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.
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.
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
Tufts School of Engineering Outstanding Graduate Contributor to Engineering Education Award, 2021
Smith College Pokora Senior Scholar Athlete, 2014
Phi Beta Kappa, 2013
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
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
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.
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)
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.
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.
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
IEEE VIS Machine Learning from User Interactions for Visualization and Analytics (MLUI), 2020 Organizer
TRIPODS - HDR Workshop, 2020 Organizer
Research Assistant, Visual Analytics Lab at Tufts
May 2017 - Present
Intern, IQT Labs
June 2020 - August 2020, Waltham, MA
Instructor, Northeastern University
August 2019, Boston, MA
Insight Center Intern, National Renewable Energy Lab
June 2018 - August 2018, Golden, CO
Data Associate, Mathematica Policy Research
June 2014 - July 2016, Cambridge, MA
Student Researcher, National Science Foundation Research Experience for Undergraduates
June 2013 - August 2013, Potsdam, NY
Association for Computing Machinery (ACM)
IEEE Computer Society
American Statistical Association (ASA)
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
Email: amosca01 (at) cs (dot) tufts (dot) edu
Department of Computer Science
School of Engineering
Tufts University
161 College Avenue
Medford, MA 02155
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.