Thoughts of Recent Graduates

A few recent graduates of our MCS and PhD programs share recollections of their time at Iowa, as well as what they are currently working on. More Senior alum as well as Bachelor's graduates may be featured.


Xiaoli Yang and Shenzhi Zhang, 1989 MS

Xiaoli Yang and Shenzhi Zhang sporting their 2017 CS Hoodies

1989 MS graduates share memories of their time at Iowa as well as highlights and tips from their careers.

When did you graduate from CS at UI? With what degrees?

We both graduated in 1989 with MS in CS.

What have you been doing professionally since then?

Xiaoli had worked for Microsoft since graduation for over a decade, worked as a software developer on programming language tools such as compiler, debugger etc., also worked on photo editing products for many years.

Shenzhi had worked for Microsoft for 5 years and then left and started his own company working on music software and game engine development. Later he joined a Startup called Syntrillium working on audio editing and Adobe bought Syntrillium in 2003 and since then he has been working on audio editing, video editing and Virtual Reality.

What memories do you have of the courses you took or the professors you interacted with in CS at UI?

We had so many fond memories of the department. We are very grateful for the chance to do graduate study there. Professor Kearney was our academic adviser. He guided our research work on computer vision, reviewed our paper and sponsored us going to conference. He also helped us find our first job at Microsoft. We are forever very grateful to him for all his help.

We also became close friend with Professor Hantao Zhang who taught Shenzhi Graph Theory. Xiaoli also worked as TA for Professor Slonneger, who was a very kind and dedicated in teaching. Shenzhi had great time in Professor Bruell’s seminar, he was always very encouraging so Shenzhi didn't feel very nervous when doing presentation.

Can you describe some of the ways in which being a Computer Science professional has changed since you started your careers?

The software industry has certainly changed a lot over the years. For a software professional, there are two major changes. First is that you need have strong communication skills. In early days the projects were small in general, machine was slow and developer just need to dive into algorithm to make the code smaller or faster and sometimes both while tester just do black box testing.  We didn't even have "program manager" job title back then. Now the projects usually are huge. A lot of times you need to coordinate with people from different groups within your organization and work with people from other organizations.

Another change is the software development method change. We used to do a planning → design → implementation → testing → release cycle, we call it waterfall model. Nowadays an agile model or scrum model is widely adopted. These two changes are related. The agile development model satisfies the communication requirement needed for huge projects.


Fredrick Galoso, BS 2013

Galoso with Georgia Tech Ramblin' Wreck, a 1930 Ford Model A Sport coupe. Schematics from mafca.com.

Fred Galoso  is a 2013 CS BS graduate. He is currently Senior Software Engineer, Trello at Atlassian.

When did you graduate from Iowa and what degree(s) did you get?

I graduated Fall 2012, B.B.A., Management Information Systems and Summer 2013, B.A., Computer Science.

What has kept you busy since you graduated and what are you up to now?

Soon after graduating from Iowa, I started working as a software developer for Dwolla, a venture backed, financial technology company in Des Moines, IA. For three years I helped build some of the core fraud, accounting, and data systems that moved billions of dollars through the payments network. In 2016, I joined Trello, where I continue to work today as a senior software engineer. I've had an opportunity to work on a product that has millions of users around the world, developing features as varied as enabling large organizations to use and manage Trello, helping develop an experimentation platform, and creating user experiences that educate and empower users to get organized and collaborate together. In early 2017, I was part of the Trello team that was acquired by Atlassian for $425 million, a NASDAQ traded collaboration software company.

I recently finished a M.S. in Computer Science from the Georgia Institute of Technology. From 2015 to 2017, I specialized in Interactive Intelligence, studying the intersection of human-computer interaction and artificial intelligence.

I've had an opportunity to work as an early employee at not just one, but multiple ambitious and industry changing companies. It has been an exhilarating ride and I've thoroughly enjoyed working to build products that have had a substantial impact in such a short amount of time.

What does Trello do?

Trello is the easy, free, flexible, and visual way to manage projects and organize anything, trusted by millions of people from all over the world. Whether it is an individual, team, or large organization like Pixar, Google, or UNICEF, we help people work more collaboratively and get more done.

How has working remotely factored into your time at Trello/Atlassian?

It has enabled me to continue to live in Iowa while working for a large multinational technology company. It's also let me experience what appears to be a way of working that will continue to become more prevalent into the future. Thanks to tools like Trello, chat, video conferencing, and other productivity applications more and more organizations are making distributed teamwork an effective and productive way of working that greatly expands the talent pool for companies.

Tell us about some of your favorite experiences as a student in the CS dept at Iowa?

I remember fondly many late nights working with my fellow classmates in MacLean Hall on assignments and projects. I enjoyed my CS classes, especially taking classes taught by Dr. Doug Jones, Dr. Aaron Stump, and Dr. Teodor Rus and being engaged in discussion about the applications of computing in greater society. Finally, I enjoyed attending and learning from interesting colloquium speakers.

What advice do you have for our students?

While in school, engage with your fellow students and instructors. Go to office hours, make connections, and be as active as you can be in your learning. As with many things, what you get out of something is proportional to what what you put into it. Many of the things I learned and remember the most came from interactions that were not directly in the classroom.

Another thing I would encourage students is to seek opportunities to apply what they are learning to interests or projects outside of class. This could be a job, a club, an organization, open source, research, or volunteering - computing is ubiquitous and there are many opportunities to reinforce and apply your learning. This will also give you a body of work that you can point to, something that will be invaluable when you're seeking your next opportunity, whether it's a job in industry or continued education.

Finally, take measured risks, be entrepreneurial, and be prepare yourself for opportunities. Risk taking enables you to go for challenges and take initiative on problems that you may not normally have worked on. Entrepreneurial thinking will enable you to find ways to solve problems creatively. You may not know what you will work on next, but if an opportunity presents itself, if you're prepared, you can actually seize it.


Andy Berns, PhD 2012

Image of Berns; Computer Science assistant professor - University of Northern Iowa; in Real-Time Embedded Systems Laboratory

Andy Berns is a 2012 PhD graduate. He is currently an Assistant Professor in Computer Science at University of Northern Iowa, Cedar Falls, Iowa. He also manages the Department's Real-Time Embedded Systems Lab. As a PhD student, Berns was a UI Presidential Scholar.

Can you tell us what you've been up to since graduating with a PhD in 2012?

After spending the spring of 2013 teaching at the University of Iowa, I became an assistant professor in the Department of Computer Science at the University of Wisconsin-La Crosse (UWL) in the fall of 2013. At UWL, I had the chance to work with some great faculty members and students, I taught a variety of courses from introductory computer science to algorithms to software engineering, I supervised several Masters of Software Engineering projects, and I helped advise students groups like the cybersecurity club. In the fall of 2016 I moved to my undergraduate alma mater, University of Northern Iowa (UNI) and became an assistant professor there. Here also, I  have the pleasure of teaching a variety of courses, as well as managing the Real-Time Embedded Systems Laboratory. I really enjoy working at a regional comprehensive university where I have the opportunity to teach a variety of courses while still performing my own research with the assistance of our students.

Can you tell us a bit about your dissertation?

My dissertation (Self-Stabilizing Overlay Networks) looked at how we can build overlay networks (networks built using logical links) that are capable of eventually operating correctly no matter what transient fault occurs, or what arbitrary initial state the distributed system is in. Common examples of overlay networks include BitTorrent and other peer-to-peer file sharing programs. With the growth of the Internet, many overlay networks now consist of a large number of computers, and these computers are of course prone to failure and lack a central point of control. Self-stabilizing overlay networks aim to give systems such as these a way to quickly form a correct network to allow, for instance, efficient communication or resource discovery. My dissertation presented a generic framework for self-stabilizing overlay network creation, as well as a time- and space-efficient algorithm for creating a particular network.

What advice can you give current graduate students in the CS department?

My first piece of advice is to start thinking about your goals early on in your graduate school career and work at tailoring your experience towards these goals. For instance, many regional comprehensive universities would like to see evidence that you can be a good teacher and also evidence that you have a growing research agenda that can involve the students at their institution. Some other types of schools may look for more evidence of a strong research agenda, or may care more about evidence of good teaching. My advice is to think about what you want to do, and then talk with your advisors to help them guide you in reaching those goals!

My second piece of advice, though, would be to be open to other opportunities that you may not have thought about! While in graduate school you may find your goals change. While you are searching for jobs, you may find openings from a variety of institutions in a variety of places, and might even find industry jobs that sound more appealing to you than academic jobs. Don't hesitate to explore these opportunities, even if they aren't exactly what you were planning on earlier.

Advisors: Sukumar Ghosh | Sriram Pemmaraju


Tyler Jensen, MCS 2011

'11 MCS Alum Tyler Jensen at Kiew Lom View Point outside of Pai, a small backpackers paradise in Northern Thailand.

Tyler Jensen is a 2011 MCS graduate. He is the Co-Founder & CTO at SpareChange Inc.

When did you graduate from Iowa and what degree(s) did you get?

I graduated from the University of Iowa with a BS/MCS in Computer Science in the winter of 2011. I took advantage of the combined 5 year MCS program but ended up completing it in 4 ½ years.

What has kept you busy since you graduated and what are you up to now?

After graduating I spent an amazing 4 years at Microsoft in Seattle, Washington working on 1st party mobile apps for Windows Phone and then switching to hyper-scale cloud services across Xbox Live and finally Microsoft Azure. Eventually I decided I wanted to travel and focus my skills on making a more positive impact on the world. I jumped at the chance to start my own company, SpareChange, after hearing an idea from a former colleague while we were at a computing conference at Twitter. Rather spontaneously I quit my job and moved to Chiang Mai, Thailand which is a popular spot for “digital nomads” who run various sorts of businesses remotely while taking advantage of Thailand’s low cost of living and excellent internet infrastructure. This was my first time leaving North America and it was quite the experience! If you ever have the chance to immerse yourself in a different culture, absolutely seize it. After a half year of developing an initial version of my app and traveling around Southeast Asia, I moved back to Seattle to be closer to my business partner and find networking opportunities to promote our app and raise funding. In April of 2017 we launched publicly on the Apple App Store and Google Play Store and will begin looking for investors shortly. It has been a wild ride, and I could not have done it without the opportunities the CS department afforded me.

What does SpareChange do?

SpareChange logo

SpareChange (gosparechange.com) lets you make tax-deductible donations to any of the 1.9+ million registered non-profits in the United States. Specifically, you can attach micro-donations to different types of transactions so you don’t even have to think about giving back to your community. For example, you can donate $1.00 every time you take an Uber, or $2.00 every time you buy gas. We noticed it’s difficult to navigate the world of non-profits. If you want to make a donation to someone, often times you have to sign up with them individually, enter in your payment info, etc. for every single one. Even worse, a majority of donations today are made by cash or check. With our platform, you can donate to any non-profit using modern payment solutions such as your credit card, bank account, and eventually Apple Pay, Google Wallet and Paypal. I like to describe it as the Venmo of non-profit donations.

Tell us about some of your favorite experiences as a student in the CS dept at Iowa?

Most of my favorite experiences as a CS student were in extra-curricular activities. I was Vice-President of the ACM for 2 years and had a blast meeting other students interested in computing, planning events and organizing the University of Iowa Computing Conference where I got to design and run the annual coding competition. When I was in grad school I absolutely loved being a teaching assistant and helping new students learn the basics of programming. Being a TA was probably one of the most rewarding experiences of my life. I also had the pleasure of being a research assistant for Professor Stump and Tinelli where I got hands on experience designing and implementing the initial version of StarExec.

What advice do you have for our students?

Take risks. If you’re young and in technology, the world is your oyster. Do bold things while you don’t have a family to support or anyone who relies on you. If you fail who cares, there is a massive shortage of good tech workers out there and jobs really aren’t that difficult to come by. I think a lot of people just assume that you get a job, work until you’re 65, then retire and die. There’s way more to life than that, but it’s up to you to truly live it.


Valerie Galluzzi, PhD 2015

Valerie Galluzzi - 2015 PhD graduate.  Assistant Professor in Computer Science and Software Engineering at Rose-Hulman Institute of Technology, Terre Haute, Indiana.

Can you tell us what you've been up to since you graduated with a PhD in Computer Science in 2015?

I have been working as an Assistant Professor in the department of Computer Science and Software Engineering at Rose-Hulman Institute of Technology. So far the first year of working as a faculty member has been a roller coaster ride, but I am very happy to be working at the top undergraduate engineering school in the country. I had always wanted to go to a faculty position in a small teaching school, and it is great to be in a place where I can get to know top-quality students. In my first year here I was able to help students start WOLFPAC (Women Of Like Fields Passionate About Computing), a club for women in computing that got national press. I was also able to start a multi-disciplinary course on the Internet of Things, which I will teach again this winter.

Can you tell us a bit about your dissertation?

My dissertation, Automatic Recognition of Healthcare Worker Hand Hygiene, focused on automatically recognizing whether healthcare workers were washing their hands. As part of my work, healthcare workers in intensive care units would wear wristbands with accelerometers in them during their normal hospital shift. I designed machine learning methods that could determine when they washed their hands during that time period and for how long. I also did work on finding out whether we could recognize correct hand hygiene technique.

Now that you are a professor yourself, do you have any advice for graduate students who might be interested in taking the academic career route?

The most important thing is to figure out whether you would like to focus on teaching or research. A professor at a teaching-intensive school is judged heavily on the quality of their teaching and pedagogy, while a professor at a research-intensive school will be judged heavily on the number of grants they receive and publications they write, as well as their work with graduate students. If you are interested in working in a teaching-intensive position, I would recommend that you pursue working as an in-class teaching assistant during your graduate studies. If you can have a “sole responsibility” course where you put together all course materials that is an excellent opportunity to take. When applying for academic positions at teaching-intensive schools the hiring committee will be very interested in your teaching experience and your teaching statement, which talks about your teaching philosophy. A teaching philosophy is not easy to get overnight—it is something you will build through experiences in class.

If you are interested in working in a research-intensive position, I would still recommend gaining experience as an in-class teaching assistant because classroom teaching is an important part of those positions. However, I would recommend focusing more on research as you will have to figure out what your research agenda will be after graduation—after all, you will be expected to lead a research lab! If possible I recommend helping your advisor to write grants and finding a way to lead a group within the lab. You should also focus on publishing in as many high quality venues as possible since your publication history will be very important to the hiring committee. You may also consider doing postdoctoral work with another lab after graduation to increase your number of publications and widen your scientific network.

Above all you must make sure that your advisor is supportive of your decision. I was fortunate as the first question my advisor, Ted Herman, asked me was “Where do you want to go after graduation?”. I was able to work towards my goal of a position at a teaching-intensive institution from the start because he was supporting me and giving me the right opportunities. If you haven’t told your advisor or they don’t support this choice it will be difficult to get the opportunities you need (e.g., teaching assistantships) to fill out your resume. The preparation for a research scientist at an industry lab is far different from the preparation necessary for academia.

Advisor: Ted Herman | CompEpi


Donald Curtis, PhD 2011

Donald Curtis, PhD 2011

Can you describe your dissertation research briefly and for a lay audience?

My dissertation research was on the spread of diseases that can happen as a result of interactions between healthcare workers in a hospital. I used anonymized computer login data for actual healthcare workers to build graphs to represent interactions that could allow disease spread. Using simulations I studied how disease spread on the graphs and compared it with popular disease graphs proposed by other researchers. I also studied targeted vaccination policies, where you want minimize disease spread by "targeting" a small set of individuals to vaccinate. This problem is important for cases of limited vaccine supply or where the cost of vaccination is high.

What are you doing now in a professional capacity?

Currently I work at Google as a Software Engineer. My work entails a lot of programming on a topic that is quite a bit different from my dissertation research, but I use the the critical thinking and communication skills I learned while researching everyday. And there have been a few times when my research has been quite handy.

Can you tell us a little bit about a problem/project that you are currently working on?

I'm currently working on WebRTC (https://webrtc.org/) which is an open-source project supported by Google that makes it remarkably easy to do real-time audio/video communication. Our team works on the open-source implementation of WebRTC which is part of Google Chrome and enables real-time communication on the web. Google Hangouts uses WebRTC and there are lots of other projects outside of Google that also build on top of the technology.

Advisor: Sriram Pemmaraju | CompEpi


Jason Fries, PhD 2015

Jason Fries - 2015 PhD graduate; currently postdoctoral fellow with Stanford University's Mobilize Center

What are you working on now?

I'm working on 2 primary projects (1) developing tools and methods using a new formalism for distant supervision called "data programming" and (2) modeling outcomes associated with joint replacement surgeries.

Chris Re's group is developing a well-known system called DeepDive (http://deepdive.stanford.edu), a new type of data processing system that extracts entities and relations from unstructured "dark data" like text, tables, images, and figures. DeepDive is used in several high-impact applications including monitoring human trafficking on the "dark" web, automatically constructing databases of paleontological data, and extracting gene-phenotype and other biological relationships from scientific literature.

DeepDive scales nicely as a system, but development cycles can be long as users iterate on distant supervision rules for labeling input data. This has motivated some interesting theoretical work in Chris's lab on programmatically supervising and de-noising data, a machine learning paradigm called "data programming" (https://arxiv.org/abs/1605.07723). I've been collaborating on building their next generation data processing system Snorkel and developing lightweight NLP systems for extracting biomedical relations from clinical text.

My second project focuses on osteoarthritis (OA). A common clinical endpoint of OA is total joint replacement so we’re looking at how to use electronic medical record (EMR) data to better predict post-operative recovery. Unstructured patient notes are quite useful in this capacity, so it's a great use case for data programming. Ultimately these models help lay the foundation for a more ambitious goal of deploying a near real-time implant surveillance system, where medical devices can be monitored and scored quantitatively using patient EMR data.

My overall goals during my postdoctoral fellowship are to (a) closely integrate research discoveries and tools into clinical settings and (b) develop a strong, empirical argument why structured data systems are important, even in the age of deep learning and automatic feature engineering. Both of these goals are a continuation of what I started during my PhD in CS at Iowa. My ultimate goal is to transition into an academic position or a research scientist in the hospital/healthcare field within the next 2 years.

Can you tell us a bit about your dissertation?

My dissertation looked at information extraction methods for population health surveillance. While some aspects of human health are reasonably well captured by primary care systems (e.g., hospitals, clinics), examining the ways in which behavior and everyday life impact health requires analyzing alternate data streams like social media or wearables and smartphones. For example, in endemic sexually transmitted infections it's useful to know prevalence rates of behaviors like safe sex practices, illegal drug use, etc. in order to tailor public health interventions. This information is hard to collect and definitely not a standard component of the EMR. The first part of my dissertation looked at sexual behavior surveillance of individuals using Craigslist to find anonymous sexual partners. I presented ways of algorithmically collecting survey-like information on risk behaviors, population demographic data, and travel patterns in near real-time and at city-level geographic resolution. The last part of my dissertation looked at a collection of 15 million clinical notes from the UIHC's EMR system, where I worked on representation learning and recurrent neural network methods for named entity recognition.

Do you have any advice for our current graduate students?

Take as many statistics courses as you can, as early as you can. Also, definitely take Calculus III! I skipped the advanced math courses and really regretted it later in grad school where my time and choices were more constrained. From the CS side, probabilistic graphical models and more generally probabilistic approaches to AI (e.g., Bayesian networks) are extremely useful in many different fields. Finally don't shy away from building toy distributed systems on Amazon EC2 or other compute infrastructures. Being able to quickly analyze large datasets is immensely valuable and the norm in any "data scientist" type of job.

Advisor: Alberto Segre | CompEpi


Andrew Reynolds, PhD 2013

Andrew Reynolds, PhD 2013

Can you describe your dissertation research briefly and for a lay audience?

My dissertation focused primarily on automatically discovering bugs in software and hardware systems. This technology was used by the Intel Corporation for testing the correctness of prototypes of hardware designs.

What are you doing now in a professional capacity?

I am currently a post-doctoral researcher at EPFL in Lausanne, Switzerland working on the Satisfiability Modulo Theories (SMT) solver CVC4.

Can you tell us about an interesting problem that you are currently working on?

I have recently worked on techniques for automating inductive reasoning. While computers are typically very good at deductive reasoning tasks such as solving Sudoku puzzles, they lack support for tasks where inductive reasoning (and hence, some form of creativity) is required. The techniques I have developed for automating induction in CVC4 are being used to prove non-trivial properties of functional programs, and to assist users of interactive theorem proving environments.

Advisor: Cesare Tinelli | Computational Logic Center


Geoffrey Fairchild, PhD 2014

Geoffrey Fairchild, PhD 2014 alumnus, in New Mexico

Geoffrey Fairchild is a 2014 PhD graduate. He had earned his MS in 2011, and a BS in Mathematics and Computer Science from The University of Texas at Austin in 2008. His advisor was Alberto Segre and he was a member of the comp|epi group.

Can you describe your dissertation research briefly and for a lay audience?

My dissertation research is focused on disease surveillance, a key aspect of public health and epidemiology. The core problem I address is this: data are gathered on people infected with certain diseases so that epidemiologists can understand disease dynamics and public health officials can make decisions such as what vaccines to produce, where to allocate vaccines, where to allocate funds, etc. Traditionally, most data are gathered from primary care facilities (e.g., doctors’ offices, hospitals) and laboratories. The first project in my dissertation focused on how to use computational techniques to improve on the location of primary care facilities from which public health data is gathered. Traditional disease surveillance networks have some problems, though; there’s often a lag of a few weeks before data are available to the public, and many regions of the world lack the infrastructure to maintain such networks. To address these concerns, there’s been a recent push to use publicly available internet data to aid in disease surveillance. The rest of my dissertation focused on using Wikipedia for this purpose.

What are you doing now in a professional capacity?

Upon finishing my PhD, I accepted an offer for a staff scientist position at the Los Alamos National Laboratory, where I interned as a grad student for several years. I am continuing to work on disease surveillance and modeling problems. A lot of my research is still focused on using Wikipedia to enhance disease surveillance efforts. I’ve also spent significant time working with a large-scale agent-based simulation of human movement and disease spread to understand potential mitigations during an epidemic or pandemic (e.g., wearing face masks, closing schools). Unrelated to my disease surveillance and modeling research, I am also working on a large operations research project studying optimal design of water distribution networks.

A few months ago, one of your papers received a lot of press. Can you tell us about that and where we can read more about that research?

Our Wikipedia work has received quite a bit of press! Our initial paper, "Global Disease Monitoring and Forecasting with Wikipedia," was published in PLOS Computational Biology and is available at https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003892. In that paper, we showed that statistical models built using time series of publicly available Wikipedia article access logs can accurately nowcast and forecast disease incidence in many regions of the world. A follow-up paper to this study, "Eliciting Disease Data from Wikipedia Articles," uses natural language processing and machine learning techniques to pull disease data from the actual article content. This paper was accepted to be presented at the 2015 9th International AAAI Conference on Web and Social Media (ICWSM) Wikipedia workshop. A pre-print is available on arXiv at https://arxiv.org/abs/1504.00657.

Advisor: Alberto Segre | comp|epi


Harley Eades, PhD 2014

"My dissertation explored the design and mathematical analysis of dependently typed functional programming languages. These are programming languages of the future because they come equipped with the ability to verify the correctness of programs using mathematical logic. Verifying the correctness of software is important especially for software that controls safety critical devices like cars, planes, and nuclear power plants."

"I am now an assistant professor of computer science in the Department of Computer and Information Sciences  at Georgia Regents University Augusta (GRU). At GRU I teach all of the theoretical computer science courses, and work on research applying logic and category theory to various areas of computer science."

Advisor: Aaron Stump | Computational Logic Center


Austin Laugesen, MCS 2012

Austin Laugesen, MCS 2012

"I work for the [Microsoft Windows Phone Services] Engineering team doing program management. It is my responsibility to determine what gets built and why. I manage projects and also connections between different teams. I don’t manage people.

I don’t do a whole lot of coding currently. But, the stronger I am technically the easier it gets to do my job.

My most useful experiences as an MCS student were the guided independent research projects I did with Prof. Stump on compiler construction and with Prof. Chipara on sensor networks."


Duckki Oe, PhD 2012

“I developed optimized automated reasoning software (namely, SAT/SMT solvers), and verified its correctness using formal theorem provers based on type theory.”

“I'm a postdoctoral associate at MIT. I'm working as a member of a 3-institution (Princeton, Yale, MIT) team on a DARPA-commissioned project, developing verified operating system and applications for a remotely controlled unmanned vehicle.”

Advisor: Aaron Stump | Computational Logic Center


Yelena Mejova, PhD 2012

Yelena Mejova, PhD 2012

“I am a Scientist at the Qatar Computing Research Institute (QCRI), living in Doha, Qatar. At QCRI I develop methods for linking the online social media world to the "real" world. We track dietary habits of social media users to estimate obesity and diabetes rates, and to discover the importance of social connections in health. We also attempt to expand the "filter bubble" of online users by personalizing recommendations of less-popular news items. As a researcher, I get to travel all over the world and meet amazing people -- I highly recommend it! Previously, I was a Postdoc at Yahoo! Labs in Barcelona”

“My PhD research was on opinion extraction and sentiment analysis of social media text.”

Advisor: Padmini Srinivasan | Web Mining


Chris Hlady, PhD 2011

Chris with his wife Megan in Olympic National Park, WA.

“My PhD research involved modeling healthcare workers, patients, and infectious diseases and building a realistic simulation of a hospital to answer questions about efficient use of resources and the spread of hospital-acquired infections.”

“I work as a software development engineer at Amazon.com. My team designs, builds and maintains the AmazonLocal website, and the Scalable, redundant back-end service used by the website and out mobile applications.”

Advisor: Alberto Segre | CompEpi


Imran Pirwani, PhD 2008

Imran with the 1986 Turing Award Winner, Robert Tarjan.

"My PhD research focused on approximation algorithms for various optimization problems inspired by applications on wireless sensor networks.

I work at Apple Inc., in Cupertino, CA, as a software engineer in the Maps Team. I am involved in research and development spanning aspects of mapping such as search, data processing and mining, geometry, traffic and more broadly, optimization.

The algorithmic tools and skills which I learned as a graduate student have been extremely useful to me as a professional at Apple Inc."

Advisor: Sriram Pemmaraju | Algorithms Research Group


Charan Varadan, MCS 2006

"I work as a Portfolio Risk and Margin Analyst working with hedge fund clients and asset managers investing in Asia.

A significant amount of my work involves working with large amounts of data. I use concepts I learned in Software Engineering, Database Systems, and Algorithms in my daily work.

The MCS program was flexible enough that I was able to concurrently take outside-the-department courses in Numerical Analysis, Economics, and Statistics. This helped me in pursuing a degree in quantitative finance, subsequently."