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News

  • Graduate Research Funding Opportunity: 
    • We are seeking graduate students to join an AI branch of our DHS-funded QuASAR project. The AI component of this project deals with novel algorithms and applications of machine learning methods to real-world cyber threat data. We are seeking 1 graduate student to work on data aggregation, literature reviews, experimental design, data analysis, and machine learning-focused research. Students interested in graph algorithms, data mining, machine learning, transfer learning, and anomaly detection are encouraged to apply. Selected students will be funded with either a research assistantship or hourly pay with a possibility of renewal after the first year’s performance. Must be a U.S. citizen to apply.
       
      To apply, please send an email to both veronika.neeley@montana.edu and daveopitz@msn.com with subject header “QuASAR GRA Application” along with a C.V. and a short statement (1-2 paragraphs) that describes your background and interest in this project. Finalists will be contacted for interviews.
  • I have written my first Medium article on my experiences as a mother in academia, especially as this topic relates to breastfeeding. 
  • If you are interested in working with me, please send me an email after you have applied to the Ph.D. program at Montana State University. If you are an MSU student interested in working with me, I'd be happy to meet you via videochat -- please email me to set up a time. I am seeking good students with background in math, computer science, and/or statistics, who are interested in the following topics:
    • Random forests
    • Clustering
    • Anomaly detection
    • Recommender systems

           Members of historically underrepresented groups in computer science are especially encouraged to apply!

Research

Broadly, I am interested in scalable anomaly detection, clustering algorithms, random forests, dimensionality reduction and graph algorithms. Recently, I have been working on graph anomaly detection for cyber security and tree-based methods for nonlinear manifold learning in large data sets.

Publications

Characterizing Online Discussions in Microblogs Using Network Analysis. Veronika Strnadova, David Jurgens, Tsai-Ching Lu. In Proceedings of AAAI Spring Symposium Series. (2013)

Efficient and Accurate Clustering for Large-Scale Genetic Mapping. Veronika Strnadova, Aydin Buluc, Jarrod Chapman, John R. Gilbert, Joseph Gonzalez, Stefanie Jegelka, Daniel Rokhsar, Leonid Oliker . Technical Report UCSB-CS-2013-10, UCSB CS Department, November 2013

Efficient and Accurate Clustering for Large-Scale Genetic Mapping. Veronika Strnadova, Aydin Buluc, Jarrod Chapman, John R. Gilbert, Joseph Gonzalez, Stefanie Jegelka, Daniel Rokhsar, Leonid Oliker . In The IEEE International Conference on Bioinformatics and Biomedicine (BIBM'14). Regular paper (19% acceptance). 2014

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome. Jarrod A. Chapman, Martin Mascher, Aydin Buluc, Kerrie Barry, Evangelos Georganas, Adam Session, Veronika Strnadova, Jerry Jenkins, Sunish Sehgal, Leonid Oliker, Jeremy Schmutz, Katherine A. Yelick, Uwe Scholz, Robbie Waugh, Jesse A. Poland, Gary J. Muehlbauer, Nils Stein, Daniel Rokhsar. In Genome Biology, Vol. 16. 2015 

Efficient Data Reduction for Large-Scale Genetic Mapping. Veronika Strnadova-Neeley, Aydin Buluc, Jarrod Chapman, John R. Gilbert, Joseph Gonzalez, Leonid Oliker. In the 6th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB15). Regular paper. 2015

LiRa: A New Likelihood-Based Similarity Score for Collaborative Filtering. Veronika Strnadova-Neeley, Aydin Buluc, John R. Gilbert, Leonid Oliker, Weimin Ouyang. In the LSRS16 Workshop for RecSys16. 

Efficient Clustering for Large-Scale, Sparse, Discrete Data with Low Dimensional Intrinsic Structure. Veronika Strnadova-Neeley, supervised by John R. Gilbert. Regular presentation at the VLDB 2017 Ph.D. workshop. 

Improved Subspace K-Means Performance via a Randomized Matrix Decomposition. Trevor Vannoy, Jacob Senecal, Veronika Strnadová-Neeley. In IEEE GlobalSIP 2019.

Geodesic Forests. Meghana Madhyastha, Gongkai Li, Veronika Strnadova-Neeley, James Browne, Joshua T. Vogelstein, Randal Burns, Carey E. Priebe. In KDD2020.

Graduate Students

I am lucky to be working with the following graduate students:

  • Gillian Reynolds (IIP Program, Computer Science & Plant Sciences, co-advised by Jennifer Lachowiec)
  • Jacob Munson (IIP Program, Computer Science & Mathematical Sciences)
  • Gerard Shu Fuhnwi (Computer Science)
  • Daniel Laden (Computer Science)

Undergraduate Research

Undergraduate Research Projects

If you are a student at Montana State University and you are interested in working on undergraduate research with me, please send me an email. In the email, breifly describe your background in computer science, math and statistics, why you would like to work on a project with me, and if you have any ideas for a potential research project (it's ok if you don't).

REU Mentorship

I mentored two students in the 2019 Summer Research Experience for Undergraduates (REU) program and one student in the 2020 Summer Research Experience for Undergraduates in the Computer Science Department at Montana State University. I am currently mentoring two students in the 2021 Summer Research Experience for Undegraduates at MSU.

Education

Ph.D. in Computer Science from the University of California, Santa Barbara, with a Computational Science Emphasis

  • My thesis was on efficient clustering methods for large-scale, discrete-valued data with many missing values, and includes applications to both bioinformatics and recommender systems. At UCSB, I was a member of the CSC Lab, with adviser John R. Gilbert, and I completed my degree with a CSE Emphasis.

M.S. in Computer Science from the University of California, Santa Barbara, with a Computational Science Emphasis

B.S. in Applied Mathematics from the University of New Mexico, summa cum laude

Teaching

CSCI 347: Introduction to Data Mining (Spring 2021, online)

CSCI 594: Graduate Seminar: Clustering Techniques (Fall 2020, online)

CSCI 347: Introduction to Data Mining (Spring 2020, partly online)

CSCI 246: Discrete Structures (Fall 2019)

(on Faculty Modified Duties in Spring 2019)

CSCI 550: Data Mining (Fall 2018)

As a graduate student UC Santa Barbara, I taught two classes:

  • CS140: Parallel Scientific Computing (Winter 2018)
  • CS8: Introduction to Computer Science (Summer 2015)

Outreach and Service

Cultural Competence in Computing (3C) Fellow (September 2020 - present)

Northwest Regional App Challenge Judge (May 2019)

  • Short article about the challenge

Rocky Mountain Celebration of Women in Computing BOF Session Organizer (2018)

  • BOF Session Title: 

    Defining the Data Science, Data Mining, Machine Learning, and Related Curricula: Towards a Standardization of Educational Goals in Data Science-Related Fields

Faculty Co-Advisor for AWC (2018-present)

  • News: (October 2018) We have started a new group for graduate women in computer science! 

Committee Member, RecSys17 LSRS Workshop (2017)
Organizing Committee Member, Panel Host, Graduate Student Workshop in Computing (GSWC) at the UCSB CS Summit (March 2016) 2016 CS Summit web page
Reviewer for ACM IUI 2016 

President, CS Graduate Student Representatives (Fall 2015 - Fall 2016) 
Diversity Committee Graduate Student Representative (Fall 2015 - Fall 2016) 
UCSB CS Student Research Colloquium Organizing Committee (February 2015) Link to colloquium website
Undergraduate Affairs Committee Graduate Student Representative (UCSB, Fall 2014-Spring 2015) 
Reviewer for Transactions on Knowledge and Data Engineering 
GUIDES mentor (UCSB, Fall 2014 - Spring 2015) 
IGERT Network Science Associate (UCSB, Fall 2013 - Fall 2016) 

Women in Science and Engineering Mentorship Committee Member (2013-2014) 
Speaker, along with Saiph Savage at Goleta Valley Jr. High Career Day (Fall 2013) 
Organizing Committee Member, UCSB CS Career Day (Spring 2013) 
After-school tutor, Goleta Valley Jr. High (Spring 2013) 
Women in Computer Science Co-President (UCSB, 2012-2013) 
Speaker, along with Morgan Vigil at Goleta Valley Jr. High Career Day (Fall 2012)  
CRA-W Grad Cohort Workshop Participant (Spring 2012) 
Women in Computer Science Officer (UCSB, 2011-2012) 
Student-Athlete Mentor (UNM, Fall 2010) 

Awards and Accomplishments

CRA-W Early Career Mentoring Workshop selected participant (2018)

2018 Outstanding Graduate Student Award from the Computer Science Department at UCSB (2018)

M.I.T. EECS Rising Stars Workshop Selected Participant (November 2015) 

Google Anita Borg Memorial Scholarship Finalist (2012, 2013)

NCAA 1A FAR Academic Excellence Award (2011)

Contact Information

Office: Barnard Hall 351
Phone: +1 406.994.6102
Email: veronika.neeley@montana.edu