contact us now!

WICS Award

posted Jan 27, 2016, 2:10 PM by Sami Rollins

The USF Women in Computer Science club is excited to announce that it has received a $3,000 seed award from the National Center for Women in Technology and

The WICS group, led by Janet Chavez, Courtni Wong, India Buckley-Becknell, and Anaelia Ovalle, is excited to use the award to raise visibility of the group and host some exciting events to help broaden participation in computing.

This semester, the club will begin a regular "WICS and Waffles" social hour, and is planning a tech field trip and a hackathon.

Congratulations USF Women in Computer Science!

Tenure Track Positions for 2016-2017 in CS

posted Sep 4, 2015, 8:51 AM by Greg Benson   [ updated Sep 4, 2015, 5:04 PM ]

We are happy to announce that we will be searching for two tenure-track faculty members this year.

Applications are due by December 1, 2015.

For more details about the position and how to apply go to: Tenure Track Position.

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