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Department of Computer and Information Science. Ph.D. Graduate Program. Where is the University of Oregon?. Eugene. Oregon. USA. What is Eugene, Oregon like?. Eugene Information. Small city! Population of 150,000 Young town! M edian age of 34 years Close to everything!

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where is the university of oregon
Where is the University of Oregon?

Eugene

Oregon

USA

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

what is eugene oregon like
What is Eugene, Oregon like?

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

eugene information
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!

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

what is the university of oregon like
What is the University of Oregon like?

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

university of oregon information
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)

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

department of computer and information science cis
Department of Computer and Information Science (CIS)

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

cis department information
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!

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

zena ariola professor
ZenaAriola, 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 information

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

sarah douglas professor emerita
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
    • Bioinformatics

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

allen d malony professor
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: malony@cs.uoregon.edu

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

tau project
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)

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

neuroinformatics center nic
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

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

selected publications
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. CurfmanMcInnes, 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.

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

andrzej proskurowski professor
Andrzej Proskurowski, Professor
  • TekniskDoktor, KTH (Royal Institute ofTechnology), 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: andrzej@cs.uoregon.edu

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

recent publications
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, AndrzejProskurowski, 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 AndrzejProskurowski, 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).

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

dejing dou associate professor
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: dou@cs.uoregon.edu

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

aim lab
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

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

semantic mining of activity social and health data
Semantic Mining of Activity, Social, and Health Data

SMASH Project

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

collaborators and students
Collaborators and Students
  • Ontology-based Information Extraction
    • Students: Fernando Gutierrez, Adam Martini, JavidEbrahimi
    • Steve Fickas (CIS, UO), Gina Griffiths (College of Education, UO), HuiZong (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), PaeaLePendu (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: NhatHaiPhan
    • 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

selected publications1
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 MehranMehergany, 2013.
  • YelongShen, 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

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

anthony hornof associate professor
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: hornof@cs.uoregon.edu

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

ph d student working with dr hornof
Ph.D. Student Working with Dr. Hornof
  • YunfengZhang, 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

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

prof hornof presenting award to yunfeng zhang
Prof. Hornof Presenting Award to Yunfeng Zhang

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

intership at palo alto research center
Intership at Palo Alto Research Center

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

jun li associate professor
Jun Li, Associate Professor
  • Ph.D., UCLA (2002)
  • Catedra de Excelencia (Chair of Excellence) at theCarlos 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: lijun@cs.uoregon.eduWechat: softlaser, Skype: softlaser2, QQ: 1494335605

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

recent projects
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

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

ongoing projects 1
Ongoing Projects (1)
  • Internet Routing & Security
    • Buddyguard: Fast and reliabledetection 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 serviceon the Internet
    • DrawBridge: Enhancing software-defined networking to throttle DDoS traffic
    • Internet traffic congestion avoidance on the fly

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

ongoing projects 2
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

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

reza rejaie associate professor
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

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

oregon network research group onrg
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

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

the impact project
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

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

selected publications2
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, NazaninMagharei, Reza Rejaie, IvicaRimac, Volker Hilt, Markus Hofmann, IEEE/ACM Transactions on Networking, January 2013
  • Unveiling the Incentives for Content Publishing in Popular BitTorrentPortals, 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, GhulamMemon, 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, MojtabaTorkjazi, MasoudValafar, Walter Willinger, IEEE Network, Special Issue on Online Social Networks, October 2010
  • PRIME: Peer-to-Peer Receiver-drIvenMEsh-based Streaming, NazaninMagharei, Reza Rejaie, IEEE/ACM Transactions on Networking, August 2009
  • On Unbiased Sampling for Unstructured Peer-to-Peer Networks, Daniel Stutzbach, Reza Rejaie, Nick Duffield, SubhabrataSen, Walter Willinger, IEEE/ACM Transactions on Networking, April 2009
  • Visit http://onrg.cs.uoregon.edu/public.html for the complete list of publications

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

kevin butler assistant professor
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: butler@cs.uoregon.edu

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

host identification
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

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

mobile privacy
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)

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

selected publications3
Selected publications
  • Adam Bates, Benjamin Mood, Joe Pletcher, Hannah Pruse, MasoudValafar, and Kevin Butler. On Detecting Co-resident Cloud Instances Using NetworkFlowWatermarkingTechniques. 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, ahbishelat, 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.
  • MachigarOngtang, Kevin Butler, and Patrick McDaniel. Porscha: Policy Oriented Secure Content Handling in Android. ACSAC 2010.

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

hank childs assistant professor
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
  • Email: hank@cs.uoregon.edu

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

current research projects
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 )

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

daniel lowd assistant professor
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
  • Email: lowd@cs.uoregon.edu

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

statistical relational machine learning
Statistical Relational Machine Learning

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

Example: Which pages are relevant?

No

No

1.20.8

0.5

Linked(x,y)  (Relevant(x) Relevant(y))Word(x, “UO”) Relevant(x)

Word(x, “CIS”) Relevant(x)

No

No

Yes

No

Yes

Weight of formula i

No. of true groundingsof formula iin x

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

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

adversarially robust machine learning
Adversarially Robust Machine Learning

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.)

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

selected publications4
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.

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

boyana norris assistant professor
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 software

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

  • http://ix.cs.uoregon.edu/~norris

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

orio autotuning framework
OrioAutotuning Framework

OpenCL

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

for more information about graduate program
For More Information about Graduate Program
  • Website

http://www.cs.uoregon.edu

  • Graduate Student Coordinator

Cheri Smith, cheri@cs.uoregon.edu

  • 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

go ducks
Go Ducks!

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