Belén Carolina Saldías Fuentes
Cambridge, MA, USA | firstname.lastname@example.org
belencarolina.com | github.com/bcsaldias
Massachusetts Institute of Technology (MIT) – Cambridge, MA, USA
Ph.D. Candidate. GPA 5.0/5.0 September 2018 - present
- Research topic: machine learning and child-centered artificial intelligence | Advisor: Prof. Deb Roy.
- Relevant classes: Advances in Computer Vision by B. Freeman, A. Torralba, and P. Isola; Affective Computing by RW Picard; Machine Learning for Natural Language by Sasha Rush at Harvard University.
Pontificia Universidad Católica de Chile (PUC) – Santiago, Chile
M.S. Machine Learning. GPA 6.72/7.0. August 2016 – August 2017
B.S. Industrial Engineering Information Technology. GPA: 6.04/7.0. March 2012 – August 2017
- Graduated with maximum distinction and ranked top 1% for both degrees.
- Co-founded and led Plan Deportivo Ingeniería (2013) to create, promote, and develop soccer, basketball, and volleyball teams in the school. Attracted around 500 students every semester.
- Awards and recognitions include:
- Best Computer Science Thesis Award (2017).
- Recipient of Academic Excellence Scholarship (2016).
- Top National Score in Mathematics, Ministry of Education of Chile, University Admission (2012).
- Recipient of Honor Scholarship (2012).
* Note that Engineering School (undergrad-only) officially lasts for 11-12 semesters in Chile.
RESEARCH AND PROFESSIONAL EXPERIENCE
Massachusetts Institute of Technology – Cambridge, MA, USA
Ph.D. Research Assistant, MIT Media Lab, Lab for Social Machines September 2018 - present
- Developing and deploying community-aware machine learning models and systems.
- Deployed a randomized controlled experiment to help increase Twitter users' emotional awareness.
- Deployed an in-the-wild pilot study over four months with middle-schoolers attending a high-poverty school in Boston, US, largely serving Black and Hispanic students to explore how a technology-mediated program might help bridge mentorship gaps. I contributed with all aspects of this project and led the tech side; a conversational agent developed to serve as a "mentor's helper" (paper under review).
- Developed an approach to understand how different attention types relate to different types of questions in Visual Question Answering (VQA). repo.
Falabella Retail S.A. – Santiago, Chile
Data Scientist and Corporate Web Intelligence Engineer September 2017 – June 2018
- First data scientist at Falabella.com. Worked with cross-functional teams, including business managers and software developers, to better understand user behavior and enhance user experience and the performance of the search engine.
- Recruited and interviewed data scientists for the company. It included various profiles: data wranglers, engineers, scientists with mathematical and algorithmic mindsets, and data science team leaders.
- Lead a data scientists’ team to outperform the user experience and findability at Falabella.com from a machine learning perspective. Analyzed customer behavior by analyzing more than 100 GB of e-commerce navigation data; results fed into better organization and prioritization of product mix. The CEO officially acknowledged our team due to the produced increase in the conversion rate of the e-commerce site.
- More details and a LinkedIn recommendation at: https://belencarolina.com/industry.
Machine Learning Intern August 2016 – December 2016
- Full-stack development of the first in-house recommender system. As I was the first person to propose such a project, my manager and the CEO gave me full flexibility to explore and innovate within Falabella. These five months were instrumental for the company to grow in machine learning capacities.
Harvard University – Cambridge, MA, USA
Research Assistant March 2016 – August 2017
- Developed my master’s thesis, as a paid RA at the Institute of Applied Computational Science (IACS), focused on machine learning, specifically on approximate variational inference for crowdsourcing labels.
- Member of the Harvard-Chile Data Science School, advised by Prof. Pavlos Protopapas, Scientific Program Director at IACS.
- Recipient of IACS financial aid to pursue my research (stipend and flight tickets).
Freelancer Consultant, Customer Intelligence October 2016 – July 2017
- Developed optimized data preprocessing and models through tens of GB of data.
- Defined a set of quick-win promotions to find the relationship between brands and type of products.
- Classified clusters of customers according to their buying behavior to give personalized service.
Massachusetts Institute of Technology – Cambridge, MA, USA
Member of the Kaufman Teaching Certificate Program to improve my teaching practice (ongoing during Fall 2020).
Ph.D. Teaching Assistant at the MIT Media Lab Fall 2020
- Serving as Chief TA for Understanding Public Thought, which is jointly offered at UW-Madison and MIT.
- Our goal is to design and advance strategies for measuring public opinion, paying particular attention to the need to understand perspectives as well as gauge preferences. website.
Ph.D. Teaching Assistant at the Department of Electrical Engineering and Computer Science Fall 2019
- Served as grad TA for graduate (6.862) machine learning and undergraduate (6.036).
- Guiding grad students in their applied machine learning projects and developing material for new problem sets related to deep learning. Worked under professors L. Kaelbling, T. Broderick, D. Boning, and P. Jaillet, J. Andreas, among others.
Pontificia Universidad Católica de Chile – Santiago, Chile
Adjunct Professor of Data Mining August 2017 – December 2017
- Youngest professor in the Computer Science Department of the School of Engineering.
- Only professor teaching Data Mining, an elective class for 4th- and 6th-year university students and a required class for Data Science minors and graduate (master and PhD) students doing Machine Learning research.
- Designed curriculum, created lectures, assessments, and feedback process for an audience of 30 students (doubled class attendance from previous years). Managing 4 teaching assistants.
- Award: Recipient of the Exceptional Quality as Lecturer and Maximum Student Satisfaction (2018).
Adjunct Professor of Data Mining and Management March 2018 – July 2018
- Designed curriculum, lectures, assessments, and feedback process for a master's class of 50 students.
- Obtained maximum student satisfaction in both scientific and practical knowledge acquired.
- I have offered versions of this class a few times since then, including lectures to peers and managers at Falabella and as an invited lecturer to PUC classes at the CS department.
Adjunct Professor of Advanced Programming March 2018 – July 2018
- Designed curriculum, lectures, assessments, and feedback process for an audience of 50 students.
- Core CS class for 2th- and 6th-year university students.
Teaching Assistant at the Computer Science Department 2013 - 2017
- Served as Chief Teaching Assistant for 8 computer science and engineering classes (2013 – 2017), including Advanced Programming, Stochastic Models, Bayesian Inference, Data Structure and Algorithms, among others.
- Managed teams of 3-30 teaching assistants (academic and administrative management).
- Award: Recipient of the Exceptional Quality as Teaching Assistant Award (2015).
- Saldias, B., & Roy, D. (2020, July) Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types. Proceedings of the 2020 ACL Workshop on Narrative Understanding, Storylines, and Events (NUSE). ACL. paper. video. repo.
- Saldias, B., & Picard, R. (2019, September). Tweet Moodifier: Towards Giving Emotional Awareness to Twitter Users. Proceedings of the 2019 International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE. paper. media.
- Saldias, B., Protopapas, P., & Pichara, K. (2019, May). A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. Proceedings of the 2019 SIAM International Conference on Data Mining (SDM) (pp. 756-764). SIAM. paper.
- Bhargava, R.*, Chung, A., Gaikwad, N., Hope, A., Jen, D., Rubinovitz, J., Saldias, B.*, & Zuckerman, E. (2019, November). Gobo: A System for Exploring User Control of Invisible Algorithms in Social Media. Submitted to the 2019 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW). ACM. *All authors contributed equally to this research. paper.
- Saldías, Belén. (2017, August) A full probabilistic model for yes/no type crowdsourcing in multi-class classification. Santiago, Chile: Pontificia Universidad Católica de Chile. (master’s thesis). paper. repo. Advisors: Prof. Karim Pichara (PUC, Chile), and Prof. Pavlos Protopapas (Harvard, USA).
- Gillani, N.*, Saldias, B.*, Makini, S.*, Hughes, M.*, & Roy, D.* (2021) Exploring a Human-Bot Partnership to Bridge Childhood Mentorship Gaps through Personal Narratives. web page. * indicates contributions of equal importance.
OTHER ACADEMIC AND RELATED VENUES
- Leader at workshop sessions:
- Saldias, B., & Ali, S. (2020, July). Abstract: Towards Children-Aware Machine Learning with a Focus on NLP Challenges and Applications. 1st WiML Un-Workshop co-located with ICML. repo.
- Saldias, B., & Roy, D. (2020, July) Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types. WiML at ICML.
- Saldias, B., & Roy, D. (2019, December). Understanding story similarity for personal narratives. 14th Women in Machine Learning (WiML) Workshop co-located with NeurIPS. Vancouver, British Columbia, Canada. Awarded a travel grant, to attend the workshop, by WiML.
- Pichara, K., & Pieringer, C., (2017). Advanced Computer Programming in Python.
I served as the main contributor of this published book as I was in charge of developing and testing the code exercises and examples in the book.
Freely available at https://advancedpythonprogramming.github.io (also in Amazon).
LEADERSHIP AND SERVICE
- Current Executive Council Co-Chair, MIT Sidney Pacific Graduate Community, 2020-2021. MIT Sidney Pacific homes nearly 700 graduate students from many corners of the world.
- Service to the academic community includes:
- Co-Chair for the 15th Workshop for Women in Machine Learning (WiML) at NeurIPS 2020.
- Super-volunteer for the 1st WiML Un-Workshop at ICML, 2020.
- Reviewer for the ICML Deploy and Monitor ML workshop, 2020.
- Reviewer for the 14th NeurIPS WiML workshop, 2019.
- Invited lectures and presentations include:
- Research in Machine Learning at PUC CS/DCC Chile, PhD Seminar, October 2020.
- Speaker, Data Science in Industry at U. of Concepción, Chile, August 2020.
- Various lectures and research presentations at PUC Chile, 2019.
- Paper presentation, Affective Computing class by Prof. Roz Picard, MIT, Spring 2019.
- Mitigating Bias in Analytics (2020, August). Hosted by Women in Analytics and Tableau video.
- Women in Data Science (2018, March). Santiago, Chile. Spoke to how to push data science and machine learning in the Chilean industry. website.
- “Six women leave footprints in Boston, one of the most important tech hubs in the world.” El Mercurio, Chile, 2020. Featured in El Mercurio's cover and in the Innovation section's cover. El Mercurio is considered Chile's newspaper of record, and it is considered the oldest daily in the Spanish language currently in circulation. pdf.
- “This is how emotions spread on Twitter.” El País, España. Article based on Saldias, B., & Picard, R. (2019, September). El País is a Spanish-language daily newspaper in Spain. According to the Office of Justification of Dissemination, it is the second most circulated daily newspaper in Spain as of December 2017. link.
- “Research in Spanish at the MIT Media Lab.” La Razón, España. Article highlighting spanish-speaking researchers at the MIT Media Lab. La Razón is a daily newspaper based in Madrid, Spain. It has the sixth-highest circulation among general-interest Spanish dailies. link.
- Languages: Spanish (native speaker), English (full professional working proficiency).