department of computer and information science ph.d. graduate program

Department of Computerand Information Science

Ph.D. Graduate Program

Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013 2

Where is the University of Oregon?

USA

Eugene

Oregon


What is Eugene, Oregon like?


Eugene Information Small city!

❍ Population of 150,000 Young town!

❍ Median age of 34 years Close to everything!

❍ Portland is 110 miles away❍ Pacific coast, mountains, and ski resorts are 50 miles❍ Several national parks and forests are nearby

Many arts, music, social, entertainment options! Micro-breweries and wineries!


What is the University of Oregon like?


University of Oregon Information 24,000 Students (3,000 Graduate) 46% male and 54% female 38% resident and 62% non-resident College of Arts and Science Professional Schools

❍ Law, Business, Architecture Union of Graduate Assistants

❍ The GTFF is a labor union representing over 1300 funded Graduate Teaching Fellows and Research Assistants

Sports❍ Division 1 football, basketball, baseball, track, volleyball❍ “Tracktown, USA” (Historic Hayward Field)


Department of Computer and Information Science (CIS)

ArtificialIntelligence

ComputationalScience

Informatics

Networking

Universal Access

Scientific Visualization & High Perf. Computing

Programming Languages & Software Engineering

Security

Human-ComputerInteraction

Parallel & DistributedComputing

TheoreticalComputerScience


CIS Department Information Tenure-track Faculty: 18 Graduate Students: 67

❍ 29 Master’s students❍ 38 Ph.D. students

CIS Lecture Series Programming language summer school Graduate Student Association (GSA)

❍ Graduate Research Forums❍ “Friday Colloquium” happy hours for inspired discussions❍ Excursions

◆ ski trips, mountain climbing, football games and more.

❍ Atmosphere of support and encouragement!

Zena Ariola, Professor Ph.D. from Harvard University (1992) NSF CAREER award (1997) Invited Professor at University of ParisVII (2012) Oregon Programming Languages Summer School

(OPLSS)http://www.cs.uoregon.edu/research/summerschool/ summer13/

Research interests❍ Programming Languages, Logic, Type Theory, Rewriting

Systems, Lambda-calculus, Category Theory SECUBE: Sequent Calculus Cube Develop a model of computation based on the interaction

between a producer / comsumer of informationPh.D. Graduate Student Recruiting, Beihang University, December 10, 2013 9

Sarah Douglas, Professor (Emerita) Ph.D., Stanford University (1983) Fulbright Lectureship

❍ Indian Institutes of Technology, India (1992) NSF Women in Engineering Leadership (2001) Chair, Human-Computer Interaction IEEE-ACM

Computing Curriculum (2001) Research Interests

❍ Human-computer interaction◆Multi-sensory interaction: haptics, graphics, audio◆Gender in virtual social environments◆Studio-based design of interaction

❍ BioinformaticsPh.D. Graduate Student Recruiting, Beihang University, December 10, 2013 10

Allen D. Malony, Professor Ph.D., University of Illinois, Urbana-

Champaign (1991) Fulbright Research Scholar

❍ Utrech University, The Netherlands (1991)❍ University of Vienna, Austria (1998)

National Science Foundation Young Investigator (1994) Alexander von Humboldt Research Award (2002) Director, UO Neuroinformatics Center Research interests

❍ Parallel performance analysis, scalable parallel software and tools, high-performance computing

❍ Computational science, neuroinformatics Email: [email protected]


mailto:[email protected]


TAU Project Tuning and Analysis Utilities (TAU)

❍ 20-year project in parallel performance analysis Performance problem solving framework for HPC

❍ Integrated, scalable, flexible, portable❍ Target all parallel programming / execution paradigms

Integrated performance toolkit❍ Multi-level performance instrumentation❍ Flexible and configurable performance measurement❍ Widely-ported performance profiling / tracing system❍ Performance data management and data mining❍ Open source (BSD-style license)

Neuroinformatics Center (NIC) Application of computational science methods to human

neuroscience problems❍ Tools to help understand dynamic brain function❍ Tools to help diagnosis brain-related disorders❍ HPC simulation, large-scale data analysis, visualization

Integration of neuroimaging methods and technology❍ Need for coupled modeling (EEG/ERP, MR analysis)❍ Apply advanced statistical signal analysis (PCA, ICA)❍ Develop computational brain models (FDM, FEM)❍ Build source localization models (dipole, linear inverse)❍ Optimize temporal and spatial resolution

Internet-based capabilities for brain analysis services, data archiving, and data mining



Selected Publications N. Chaimov, S. Biersdorff, and A. Malony, “Tools for Autotuning and Specialization,” International Journal on High-

Performance Computing Applications, to appear, 2014. K. Huck and A. Malony, “General Hybrid Parallel Profiling,” International Conference on Parallel, Distributed and

Network-Based Computing (PDP), to appear, February 2014. A. Charif-Rubial, D. Barthou, C. Valensi, S. Shende, A. Malony, and W. Jalby, “MIL: A Language to Build Program

Analysis Tools through Static Binary Instrumentation,” IEEE Conference on High Performance Computing (HiPC), to appear, December 2013.

D. Ozog, J. Hammon, J. Dinan, P. Balaji, S. Shende, and A. Malony, “Inspector-Executor Load Balancing Algorithms for Block-Sparse Tensor Contractions,” International Conference on Parallel Processing (ICPP), September 2013.

J. Hammond, S. Krishnamoorthy, S. Shende, N. Romero, and A. Malony, “Performance Characterization of Global Address Space Applications: A Case Study with NWChem,” Concurrency and Computation: Practice and Experience, 24(2):135–154, 2012.

S. Shende, A. Malony, J. Linford, A. Wissink, and S. Adamec, “Isolating Runtime Faults with Callstack Debugging using TAU,” IEEE High Performance Extreme Computing Conference (HPEC), 2012.

A. Malony, S. Biersdorff, S. Shende, H. Jagode, S. Tomov, G. Juckeland, R. Dietrich, D. Poole, and C. Lamb, “Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs,” International Conference on Parallel Processing (ICPP), September 2011.

A. Malony, J. Mellor-Crummey, and S. Shende, “Methods and Strategies for Parallel Performance Measurement and Analysis: Experiences with TAU and HPCToolkit,” in D. Bailey, R. Lucas, S. Williams (Eds.), Performance Tuning of Scientific Applications, CRC Press, 2010.

K. Huck, O. Hernandez, V. Bui, S. Chandrasekaran, B. Chapman, A. Malony, L. Curfman McInnes, and B. Norris, “Capturing Performance Knowledge for Automated Analysis,” Supercomputing Conference (SC), November 2008.

K. Huck, A. Malony, S. Shende, and A. Morris, “Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0,” Journal of Scientific Programming, special issue on Large-Scale Programming Tools and Environments, 16(2-3): 123–134, 2008.

Andrzej Proskurowski, Professor Teknisk Doktor, KTH (Royal Institute of

Technology), Stockholm 1974 Head, Steering Committee organizing Workshops on Graph

Classes, Optimization, and Width Parameters Research interests

❍ Complexity of combinatorial optimization problems❍ Computations in tree-like graphs

When restricted to graphs with bounded treewidth ("partial k-trees") many inherently difficult optimization problems are efficiently solvable

I and my colleagues have been working on developing efficient algorithms for problems on partial k-trees, on structural properties of those classes of graphs and their subclasses, as well as on finite recognition mechanisms for subclasses of those graphs

http://www.cs.uoregon.edu/~andrzej/ Email: [email protected]

Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013

http://www.cs.uoregon.edu/~andrzej/treewidth.html

http://www.cs.uoregon.edu/~andrzej/


Recent Publications H. Broersma, J. Fiala, P. Golovach, T. Kaiser, D. Paulusma and A. Proskurowski, Linear-Time Algorithms for

Scattering Number and Hamilton-Connectivity of Interval Graphs, in Proceedings of 39th International Workshop WG 2013, Springer-Verlag, Lecture Notes in Computer Science LNCS 8165, pp.127-138 (2013).

I. Adler, A.M. Farley, A. Proskurowski, Obstructions for linear rank-width at most 1, Discrete Applied Mathematics, (to appear).

H. Rodriguez, A. M. Farley, J. J. Flores, Andrzej Proskurowski, Qualitative Bifurcation Diagrams, Expert Systems (to appear).

A. Farley, S. Faulk, V. Lo, A. Proskurowski, M. Young Intensive International Summer Schools inGlobal Distributed Software Development, in Proceedings of 2012 Frontiers in EducationConference FIE'12, pp. 772-777 (2012).

P. Heggernes, J. Kratochvil and A. Proskurowski, Fourth Workshop on Graph Classes, Optimization, and Width Parameters, Guest Editors' Foreword, in Special Issue of Discrete Applied Mathematics 160(6), pp. 683-684 (2012).

P. Bonsma, A. Farley, and A. Proskurowski, Extremal graphs having no matching cuts, Journal of Graph Theory 69(2), pp. 206-222, (2012).

Binh-Minh Bui-Xuan, Pinar Heggernes, Daniel Meister, and Andrzej Proskurowski, A generic approach to decomposition algorithms, with an application to digraph decomposition, in Proceedings of COCOON 2011, Bin Fu, Ding-Zhu Du (Eds.), Springer-Verlag, Lecture Notes in Computer Science 6842, pp. 331-342 (2011).

P. Heggernes, D. Meister, and A. Proskurowski, Computing minimum distortion embeddings into a pathfor bipartite permutation graphs and threshold graphs, Theoretical Computer Science 412(12-14), pp. 1275-1297(2011).


http://ix.cs.uoregon.edu/~andrzej/pubs.html

http://ix.cs.uoregon.edu/~andrzej/pubs.html

http://ix.cs.uoregon.edu/~andrzej/pubs/JGT2010abc.pdf

http://ix.cs.uoregon.edu/~andrzej/pubs/101105distortion.pdf

http://ix.cs.uoregon.edu/~andrzej/pubs/101105distortion.pdf

Dejing Dou, Associate Professor Ph.D., Yale University (2004) Visiting Associate Professor at Stanford Center for Bioinformatics

Research (2012-2013) Best Research Paper Award Nomination for KDD (2007) Research Interests:

❍ Artificial Intelligence (specially Ontologies)❍ Data Integration❍ Data Mining❍ Biomedical and Health Informatics

Director: Advanced Integration and Mining (AIM) Lab❍ http://aimlab.cs.uoregon.edu❍ Many exciting research projects and collaborations

Email: [email protected]


http://netsec.cs.uoregon.edu/


AIM Lab Advanced Integration and Mining (AIM) Lab

❍ Semantic Data Mining❍ Data Integration and Data Mining ❍ Biomedical and Health Informatics

Knowledge Translation and Integration (SKTI, NSF)

Ontology-based Information Extraction Domain-specific Data Integration and Mining

❍ SMASH Project◆Health Social Network Analysis, NIH

❍ NEMO Project◆Neuroscience EEG Data Integration, NIH



Semantic Mining of Activity, Social, and Health Data

SMASH Project

20

Collaborators and Students Ontology-based Information Extraction

❍ Students: Fernando Gutierrez, Adam Martini, Javid Ebrahimi ❍ Steve Fickas (CIS, UO), Gina Griffiths (College of Education, UO), Hui Zong (Biology,

UO), Daya C. Wimalasuriya (Ph.D., 2011, Faculty at University of Moratuwa, Sri Lanka)

Semantic Data Mining❍ Students: Haishan Liu (Ph.D., 2012, joined LinkedIn as a Senior Software Engineer),

Hao Wang❍ Ruoming Jin (Kent State U), Paea LePendu (Ph.D., 2010, Stanford U), Nigam Shah

(Stanford U) Knowledge Translation and Integration (SKTI)

❍ Students: Shangpu Jiang, Adam Martini❍ Daniel Lowd (CIS)

SMASH❍ Students: Xiao Xiao, Hao Wang, Sabin Kafle❍ Postdoc: NhatHai Phan ❍ Brigitte Piniewiski (PeaceHealth), Ruoming Jin (Kent), Xintao Wu (UNCC), Jessica

Greene (UO/GWU), Daniel Lowd (CIS)Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013

21

Selected Publications Jessica Greene, Rebecca Sacks, Brigitte Piniewski, David Kil, and Jin S.

Hahn. “The Impact of an Online Social Network with Wireless Monitoring Devices on Physical Activity and Weight Loss.” (Accepted by) Journal of Primary Care and Community Health, 2012.

Yue Wang, Xintao Wu, Jun Zhu, and Yang Xiang. “On Learning Cluster Coefficient from Private Networks.” In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM12). pp. 395-402, 2012.

Brigitte Piniewski. “Personalized Medicine and Public Health." in Wireless Health: Remaking of Medicine by Pervasive Technologies. Edited by Mehran Mehergany, 2013.

Yelong Shen, Ruoming Jin, Dejing Dou, Nafisa Afrin Chowdhury, Junfeng Sun, Brigitte Piniewski, and David Kil. “Socialized Gaussian Process Model for Human Behavior Prediction in a Health Social Network</a>." In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM 2012). pp. 1110-1115, 2012


Anthony Hornof, Associate Professor Ph.D. from University of Michigan Program Director at the National Science Foundation

(2012-2014) Research interests

(1) Human-Computer Interaction (HCI)

(2) Assistive technology for people with disabilities Cognitive Modeling and Eye Tracking Lab

❍ The research in this lab combines cognitive psychology, human experimentation, computer interface design, sensor technology (eye tracking), and computer science

Email: [email protected] Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013 22



Ph.D. Student Working with Dr. Hornof Yunfeng Zhang, Ph.D. (expected 2014) Undergrad degree from Beijing Normal University Yunfeng is the ideal Ph.D. candidate for HCI

❍ Before starting at University of Oregon:◆Excellent written English (initially slow but very accurate)◆Experience running human experiments◆Excellent programming skills

❍ Strong interest in combining lots of different ideas from many different disciplines and fields

Accomplishments at UO❍ 7 papers (4 as 1st author) all in top venues❍ 7 awards and monetary prizes

24Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013

Prof. Hornof Presenting Award to Yunfeng Zhang

25

Intership at Palo Alto Research Center


Jun Li, Associate Professor Ph.D., UCLA (2002) Catedra de Excelencia (Chair of Excellence) at the

Carlos III University of Madrid, Spain (2010-2011) National Science Foundation CAREER awardee (2007) Senior Member of ACM (2009), IEEE (2011) Chinese Academy of Sciences Presidential Scholarship (1995) Research Interests

❍ Computer networking, Internet architecture, software-defined networking, online social networking

❍ Network security (for Internet routing, DNS, DDoS prevention, malware) Director: UO Network & Security Research Lab

❍ http://netsec.cs.uoregon.edu❍ Many exciting research projects and collaborations

Email: [email protected]: softlaser, Skype: softlaser2, QQ: 1494335605

26Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013

http://netsec.cs.uoregon.edu/


Recent Projects Internet routing forensics IP spoofing prevention Ghost domain name: removed but still alive Behavior-based Internet worm detection Active phishing disruption Trusted and incentivized peer-to-peer data sharing

between distrusted and selfish clients Tsunami: A parasitic, indestructible botnet on Kad


Ongoing Projects (1)

Internet Routing & Security❍ Buddyguard: Fast and reliable

detection of IP prefix hijacking andanomalies

❍ I-Seismograph: Observing andmeasuring Internet earthquakes

❍ E[BGP]: When expectations meetsreality: filtering illegitimate BGP routes

Internet Content Discovery & Delivery❍ Compass: A content discovery service

on the Internet ❍ DrawBridge: Enhancing software-defined

networking to throttle DDoS traffic❍ Internet traffic congestion avoidance on the fly


Ongoing Projects (2)

Online Social Networking❍ oSafari: OSN Fraud and Attack

Research and Identification❍ Sybils in Disguise: OSN-based

Sybil defenses revisited❍ Cosplay: When OSN meets cloud

computing❍ SOUP: Self-organized universe of

people


Reza Rejaie, Associate Professor Ph.D., University of Southern California

(USC) (1999) European Union Marie Curie Fellowship (2009) National Science Foundation CAREER Award (2005) h-index of 32 with more than 6000 citations Research Interests:

❍ Computer Networks, Network Measurement, Online Social Networks, Software Defined Networks, P2P Networks, P2P Streaming, Multimedia Networking

Director, Oregon Network Research Group (ONRG) http://www.cs.uoregon.edu/~reza


http://www.cs.uoregon.edu/~reza

Oregon Network Research Group (ONRG) Our research focuses on the applied areas of network

systems Collaborators include AT&T Labs, Bell Labs, Akamai Tech.

❍ Internship opportunities Selected ongoing projects

❍ IMPACT: Inferring the PoP-level, Geo-aware view of Internet’s inter-AS Connectivity

❍ CRONA: Cross Online Social Network Analysis❍ TAU: Traffic Analysis on Uonet❍ Instinct: Interdisciplinary Behavioral Analysis on OSNs❍ WalkAbout: Inferring Coarse-view of Connectivity for Very

Large Graphs For more information visit http://onrg.cs.uoregon.edu


http://onrg.cs.uoregon.edu/

The IMPACT Project Inferring the geographic footprint of individual

Autonomous Systems (AS) in the Internet Inferring the location of Points of Presence (PoPs)

for each AS and its connection through each PoP


Geo-aware PoP Level Topology of three ASes

Selected Publications Google+ or Google-? Dissecting the Evolution of the New OSN in its First Year, Roberto

Gonzalez, Ruben Cuevas, Reza Motamedi, Reza Rejaie, Angel Cuevas, WWW 2013 ISP-friendly Live P2P Streaming, Nazanin Magharei, Reza Rejaie, Ivica Rimac, Volker Hilt,

Markus Hofmann, IEEE/ACM Transactions on Networking, January 2013 Unveiling the Incentives for Content Publishing in Popular BitTorrent Portals, Ruben

Cuevas, Michal Kryczka, Angel Cuevas, Sebastian Kaune, Carmen Guerrero, Reza Rejaie, IEEE/ACM Transactions on Networking, October 2013

Montra: A Large-Scale DHT Traffic Monitor, Ghulam Memon, Reza Rejaie, Yang Guo, Daniel Stutzbach, Elsevier Computer Networks, Special Issue on Measurement-based Optimization of P2P Networking and Applications, February 2012

Sizing up Online Social Networks, Reza Rejaie, Mojtaba Torkjazi, Masoud Valafar, Walter Willinger, IEEE Network, Special Issue on Online Social Networks, October 2010

PRIME: Peer-to-Peer Receiver-drIven MEsh-based Streaming, Nazanin Magharei, Reza Rejaie, IEEE/ACM Transactions on Networking, August 2009

On Unbiased Sampling for Unstructured Peer-to-Peer Networks, Daniel Stutzbach, Reza Rejaie, Nick Duffield, Subhabrata Sen, Walter Willinger, IEEE/ACM Transactions on Networking, April 2009

Visit http://onrg.cs.uoregon.edu/public.html for the complete list of publications


http://onrg.cs.uoregon.edu/public.html

http://onrg.cs.uoregon.edu/public.html

Kevin Butler, Assistant Professor Ph.D., Penn State (2010) NSF CAREER Award (2013) Research interests

Storage and embedded systems security, privacy in mobile devices, cloud computing and web security, telecommunications and Internet security, secure data provenance and information flow control

Founder and Director of Oregon Systems Infrastructure Research and Information Security (OSIRIS) Lab

http://osiris.cs.uoregon.edu Email: [email protected]


http://osiris.cs.uoregon.edu/

http://osiris.cs.uoregon.edu/


Host Identification How do we protect storage devices against

potentially malicious hosts? Kells system (ACSAC 2010)

Shows how we can protect USB flash drives using trusted hardware of hosts

What if those hosts don’t have trusted hardware? Can we identify machines based strictly on USB?

Answer: yes! (NDSS 2014) Using machine learning classification algorithms and

corpus of 260 machines, showed ability to uniquely identify model, OS, use of virtualization


Mobile Privacy Consider two parties wanting to jointly compute a

function without either revealing their input to the other party - how can this be done?

Easy way: use a third party as arbiter

What if there’s no third party? Is this still possible?

Yes! Secure two-party computation: cryptographically complex and difficult, but we show it’s possible to do on mobile phones (USENIX Security 2013)



Selected publications Adam Bates, Benjamin Mood, Joe Pletcher, Hannah Pruse, Masoud Valafar, and Kevin

Butler. On Detecting Co-resident Cloud Instances Using Network Flow WatermarkingTechniques. International Journal of Information Security, 2013.

Thomas Moyer, Kevin Butler, Joshua Schiffman, Patrick McDaniel, and Trent Jaeger. Scalable Web Content Attestation. IEEE Transactions on Computers. 2011.

Adam Bates, Ryan Leonard, Hannah Pruse, Daniel Lowd, and Kevin Butler. Leveraging USB to Establish Host Identity Using Commodity Devices . NDSS, 2014.

Henry Carter, Benjamin Mood, Patrick Traynor, and Kevin Butler. Secure Outsourced Garbled Circuit Evaluation for Mobile Devices 22nd USENIX Security Symposium (Security'13), August 2013.

Benjamin Kreuter, ahbi shelat, Benjamin Mood, and Kevin Butler. PCF: A Portable Circuit Format For Scalable Two-Party Secure Computation. 22nd USENIX Security Symposium August 2013.

Devin J. Pohly, Stephen McLaughlin, Patrick McDaniel, and Kevin Butler. Hi-Fi: Collecting High-Fidelity Whole-System Provenance. ACSAC 2012.

Adam Bates, Kevin Butler, Micah Sherr, Clay Shields, Patrick Traynor, and Dan Wallach. Accountable Wiretapping -or- I Know They Can Hear You Now. NDSS 2012.

Machigar Ongtang, Kevin Butler, and Patrick McDaniel. Porscha: Policy Oriented Secure Content Handling in Android. ACSAC 2010.

http://ix.cs.uoregon.edu/~butler/pubs/ijis13.pdf






http://ix.cs.uoregon.edu/~butler/pubs/spork.pdf

http://ix.cs.uoregon.edu/~butler/pubs/acsac12b.pdf

http://ix.cs.uoregon.edu/~butler/pubs/ndss12.pdf

http://ix.cs.uoregon.edu/~butler/pubs/acsac10b.pdf

Hank Childs, Assistant Professor Ph.D., UC Davis (2006) Research interests

❍ Scientific visualization, high-performance computing, visualization of large data sets, Big Data, computer graphics

Awards:❍ Department of Energy Career Award for “Data Exploration

at the Exascale”❍ R&D 100 Award for VisIt visualization tool

CDUX: Computing and Data Understanding at Extreme Scale




Current Research Projects Data Exploration at the Exascale

❍ How can we compress scientific data for meaningful analysis afterwards, all within an exascale environment?

A Comprehensive Ray Tracing Framework for Visualization in Distributed-Memory Parallel Environments❍ Have architectural trends on supercomputers shifted enough for

ray-tracing to replace traditional rasterization-based graphics? Scalable Data Management, Analysis, and Visualization

Institute (SDAV)❍ One of 14 partners in $25M Institute on supporting leading

edge supercomputers ( http://www.sdav-scidac.org )


http://www.sdav-scidac.org/

Daniel Lowd, Assistant Professor Ph.D., University of Washington (2010) Research interests

❍ Learning statistical relational models forgraph/network data

❍ Adversarially robust machine learning❍ Learning tractable probabilistic models




Statistical Relational Machine Learning

No No

No

No Yes

No Yes

Example: Which pages are relevant?

Applications: Social network analysis, protein localization, entity resolution,information integration, and many more!

Weight of formula i No. of true groundings of formula i in x

iii xnw

ZxP )(exp

1)(

Markov logic turns a first-order knowledge base into a probability distribution by adding weights:

Linked(x,y) (Relevant(x) Relevant(y))Word(x, “UO”) Relevant(x)Word(x, “CIS”) Relevant(x)

1.2

0.80.5


42

Scenario: Adversary knows our classifier and can maliciously modify data to attack.

Applications: Email spam filtering, malware detection, online auction fraud, intrusion detection, link spam, blog spam, etc.

Goal: Select the best classifier, assuming the worst adversarial manipulation. (Zero-sum Stackelberg game.)

Adversarially Robust Machine Learning



Selected Publications D. Lowd and J. Davis, “Improving Markov Network Structure Learning Using Decision Trees,” Journal

of Machine Learning Research (JMLR), to appear, 2014. D. Lowd and A. Rooshenas, “Learning Markov Networks with Arithmetic Circuits,” 16th International

Conference on Artificial Intelligence and Statistics (AISTATS), 2013. M. Torkamani and D. Lowd, “Convex Adversarial Collective Classification,” 30th International

Conference on Machine Learning (ICML), 2013. S. Jiang, D. Lowd, and D. Dou, “Learning to Refine an Automatically Extracted Knowledge Base using

Markov Logic,” IEEE International Conference on Data Mining (ICDM), 2012. D. Lowd, “Closed-Form Learning of Markov Networks from Dependency Networks,” 28th Conference

on Uncertainty in Artificial Intelligence (UAI), 2012. D. Lowd and A. Shamaei, “Mean Field Inference in Dependency Networks: An Empirical Study,” 25th

Conference on Artificial Intelligence (AAAI), 2011. D. Lowd and P. Domingos, “Approximate Inference by Compilation to Arithmetic Circuits,” Advances in

Neural Information Processing Systems (NIPS) 23, 2010. S. Natarajan, T. Khot, D. Lowd, K. Kersting, P. Tadepalli and J. Shavlik, “Exploiting Causal

Independence in Markov Logic Networks: Combining Undirected and Directed Models,” European Conference on Machine Learning (ECML), 2010.

P. Domingos, D. Lowd, S. Kok, H. Poon, M. Richardson, and P. Singla, “Markov Logic: A Language and Algorithms for Link Mining,” in P. Yu, C. Faloutsos, and J. Han (eds.), Link Mining: Models, Algorithms and Applications. New York: Springer, 2010.

P. Domingos and D. Lowd, “Markov Logic: An Interface Layer for Artificial Intelligence,” San Rafael, CA: Morgan & Claypool, 2009.

Boyana Norris, Assistant Professor

Ph.D., University of Illinois, Urbana-Champaign (2000)

Automated HPC software analysis and transformation❍ For performance analysis and optimization (PBound)❍ For improving software design

Optimization of human and application performance ❍ Embeddable domain-specific languages for performance

portability and productivity; source transformation and autotuning:

http://brnorris03.github.io/Orio/

❍ Software taxonomies, adaptive algorithms and softwarehttps://code.google.com/p/lighthouse-taxonomy/

http://ix.cs.uoregon.edu/~norris Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013 44

http://brnorris03.github.io/Orio/

https://code.google.com/p/lighthouse-taxonomy/

https://code.google.com/p/lighthouse-taxonomy/

http://ix.cs.uoregon.edu/~norris

http://ix.cs.uoregon.edu/~norris


Orio Autotuning Framework

OpenCL

For More Information about Graduate Program

Websitehttp://www.cs.uoregon.edu

Graduate Student CoordinatorCheri Smith, [email protected]

Ph.D. program application❍ Deadline is January 15, 2014

http://www.cs.uoregon.edu/Education/Graduate_Admissions.php Contact information

Department of Computer and Information Science

University of Oregon

1202 University of Oregon

Eugene, Oregon 97403-1202

1-541-346-4408 (Phone) / 1-541-346-5373 (FAX)Ph.D. Graduate Student Recruiting, Beihang University, December 10, 2013 46

http://www.cs.uoregon.edu/


http://www.cs.uoregon.edu/Education/Graduate_Admissions.php

http://www.cs.uoregon.edu/Education/Graduate_Admissions.php


Go Ducks!

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