Ab Mosca
(they\them\theirs)
I'm a fifth year PhD candidate working with Remco Chang in the Visual Analytics Lab at Tufts ([v]alt). I graduated from Smith College in 2014 with a B.A. in Mathematics, and then worked at Mathematica Policy Research as a Data Associate. Working at Mathematica sparked my interest in visualization as a way to promote data-driven decision making in policy.
Research Interest
My research interest lies in supporting visual reasoning with data at different abstraction levels. Specifically, I take a human-centered approach to identifying how visualizations can leverage perception and cognition to better support reasoning. By better understanding these nuances we can build better visualizations for a wider range of users and enable more people to harness the power of data-driven decision making.
Education
PhD in Computer Science (in progress)
Tufts University, Medford, MA
Expected August 2021
Advisor: Remco Chang
MSc in Computer Science
Tufts University, Medford, MA
May 2019
Advisor: Remco Chang
BA in Mathematics, magna cum laude
Smith College, Northampton, MA
May 2014
Awards/Honors
Tufts School of Engineering Outstanding Graduate Contributor to Engineering Education Award, 2021
Smith College Pokora Senior Scholar Athlete, 2014
Phi Beta Kappa, 2013
Teaching Experience
Co-instructor, Visualization Seminar
Tufts University
Fall 2020
Co-instructor, Directed Study in Visual Analytics
Tufts University
Spring 2020
Guest Lecture, Visual Analytics
Tufts University
Fall 2019
Instructor, Pre-Align Math Intro
Northeastern University
Summer 2019
Teaching Assistant, Graphics
Tufts University
Spring 2019
Undergraduate Research Coordinator, VALT
Tufts University
Summer 2017
Head Teaching Assistant, Discrete Mathematics
Tufts University
Fall 2016, Spring 2017
Undergraduate Teaching Assistant, Modeling in the Sciences
Smith College
Spring 2014
Quantitative Tutor, Spinelli Center for Quantitative Learning
Smith College
Fall 2013, Spring 2014
Peer Tutor, Pre-Calculus, Calculus I, Calculus II, Calculus III, Discrete Mathematics, Linear Algebra
Smith College
Spring 2012, Fall 2012, Spring 2013, Fall 2013, Spring 2014
Mentoring Experience
Alice Dempsey, Tufts 2021
Fall 2020 – Present
VALT Undergraduate Researcher
Andrew Wang, Tufts 2021
Fall 2020 – Present
VALT Undergraduate Researcher
Helen Li, Tufts 2023
Fall 2020 – Present
VALT Undergraduate Researcher
Kate Hanson, Tufts 2021
Fall 2019 –Present
VALT Undergraduate Researcher
Tania Valrani, Tufts MS 2021
Spring 2020
Master’s Student Directed Study
Sammy Stolzenbach, Tufts 2020
Summer 2019 –Spring 2020
VALT Undergraduate Researcher
Currently: Data Analyst at New York Times
Sebastian Coates, Tufts 2020
Fall 2017 –Spring 2018
VALT Undergraduate Researcher
Currently: Co-founder at Immuto
Meredith Clarke, Tufts 2019
Summer 2017 –Spring 2018
VALT Undergraduate Researcher
Currently: Analyst at Education Resource Strategies
Rebecca Redelmeier, Tufts 2019
Summer 2017 –Spring 2018
VALT Undergraduate Researcher
Currently: Audience Engagement Associate at Committee to Protect Journalists
Julia Romero, University of Texas at Austin 2020
Summer 2017
REU Student
Currently: PhD Student in Computer Science at University of Colorado at Boulder
Papers
A. Mosca, A. Ottley and R. Chang. Does Interaction Improve Bayesian Reasoning with Visualization?. ACM CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 2021. (PDF, DOI)
M. Procopio, A. Mosca, C. Scheidegger, E. Wu and R. Chang. Impact of Cognitive Biases on Progressive Visualization. IEEE Transactions on Visualization and Computer Graphics, 2021. (PDF, DOI)
A. Mosca, S. Robinson, M. Clarke, R. Redelmeier, S. Coates, D. Cashman, and R. Chang. Defining an Analysis: A Study of Client-Facing Data Scientists. EuroVis 2019 - Short Papers, 2019. (PDF, DOI)
D. Cashman, S. R. Humayoun, F. Heimerl, K. Park, S. Das, J. R. Thompson, B. Saket, A. Mosca, J. Stasko, A. Endert, M. Gleicher, and R. Chang. A User-based Visual Analytics Workflow for Exploratory Model Analysis. Computer Graphics Forum, 2019. (PDF, DOI)
G. Ryan, A. Mosca, R. Chang, and E. Wu. At a Glance: Pixel Approximate Entropy as a Measure of Line Chart Complexity. IEEE Transactions on Visualization and Computer Graphics, 2018. (PDF, DOI)
D. Cashman, G. Patterson, A. Mosca, N. Watts, S. Robinson, R. Chang. RNNbow: Visualizing Learning via Backpropagation Gradients in RNNs. IEEE Computer Graphics and Applications, 2018. (PDF, DOI)
R. S. Lester, C. V. Irvin, A. Mosca, &C. Bradnan (2015). Tipping the Balance: The Balancing Incentive Program and State Progress on Rebalancing Their Long-Term Services and Supports. Medicaid.gov. (PDF)
A. Mosca, & N.D. Teitelbaum (2015). Pancreas. In Brehm, B.A. (ed.), Nutrition: Science, Issues, and Applications. Santa Barbara, CA: Greenwood Press.
A. Mosca (2015). Microbiota and Microbiome. In Brehm, B.A. (ed.), Nutrition: Science, Issues, and Applications. Santa Barbara, CA: Greenwood Press.
A. Mosca (2015). Polyphenols. In Brehm, B.A. (ed.), Nutrition: Science, Issues, and Applications. Santa Barbara, CA: Greenwood Press.
Papers in Submission and Preparation
A. Suh, A. Mosca, D. Cashman, Q. Pham, S. Robinson, A. Ottley, & R. Chang. Inferential Tasks as an Evaluation Technique for Visualization. (In submission, VIS 2021)
N. Lopatina, A. Mosca, and A. Brennen. How Good is your Machine Translation? Design and Evaluation of a Quality Estimation System. (In submission, ACL Demo Papers 2021)
Workshops
A. Mosca, A. Ottley, and R. Chang. Does Interaction Improve Bayesian Reasoning with Visualization? In IEEE Visualization Workshop on Visualization for Communication (VisComm), 2020. (PDF)
D. Cashman, G. Patterson, A. Mosca, and R. Chang. RNNbow: Visualizing the Learning Process in Recurrent Neaural Networks. In IEEE Visualization Workshop on Visual Analytics for Deep Learning (VADL), 2017.
Posters
A. Mosca, Sh. Robinson, M. Clarke, R. Redelmeier, S. Coates, D. Cashman, and R. Chang. Towards Data Science for the Masses: A Study of Data Scientists and Their Interactions with Clients. Poster, IEEE Conference on Information Visualization (InfoVis), 2018.
G. Ryan, A. Mosca, R. Chang, and E. Wu. Approximate Entropy as a Measure of Line Chart Complexity. Poster, IEEE Conference on Information Visualization (InfoVis), 2017.
Reviewing Activities
ACM CHI Conference on Human Factors in Computing Systems (CHI), 2021
International Journal of Human - Computer Studies (IJHCS), 2020
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020
IEEE Conference on Information Visualization (InfoVis), 2019 - 2020
IEEE Conference on Visual Analytics Science and Technology (VAST), 2019 - 2020
Eurographics and IEEE Visualization and Graphics Technical Committee Conference on Visualization (EuroVis), 2019
Workshop Organization
IEEE VIS Machine Learning from User Interactions for Visualization and Analytics (MLUI), 2020 Organizer
TRIPODS - HDR Workshop, 2020 Organizer
Work Experience
Research Assistant, Visual Analytics Lab at Tufts
May 2017 - Present
- Funded graduate research assistant for the Walmart Foundation funded Nudging Online Shoppers to Healthier Meals project (OAC-1940175, OAC-1939945, IIS-1452977, DGE-1855886)
- Tufts' graduate research coordinator for the NSF HDR funded: GenoPhenoEnvo project (1939945, 1940059, 1940062, and 1940330)
- Funded graduate research assistant for DARPA D3M: User-Driven Model Steering and Curation via Inference from Interaction and Model-Space Sampling project (FA8750-17-2-0107)
Intern, IQT Labs
June 2020 - August 2020, Waltham, MA
- Designed, built, and executed a user evaluation of IQT Labs' VeriCAT system. VeriCAT is an Explainable AI (XAI) system that aims to help users understand the limitations of machine translation (MT)
- Analyzed and presented results of the VeriCAT user evaluation to senior leaders of IQT to inform next steps for XAI research. Specifically, the idea that user evaluations can inform not only user interface design, but also AI model features
Instructor, Northeastern University
August 2019, Boston, MA
- Designed curriculum for Pre-Align Math Introduction course offered to incoming Align students at Northeastern University. The goal of the course was to build math confidence for incoming students many of who are from underrepresented minorities in computer science, and/or enter the program from a field other than computer science
- Delivered lectures and practice problems on high school and introductory-college level material including binary numbers, modulo, logarithms, exponents, word problems, introductory proof techniques, polynomials, functions, and combinatorics
- Managed 5 teaching assistants
Insight Center Intern, National Renewable Energy Lab
June 2018 - August 2018, Golden, CO
- Built framework of an interactive geospatial visualization that illustrates the economic impacts of wind turbine research and development across the contiguous United States under the guidance of Kristi Potter
Data Associate, Mathematica Policy Research
June 2014 - July 2016, Cambridge, MA
- Developed, maintained, and executed programs to assess quality of Medicare and Medicaid data, to automate repetitive administrative tasks, and to perform statistical analyses for research studies
- Assisted building novel dashboard reporting systems utilized by Accountable Care Organizations and Medicaid offices to inform decisions (demo)
- Managed spending, staffing, and data access on tightly budgeted multi-year government contracts for research projects with sensitive private data
- Mentored junior staff, and aided in the development of training tools and programs
Student Researcher, National Science Foundation Research Experience for Undergraduates
June 2013 - August 2013, Potsdam, NY
- Performed an in-depth analysis of geometry of, and integration on, the Cantor Set in collaboration with other undergraduates under the supervision of Dr. Klawitter, who presented our results at the 2013 Peterson Conference at the University of Nebraska. In addition, findings were presented at the poster session of the 2014 Joint Mathematics Meetings in Baltimore, MD
Professional Memberships
Association for Computing Machinery (ACM)
IEEE Computer Society
American Statistical Association (ASA)
Leadership Positions
President, ACM-W Student Chapter - Tufts University
Spring 2017 - Spring 2019
Member, Tufts Computer Science Student Council
Spring 2018 - Spring 2019
First Year and Masters Representative, Tufts Computer Science Student Council
Spring 2017 - Spring 2018
Captain, Smith College Track and Field
Spring 2013 - Spring 2014
Captain, Smith College Cross Country
Fall 2012 - Fall 2013
When I'm not working some of my favorite things are:
Running--I did four years of cross country and indoor and outdoor track at Smith.
Now I dabble in trail running,
biking,
hiking,
and cooking over a campfire.
