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MATTHEW BEJTLICH

Matthew (b. 1991) is a data scientist, information designer, electrical engineer, photographer, and musician who is interested in building communities that are more inclusive, circular, just, and resilient.
        He makes abstract, beat-driven electronic music as part of the audio-visual duo Dayspired and is a current partner at Rhythm Section International (London, UK), where he is being mentored by record label founder Bradley Zero (DJ at BBC Radio 1, NTS Radio, Boiler Room).
      Most recently, Matthew has pursued his MFA in Graphic Design at Rhode Island School of Design (RISD) after receiving his MS in Data Science from Brown University. He is a graduate researcher at Brown’s Human-Computer Interaction Lab, and the head teaching assistant for the class “Machine Learning and Design.” He is currently looking for engaging and rigorous full time data science, design, and systems engineering work (either remote or in-person) dealing with high-impact social or environmental problems.

Connect
Email, Resume, Music, Instagram, LinkedIn, GitHub

Client list
He has worked or collaborated with Google, Holition, Warren Alpert Medical School of Brown University, British Fashion Council, Brown University HCI Lab, and the Naval Undersea Warfare Center.

Education
Rhode Island School of Design
MFA Graphic Design, 2021

Brown University
MS Data Science, 2018

University of Massachusetts Dartmouth
BS Electrical Engineering, 2015



MATTHEW BEJTLICH

Matthew (b. 1991) is a data scientist, information designer, electrical engineer, photographer, and musician who is interested in building communities that are more inclusive, circular, just, and resilient.
        He makes abstract, beat-driven electronic music as part of the audio-visual duo Dayspired and is a current partner at Rhythm Section International (London, UK), where he is being mentored by record label founder Bradley Zero (DJ at BBC Radio 1, NTS Radio, Boiler Room).
      Most recently, Matthew has pursued his MFA in Graphic Design at Rhode Island School of Design (RISD) after receiving his MS in Data Science from Brown University. He is a graduate researcher at Brown’s Human-Computer Interaction Lab, and the head teaching assistant for the class “Machine Learning and Design.” He is currently looking for engaging and rigorous full time data science, design, and systems engineering work (either remote or in-person) dealing with high-impact social or environmental problems.

Connect
Email, Resume, Music, Instagram, LinkedIn, GitHub

Client list
He has worked or collaborated with Google, Holition, Warren Alpert Medical School of Brown University, British Fashion Council, Brown University HCI Lab, and the Naval Undersea Warfare Center.










 





SKETCHY

Sketchy is a web-based drawing application that allows users to sketch in virtual rooms and get ideas from viewing their peer’s sketches in real-time. In my contribution as a graduate research for the Brown University HCI Group, I conceptualized and constructed novel artistic features from 2D stroke data to help in building a personalized recommendation model in support of designers in their creative process. Reviewed paper for CHI 2020 conference. 

Date: 2020
Client: Brown University HCI Lab
Advisor: Jeff Huang, PhD & Shawn Wallace, MS
Data science, Human Computer Interaction


(︎︎︎Feature analysis)
(︎︎︎Summary)


LONDON FASHION WEEK S/S 2018  

Worked in collaboration with Google, Conde Nasté, and a select team of interns to create an art installation for the London Fashion Week Spring/Summer 2018 event. The algorithmic tree visualization shows the emerging conversations (e.g. sustainability, diversity, model health) in the London fashion industry over the course of the two week event.
       As the primary data scientist, I performed initial brand identity research, helped craft a compelling message that aligned with the core principles of British Fashion Council, identified and evaluated
relevant data streams, analyzed data, and helped to code the final visual concept. 
       As a secondary project, I lead in the research and prototype development of an internal proprietary digital curation tool —a mechanism for pooling and analyzing information from online sources and revealing emerging fashion trends.

Client: Holition
Date: 2018
Class: Data Science Capstone
Instructor: Dan Potter, PhD

SEEDLINKED: DATA-DRIVEN SEED SHARING

How do we unflatten, juxtapose, and reveal the multiple stakeholder perspectives in the agri-food supply chain to offer a more authentic experience? How can personal stories be used to connect people in the supply chain? Through shared data-driven insight, the SeedLinked platform aims to bring connectivity to plant breeders, seed companies, farmers, gardeners, chefs, universities, and other testing organization in order to support the growth of local organic farming. 
      In this essay, I examine and discuss SeedLinked (as a networked system) in relation to class readings, academic literature, and current entrepreneurial initiatives in the food industry. A secondary goal is to propose clear recommendations to help improve the interface design and the way that the data is shared across multiple users.

Date: 2020
Client: SeedLinked
Class: Foodways & Sustainable Food Systems, RISD
Instructor: Jonathan Highfield, PhD
Data Science, Food


(︎︎︎Read report)


PREDICTING HOUSEHOLD INCOME IN NYC

The goal of this collaborative project was to use census data to create two sensible models for predicting median household income and income per capita in New York City and the surrounding area. 
        Two analytical approaches, Stepwise Selection and Shrinkage Methods, were used to select a subset of predictors. Using the variables selected, we performed multiple linear regression to model median household income and income per capita as a linear combination of the potential predictors. Starting from that baseline model, we added interaction terms and performed transformations on variables based on exploratory analysis and model diagnosis. Finally, an interpretation for each model was provided.


Client: Self
Date: 2018
Class: Statistical Learning, Brown University
Collaborators:  Yiwen Shen and Zhiwei Zhang
Instructor: Alice Paul, PhD


FORCE AND POSITION MIDI CONTROLLER

For my senior capstone project in electrical engineering, I led a team of five other engineering students to design a highly customizable position and force sensing MIDI (Musical Instrument Digital Interface) controller prototype for a small synth repair company based in Southern Maine called New England Analog. MIDI is a technical standard for digitally representing and transmitting sounds — it is used as a touch surface to allow the user to control a wide range of sound parameters (e.g velocity, pitch, and panning) base upon the force of the applied touch.
        Over the course of the year, my team developed and produced a working prototype satisfying the major requirement and needs of the customer. We presented the result in front of a panel of judges and industry leaders. 

Date: 2014
Client: New England Analog 
Class: Electrical Enginnering Senior Capstone
Collaborators: Cameron Connor, Jean Pierre, Aaron
DaPonte, Greg Ladd, Devin Honeycutt
Advisors: David Rancour, PhD and Howard Michel, PhD
Data science, data visualization



(︎︎︎Process documentation)
(︎︎︎Full Report)


HUNGARY ACCORDION

A visually coherent group of information graphics and statistics about Hungary.

Date: 2016
Client: Self
Class: Information Design and Data Visualization (RISD)
Instructor: Doug Scott, MFA 
Data visualization














SLICE OF LIFE

Designed a data visualization telling the story of three personal trips: from my RISD room to the RISD Design Center, from my RISD room to home, and from my RISD room to Iceland.

Date: 2016
Client: Self 
Class: Information Design (RISD)
Instructor: Doug Scott, MFA
Data science, data visualization



SPEAKER DESIGN AND VISUALIZATION

I designed a speaker from scratch and then created an experiment to test it and visualize the acoustic data. The images shown here depict my full process, including research, circuit design, modeling, fabrication, testing, and visualization. 
        Directivity is the measure of how directional a source is — in other words, how good the loudspeaker is of transmitting sound at a specific direction. The final performance results indicate, as expected, that the speaker is more directional at higher frequencies. Sounds were produced using a frequency tone generator source at constant amplitude and recorded at five angles using a Zoom H2N microphone.

Date: 2016
Client: Self
Collaborator: Jorge Tonelli (circuit schematic)
Class: Electroacoustic Transducers
Instructor: David Brown, PhD
Electrical engineering, Data visualization



(︎︎︎Process documentation)







THE ETHICS OF SELF-TRACKING  

While the emergence of self-tracking devices presents numerous health benefits (e.g. sleep monitoring and “lab on a chip blood sensors”), it also raises important concerns as to how the data is being used and who is using it.
        In this essay, I provide a summary of the book “Self-tracking” by Gina Neff and Dawn Nafus and discuss the key ethical issues at hand with regards to the practice—privacy, data access, transparency, and commercial exploitation—in context with my research and class discussions.

Date: 2018 
Client: Self
Class: Data and Society, Brown University
Instructor: Roger Blumberg, PhD 
Data Science, Data Ethics



(︎︎︎Read report)


ARCHETYPE

Proposed a narrative-driven framework (a dual-sided marketplace) that connects multiple players in the fashion industry in order to help designers make use of upcycled materials at scale. Participated in RISD’s inaugural entrepreneurial accelerator, UpStart.

Date: 2019
Client: Self
Collaborator: Misha Gehring 
Advisors: Lindsay Degen (Converse), Michael Savoia (RISD), Dr. Jeff Huang (Brown University)


PAINTING CLASSIFICATION WITH CNNS

Within recent years, museums and online art collectives around the world have started to digitize their art collections. In order to help support educators, curators, and archivists to archive and find interesting correlations between artwork, I helped to design a deep learning model.
        A database was formed with over 15,000 web-scraped images, each having attributes like (e.g. date and artistic style). A total 12 total artistic styles and 28 artists were represented. A convolutional neural network (CNN) was trained to predict style and artist, with a validation classification accuracy of 40% for style and 53% for artists. A simple visual interface was made to allow a user to run new (untrained) images through the model.
        The research was conducted under the guidance and mentorship of Dr. Serre from the Cognitive, Linguistic, and Psychological Sciences  (CLPS) lab at Brown University. 

Client: Self
Date: 2017
Class: Data and Computational Science
Instructor: Dan Potter, PhD


SPATIAL PERCUSSION THROUGH MOVEMENT

Spatial Percussion is an expressive musical composition tool which uses hand gesture to enable the real-time positioning of percussive sounds in spatial audio (ambisonics format). The project was born out of the desire to compose a spatially-located percussive beat through movement. All drum sounds were recorded manually. The project was programmed in Max/MSP.

Date: 2019
Client: Self
Class: Spatial Audio (RISD)
Collaborator: Arjun Shah
Instructor: Shawn Greenlee, PhD
Data science, Sound design






SEARCH ENGINE

Created a search engine from scratch to navigate, query, and analyze a large Wikipedia corpus. Two ranking schemes were implemented in the system (tf-idf and PageRank) as well as a number of query types: one-word, free-text, phrase, and boolean. 

Date: 2018
Client: Self
Collaborators: Tong Zhang

Matthew Bejtlich © 2020
Matthew Bejtlich © 2020