Prize Winners

For mentor biographies, please see the Mentors page.

Anshul Aggarwal (2018-2019)
Nettd: Mapping Your Personal IRL Social Network
Mentor: Venky Harinarayan
Year: Senior
Major: Computer Science and Engineering

Digital social networks are well mapped-out, yet little has been done to map personal interactions – interactions that carry more emotional weight in an individual’s life. This project aims to create and design a living, viewable, and personal social network graph based on the quality and quantity of a user’s daily, real life interactions. We capture this data through a mobile application with GPS tracking and analyze all interactions with other users: everything from passing by on the street to spending hours talking. Using our server, we calculate the length and weight of the interaction, and update the social graph for the user to view from the app or online. Using this information, a user can better dictate how they spend their time and who they spend it with.

Oluwatomi Balogun (2017-18)
Auditing Attention: The Correlation between Social Media Usage and Attention Span
Mentor: Bran Ferren
Major: Communications
Year: Senior

This research project investigates the impact of social media usage on attention span. The research aims to elucidate the following concepts: the effects of digital media on cognitive functioning, the differences and similarities between the individual yet interdependent dimensions of attention, and the merits and perils of social media and living in a digital society. The project’s methods include running a correlational study that explores the relationship between a subject’s social media use (measured as a unit in time in hours) and their score on a corroborated test of attention with high construct validity. The final product of this research will be a  paper outlining the study and its implications.

Output: QuadChartOluwatomiBalogun

Byron Briones (2019-2020)
The Culture of the Online Political
Mentor:  Ninez Ponce
Major: Political Science, Education Studies Minor
Year: Junior

As of now, there is no correctly informed understanding of the political culture of the modern internet, especially within the Generation Z and late millennial generation, and its ideas, memetic ways of spreading, hidden means of subtle communication, and dominant communities. This project will use ethnological and empirical methods to provide this understanding for the internet savvy of the left and right wing with a special emphasis on the right. This project is unique in that it will be analyzed by a person who is extremely familiar with the ideas and that it’s supplemented by three empirical studies. The first will identify the Reddit communities most used by both ideologies. The second will find if meme involvement and understanding is strongest by the right or left. The third will analyze interpretations of memes and correlate them with frequency of internet usage and the online communities they most use for political networking. With this, internet hosts and law enforcement can prevent domestic terrorism through deplatforming and identification of hidden memes and ideas.

Sarah Brown (2016-17)
Researched potential of internet to improve health care experiences for young people.
Mentor: John Silvester
Year: Junior
Major: Human Biology and Society, Entrepreneurship minor

Alexander Chen (2017-18)
The applicability of deep learning in the diagnosis of stroke
Mentor: Michael Silton
Year: Sophomore
Major: Computational and Systems Biology, Bioinformatics minor

Stroke is a serious issue across the world, leading to disability or death. Annually 15,000,000 people suffer from stroke, 5,000,000 of which become disabled and 5,000,000 of which die. My research attempts to alleviate some of this harm by enhancing the stroke diagnosis process using machine learning on MRI. The project includes the binary “stroke” or “no stroke” classification of MRI data, and extraction of useful information from MRI data to develop AI software to diagnose stroke from the raw MRI data. This will promote a more effective selection of treatment for patients.

Output: AlexanderChenQuadChart

Abineet Das Sharma (2017-18)
Flying a drone reliably over the Internet
Mentor: Leonard Kleinrock
Year: Senior
Major: Computer Science

Drones today primarily fly over radio telemetry. My goal is to completely migrate the telemetry, as well as video streaming and processing, to the ground station over the Internet. My research goal is to attempt to prove that drones can fly over the internet, and handle themselves reliably when out there is a loss of connection. The drone would connect to the internet and communicate with a ground station over it, and hopefully be smart enough to handle situations where it loses connection temporarily.

Output: QuadChartPresentationAbineetDasSharma

Jeremy Giampaoli (2016-17)
Researched brain-computer interfaces for the control of physical technologies.
Mentor: Roy Doumani
Year: Junior
Major: Mechanical Engineering, Conservation Biology Minor

Miguel Gutierrez (2018-2019)
Design & Power: How Information Architecture Reibes Information Asymmetries
Mentor: Lilian Coral
Year: Senior
Major: Art History

Donald Rumsfeld once convolutedly explained that “there are known knowns…unknown knowns…and unknown unknowns,” and in the advent of an algorithmic culture and data capture, there are perhaps more “unknown unknowns” than we as users or the outfits who employ these methodologies would like to admit. Critical algorithm studies have looked closely at what algorithms are, what they are doing, and what are their “real-world” consequences are, but the focus on a subject in the context of information architecture has been widely overlooked. The interface, as a site of a subject’s relationship to system affordances, is perhaps why there are as many “unknown knowns” and “unknown unknowns” as there are. If the interface itself was to be the locus of analysis, we will have to look critically at their design. In my project, I would first like to write a research essay that focuses will be on how information architecture itself has the power to give visibility and to silence, reinforce the information asymmetry between subjects and proprietary outfits/government actors, and limits subject agency in the context of civic participation. I would like to accompany this research-based essay with a proposal for a platform redesign that fixes the issues my essay points out. This proposal will include empirical research with stakeholders, developed personas, and wireframes that will eventually lead to a prototype.

Howard Huang (2017-18)
Use of machine learning to detect fake news
Mentor: Venky Harinarayan
Year: Senior
Major: Computer Science

I am researching the applications of machine learning in digital journalism. The idea is to apply current techniques and research in machine learning and deep learning to find if there can be a way to automate the fact checking process. Although this is a long running problem that is already being researched, I hope to take a different perspective on tackling fake news by looking at it from a new perspective. One of the research goals is to create a tool that newsroom can use to help streamline copy editing process.

Output: HuangDemo, QuadChartHowardHuang

Michael Ho (2016-17)
Researched virtual reality in the fine arts.
Mentor: Jayathi Murthy
Major: Fine Arts and Design and Media Arts

Canaan Howard (2017-18)
Augmented and virtual reality technology in healthcare
Mentor: Roy Doumani
Year: Senior
Major: Psychobiology

This project’s focus for the year will be exploring the potential applications of virtual and augmented reality in the healthcare space, primarily investigating how these technologies could be used to improve both caregiver and patient experience. Research includes interviews with healthcare technologists and practitioners, and reviews of existing healthcare technologies to discover a space where it would be practical to use AR or VR without trying to simply use the technology for the sake of using it. The final deliverable will build from the previous quarters’ research to develop some simple prototypes of software that could have applications in healthcare that could be improved upon in the future.

Output: HowardDemo, QuadChartCanaanHoward

Ashley Hoffman (2016-17)
Researched filter bubbles
Mentor: Jean-François Blanchette
Year: Junior
Major: Computer Science, Art History minor

Devin Johnson (2017-18)
Erotic Labor on the Internet
Mentor: Ninez Ponce
Year: Senior
Major: Design & Media Arts

Just as many have over-optimistically written about the Internet’s radical potential for social liberation, academics who have researched Internet sex work have also given the Internet too much credit for providing affordances for sex workers as a supposedly “democratizing” force. Through my research, I would like to provide a more critical lens for understanding how the digital era has transformed sex work. I will illuminate the experiences of those most vulnerable to exploitative power structures, and how computer mediated communication and the online marketplace can reinforce the oppression of poor, queer, and disabled sex workers, and sex workers of color. I will also investigate methods in which the internet and new media technologies can truly be employed to facilitate safer conditions for marginalized peoples to engage in sex work, labor unionization, art making, intimacy, and gender performances online in non-exploitative and beneficial ways.

Ryou Kato (2016-17)
Researched live virtual reality streaming.
Mentor: Leonard Kleinrock
Year: Senior
Major: Mechanical Engineering

Zoe Ingram (2017-18)
Speech to Shape Tool: voice-activated technologies for accessible design
Mentor: Johanna Drucker
Year: Senior
Major: Design | Media Arts

About 15% of the world’s population has a disability. One would assume that the internet would enhance opportunities for disabled people, however, most technology is developed without the needs of the disabled in mind, with the result that disabled people are far less engaged with the internet than the general population. To critically engage the design issues surrounding this problem, I am building a speech activated drawing and design application that runs in the browser. This application will be built on the foundation of accessibility. The software will be designed for users who, due to congenital, disease, or injury-related disabilities, are unable to use traditional digital hardware like a mouse and keyboard. Users who do not have the time or ability to master complex software like Adobe Photoshop or Illustrator will also benefit from the simplicity of this application. By removing the human dependencies present in current visual creation software, I am able to build my application with just one human requirement: speech. By using simple phrases to illustrate shapes, colors and lines, users will be able to take the intuitive control of drawing with a pencil and combine it with the convenience of working digitally.

Output: IngramDemo, ZoePres

David Gary Khachatrian (2016-17)
Researched correlation between social media use and depression
Mentor: Safiya Noble
Year: Senior
Major: Bioengineering

Annita Kuo (2016-17)
Researched a new language learning tool that provides visual feedback to language learners using frequency analysis.
Mentor: Johanna Drucker
Year: Senior
Major: Linguistics and Computer Science

 

Daniel Seung Lee (2019-2020)
Information Canvas : Making University Research Accessible Through Generative Art
Mentor: Jayathi Murthy
Year: Junior
Major: Design and Media Arts

I am proposing a public art project which I will use the television monitors installed on
campus to showcase generated infographic artwork based on student research data.
Undergraduate students at UCLA produce an outstanding amount of thoughtful research, yet it is hard for some to communicate on the internet outside of monopolized publication journals or their personal social media. Also it is difficult for some students not well versed in computer graphics to create infographics for their work. At the same time, there is not enough opportunities for public to engage with university research outside of news media. My project’s goal is to make a web-based tool that creates generative infographic artwork based on research paper or projects students submit. I aim to filter and organize the submitted information through machine learning algorithm and generate corresponding information based visuals with set parameters. The project is unique as it uses televisions as framed canvas to give people more access to art and undergraduate research. Moreover it can empower students to create infographic visuals they can use with the project’s website. It will
also be open sourced, so the outcome of my research can benefit anyone interested in using similar approach.

Wan Di Liu (2016-17)
Researched affective computing for an online therapy artificial intelligence that analyzes human sentiment.
Mentor: Eric Haseltine
Year: Sophomore
Major: Linguistics and Computer Science

Cheechee Lin (2016-17)
Researched millennial purchasing and browsing behavior in m-commerce.
Mentor: Michael Silton
Year: Senior
Major: Communication Studies

Natasha Lum (2019-20)
Putting the Globe on the Blockchain
Mentor: Leonard Kleinrock
Year: Junior
Major: Global Studies/Digital Humanities

Coined the world’s next disruptive technology after the invention of the internet, blockchain has taken the world by storm since it was introduced in 2008 as the core technology behind the cryptocurrency, Bitcoin. While it is still in its infancy, its applications as a platform for decentralized governance are believed to be wide-ranging, going far beyond the realm of digital finance and extending to the wider fields of politics, business and society. Several developed countries have recognized the potential of blockchain and have launched nation-wide initiatives to promote the adoption of blockchain technology in both the private and public sector, and a few states in the US have also replicated such efforts on a state level. Despite such advances in the technology, there is still little scholarship in the field. My project seeks to find out if there is an imperative for world leaders like the US to set a global example by launching a national strategy for blockchain through the investigation of the potential benefits and challenges of promoting and regulating blockchain technology in the private and public sector. I eventually hope to theorize a possibility of global governance by putting the world on a blockchain through its implementation in the UN. While I am not seeking to be an advocate for a national or international strategy for blockchain, I do hope that this research will encourage further scholarship in the area and inspire greater innovations in blockchain technology.

Ellen Mei (2019-20)
Labor Organization and Activism in the Tech Industry
Mentor: Miriam Posner
Year: Junior
Major: Linguistics of Computer Science

Issues of diversity, equality, and ethics in tech are structural across the industry and its products. To achieve a future of ethical and equitable Internet technology and labor relations, workers from marginalized groups should be given sustainable means to self-advocate, and more privileged workers should understand and invest resources into labor activism. This project investigates the contemporary challenges, methods, and gains of labor organization and activism in the high-tech and knowledge industries, focusing on companies who primarily build and therefore promote their agenda and values via company domains on the Internet (i.e. Google, Facebook, Amazon, etc.). Through investigating labor history and conducting interviews with tech workers, the intention is to create an online learning resource for students and tech workers to understand available means of self-advocacy across labor classes and diverse identities. This project can help those who seek to positively impact tech understand ways they can promote social justice, advocate for themselves, and find community. In a time when people increasingly feel the necessity of labor solidarity and empowerment, this project seeks to gather together historical overview, laborer realities, and contemporary organizational methods for enacting change, giving tech students accessible knowledge to help advance their own goals for self-advocacy.

Angelo Mendoza (2018-19)
Personal Budget Application for Low-Income Households
Mentor: Ninez Ponce
Year: Junior
Major: Political Science

Many low-income households do not keep a detailed budget. This is a problem since not properly tracking expenses can lead to overspending. Overspending is especially a problem in low-income households as it can lead to excessive credit card debt or the reliance on payday loans to make up the difference between paychecks. My proposed project is the creation of an affordable personal budget application that is also simple to use. Low-income households that can’t afford expensive budget applications and individuals that do not have very much spare time to spend creating detailed budgets will bnd this software useful. Creating a budget will allow households to know where exactly their income is going to and will help them manage their spending more easily. This project will be unique as many other budgeting software are expensive with some costing almost $100/year. Also, currently existing budgeting software can be didcult and time-consuming to use. The successful completion of this project will result in personal budgeting software being more accessible to low-income households and more.

Ethan Mitchell (2019-20)
Using Connected Mobility and Disability Data for Economic Development Planning
Mentor: Lilian Coral
Year: Senior
Major: Electrical Engineering

With the recent rise of IOT devices came a rise of connected mobility devices. I am investigating the intrinsic inequalities for low-income and disabled residents that have arisen as cities began to rely on paid last-mile and other single-use transportation in their planning and economic developments. Using GeoHub DASH data and automatic traffic counters to map and track the impact of last mile transportation will allow the visualization dashboard to have both a real-time and in-depth effectiveness. Here I propose a webapp to mitigate the unintentional effects of technological bias and induced error in DASH data and bus statistics. This solution is unique because it uses data from connected mobility devices as well as the usual city data to create a full, real-time visualization of the negative impacts that connected mobility devices have on low-income and disabled residents. The visualization portal will reduce the impact that connected mobility devices have on low-income and disabled residents.

Liam Monninger (2018-2019)
Twitter Finger: Tweets as Commitment Devices in Modern Diplomacy
Mentor: Sarah Roberts
Year: Junior
Major: Political Science

The era of the social media politician challenges many of the established norms of political discourse. Nowhere is this more true than in the realm of international relations, wherein the calculus of diplomatic discourse has been inundated by heads of states firing off tweets from armchairs. To understand the effects of this shift, this paper zeroes in on the medium of Twitter and seeks to gauge the viability of the tweet as a commitment device. To gauge said viability, this paper performs qualitative case by case analysis of the effects of tweets on various regimes and performs a quantitative analysis of the effects of tweets on domestic and foreign audiences. The intent of this project is to further the understanding of Twitter as an instrument of politics in the 21st century.

Liam Monninger’s report

Elizabeth Nakamura (2018-2019)
Machine Ethics and the Problematics of Deepfake
Mentor: Lauren McCarthy
Year: Senior
Major: Art History/Digital Humanities

Deepfake is a technique that employs machine learning and deep neural networks to produce realistically manipulated faceswap videos. In late 2017, Deepfake gained prominence on Reddit as a means of proliferating fake celebrity pornography. Because of the technology’s accessibility, anonymous users, using external imagery gathered from videos and images, easily superimposed the faces of Hollywood actresses onto the faces of porn stars. While Deepfake is not sophisticated enough to bridge the uncanny valley, these videos are realistic enough to raise moral concerns, forcing us to contend with our vulnerability to misinformation in today’s info-driven society. Deepfake serves as an epistemic provocation that challenges current understandings of machine ethics. Using Deepfake as a starting point, I want to point out the risks our society collectively risks if technocrats fail to establish an effective AI moral code. Furthermore, I seek to combat the perpetuation of misogynistic power structures in the digital age by addressing issues of consent, sexual objectification, and labor abuse in pornography and its impacts on human interaction. In my research I hope to address Deepfake from an interdisciplinary perspective, analyzing both its sociopolitical and technological implications.

Inesa Navasardyan (2019-2020)
Effectiveness of informatics on improving patient outcomes
Mentor: Peter Reiher
Year: Senior
Major: Biophysics

The problem I am investigating is the barriers that prevent health organizations from implementing informatics in the clinical setting. Integrated use of health IT has been shown to improve patient care, reduce medical errors, and curtail administrative expenses. This project is unique because although many individuals are aware of the benefits of using information technology in healthcare delivery systems, evidence-based research regarding these outcomes are limited. The goal of this project is to provide qualitative evidence regarding the outcomes of IT in health care delivery systems. The benefit of this project will be to overcome user resistance by identifying and overcoming barriers in utilizing informatics in health care.

David Nguyen (2017-18)
Evaluating Community College to PhD Association’s Internet-mediated interventions
Mentor: Amit Sahai
Year: Senior
Major: Sociology

I am implementing and conducting evaluation research of the pilot program: Community College to PhD (CC2PhD) Scholars Programs. The program’s goal is to diversify the professoriate by preparing community college transfer students for doctoral studies.  My IRI research investigates the potential of internet-mediated interventions to improve the community college to PhD process. I look to understand program participants’ perceptions of the efficacy and self-reported use behavior of the CC2PhD Scholars Program’s internet mediated interventions: videoconference e-mentoring, private Facebook group as an online community of practice, and lecturecasts of CC2PhD Saturday Academies.

Output: QuadChartDavidNguyen

Kiarod Pashminehazar (2018-2019)

Origins of Fake News: Tracking Information Mutation on the Internet
Mentor: Leonard Kleinrock
Year: Junior
Major: Mechanical Engineering

This is an investigation into the mutation of information reported by various media outlets presently on the internet. Often, the same story is covered by multiple news outlets, and this redundancy creates the opportunity to cross examine the information provided and create a comprehensive, informative history of a story. This data could help in analyzing a multitude of trends, the foremost being information mutation. With a dataset of story history’s I would like to analyze trends such as: sources which often report first, sources which seemingly have a relationship with other sources, sources
which consistently introduce differing/new information to a story history. With this information I am aiming to build a tool which will evaluate the media efficacy, and help take a step towards restoring authenticity on the internet.

Niyati Patel (2016-17)
Researched the Internet of Things and Big Data’s impact on existing public infrastructure, workforce development and civic engagement in Los Angeles.
Mentor: Ellen Levy
Year: Senior
Major: Economics and Human Biology and Society

Michael-Sesen Perrilliat (2019-2020)

Equal Footing: Art and Activism meets Equitable Technology
Mentor: Jeff Burke
Year: Junior
Major: Political Science/ Af Am

The use of social media, smartphones, and accompanying compatible apps, websites, and tools allow members of marginalized populations to have a platform previously unattainable. Social media has played a huge role in the recent evolution of the civil and human rights movement, as Black Lives Matter itself was founded from a tweet and many organizers utilize social media to effectively communicate with others and to plan for methods to achieve change. In this new era, anyone with access to a smartphone or the internet can impact their surrounding community. However, this still requires particular skill sets, knowledge, and nuance to harness. The lack of diversity in the tech field suggests this. However, community organizations like the HUB and initiatives like yes we code that target previously excluded populations suggest change. By addressing the use of social media and technology, this project will specifically address marginalized populations, and with my major in poli sci and minor in af am, as well as my personal experience with community organizing, I’ll be able to target groups unreached previously. This research will help develop a framework of understanding, provide artists and activists a voice, and provide others a guideline toward a platform that embraces equitable use. I also seek to find difficulties or hurdles associated with the use of social media and technology.

Devin Reeh (2018-2019)
Failure to Adopt – Big Data, Machine Learning, & IoT
Mentor: Rajit Gadh
Year: Senior
Major: Statistics/Bioinformatics

Big data, machine learning, and the internet of things have and will continue to fundamentally change how our society functions over the next twenty years. Currently, a small portion of companies have had massive integrations of such technologies, whereas a vast majority have had minor implementations or none at all. This project will investigate how the spectrum of adoption and, and more importantly, how the lack of adoption, have affected businesses and the middle class workforce in developed markets. Furthermore, “Failure to Adopt” will examine how the teachings of these instances can be applied to lagging firms and whether their technological adaptation has the momentum to prevent economic stagnation of middle class individuals.

Sahen Rai (2019-2020)
You Are Loved: Mental Health Tracking for Everyone
Mentor: Amit Sahai
Year: Freshman
Major: Computer Science

After losing a classmate to suicide last year, I realized that I wanted to dedicate my life toworking on things that help people struggling through depression and anxiety. I believe that the hardest thing about discussing mental health is not wanting to be a burden to people by telling them how you feel. This is why I created my app, You Are Loved. You Are Loved is a way for friends and families to keep track of how their loved ones are doing. Users enter a number every day on a scale of 1 to 10 based on how they feel; then, app takes an average of how their ratings and creates a graph tracking their numbers. This allows users to understand their data and identify days or time periods when they feel worse. Furthermore, whoever has added you on the app can tap your name to give you a call if you don’t seem to be doing great. You Are Loved also provides users with uplifting articles meant to make them feel better about the world, and sends them a reminder that they are loved every day.

Parsa Rezvani (2017-18)
Tutorfly’s Sustainable Peer Tutoring in Low Income Communities
Mentor: Jayathi Murthy
Year: Senior
Major: Economics, entrepreneurship minor

Tutorfly.org is a peer to peer tutoring model platform that pairs high school student tutors with younger students at the same school needing tutoring. The goal is to create a tutoring model that is more efficient and cost efficient as well. We have performed some tests with our alpha launch to better understand the market in more affluent neighborhoods in the Bay Area and Los Angeles. The IRI project extends upon previous research to investigate the effectiveness of peer-to-peer tutoring in lower income communities.

Output: Parsa Rezvani_#4 Final Presentation

Sydney Richter (2017-18)
Hyperfocus: An ADD/ADHD Application
Mentor: Krisztina “Z” Holly
Year: Junior
Major: Applied Linguistics

My research project focuses on building a computer application that will benefit students with ADD or ADHD with their studying. People who have ADD/ADHD struggle to concentrate and complete anything from menial tasks to academic projects. This stems from several factors, including, but not limited to swayed sense of time, inability to block out external inputs, and lack of stimulation from the part of the brain that promotes focus. However, when someone who has ADD/ADHD finds something that they enjoy or are passionate about, they are able to hyperfocus. My project aims to tap into this ability to hyperfocus by creating an app that turns school material into a format that will make learning enjoyable and more efficient.

Output: QuadChartPresentationSydneyRichter

Shanmukha Srinivas (2016-17)
Researched impact on public health outcomes from internet connected computer labs for squatter community in Maclovio Rojas.
Mentor: Amit Sahai
Year: Senior
Major: Psychobiology, Global Health minor

Avirudh Theraja (2017-18)
Extraction of software metadata from scientific publications
Mentor: Eric Haseltine
Year: Senior
Major: Computer Science

My project aims to solve a problem faced by a lot of academic researchers in Bioinformatics and Computer science. The goal is to build a high quality web service which allows researches to search for all sorts of open source software published in articles in prestigious journals in the academia world. This software data will be collected by writing a robust backend and data pipeline which extracts high quality metadata from the articles. The end result is a web application which allows fast searching and relevant information of the vast number of new and exciting open source software which is published frequently in all sorts of journals such as Bioinformatics, Nature, BMC Bioinformatics etc.

Output:QuadChartPresentationAvirudhTheraja

Nephele Troullinos (2018-2019)
Agency through Virtual Sociality: Social Media in Critical Media Literacy Curricula
Mentor: Miriam Posner
Year: Senior
Major: Fine Art

This research will aim to uncover the potential of social media to create personal agency in young students, through a pointed focus on social media within a media literacy program. The question at the core of this research will be: As social media lies at the intersection of information gain and sociality, how could the intentional use of social media increase cognizance and political engagement in youth? The United States education system and its primary school students will be at the focus of this research. America’s youngest generations have now been dubbed ‘digital natives’ for their presumed digital literacy. Concurrently, widespread moral panic about the detrimental effects of technology on an impressionable population, largely from older generations of ‘digital immigrants,’ has discredited the constructive potential of a high-networked future populace. Such potential, however, may only begin to be uncovered when emerging social media studies and theory becomes integrated into primary education programs. Looking to scholarship and case studies on the intersection of digital media and education, this project hopes to propose a model social media studies program. A curriculum that guides students through the historical evolution, and societal and psychological implications of social media platforms, may allow students to unpack its informative and empowering potential.

Adam Weiner (2018-2019)
Identification of emerging flu strains and subsequent vaccine analysis
Mentor: Michael Silton
Year: Senior
Major: Bioengineering

Each year, the flu virus hinders the lives of millions of people across the globe. Despite the yearly release of vaccines, there are thousands of flu related deaths andmany more hospitalizations per year. If we can develop vaccines which better target emerging flu strains and have more people get vaccinated, we can reduce the dangers of flu season each year. The goal of this project is to tackle both of these issues through providing high level virus and vaccine analysis that is publicly available and interpretable. I plan on using influenza H3N2 hemagglutinin sequencing data paired with machine learning methods to identify emerging flu strains and evaluate how well each year’s vaccine protects individuals against these emerging strains. Once I have completed my analysis pipeline, I will perform critical analysis of flu vaccine from different years to track the improvement of the flu vaccine over time. Lastly, I will develop a website that continually identifies emerging flu strains and evaluates vaccines by analyzing the sequencing data as it is released, providing health officials with valuable information about circulating flu strains and shedding light on vaccine development to the general public.

Results: Adam Weiner Quad Chart

William Whitehead (2018-2019)
Pixel-wise semantic image segmentation with variable pixel density
Mentor: Jeff Burke
Year: Junior
Major: Electrical Engineering

Each pixel in an image represents a part of some object. Semantic segmentation figures out what each pixel in an image belongs to and gives it a corresponding label. Currently, the best segmentation algorithms are Fully Convolutional Networks (FCNs), a type of artificial neural network that outputs an entire image segmentation at once. While these networks often get good results, they have trouble precisely identifying smaller objects and edges. I want to investigate ways of warping images around focus pixels to help the neural network identify where the border of an object is. This idea draws inspiration from human vision, which has a much greater spatial resolution at the center than at the edges. However, the segmentation will have to be done pixel by pixel, which has a high computational cost. If this method does result in better segmentations, it could find immediate use in fields that desire precision at any computational cost, such as medical image analysis. However, its high computational requirements would prevent its use in real time applications such as autonomous cars. The results however may inspire better design of FCNs, which could find use in real time systems.

Rhiannon Wilson (2019-2020)
Computer Room: Poetry Exploring Digital & Domestic Intimacy
Mentor: Sarah Roberts
Year: Senior
Major: English/Developmental Psychology

A “computer room” changes shape based on context. In the realm of technology, it is a storage vault of servers. In historical terms, it might be the break room for NASA secretaries.  For many people of my generation, the computer room was a space designated for the desktop. As digital technology became more portable, that room disappeared alongside the boundary between private life and public connection: the computer room is now any pocket.

Charles Zaloom (2019-2020)
EmbeddedML Application and Toolkit for Low-Power IoT and Wearables
Mentor: Venky Harinarayan
Year: Senior
Major: Electrical Engineering

Measuring muscle fatigue has historically been an imperfect science based on individual perceptions. Medical doctors, the military and athletes all work to maximize muscular optimization within the limitations of qualitative measurement. My project will provide a toolset that interprets electrical activity in muscle groups during physical activity providing measurable quantitative data. Data will be recorded and processed with a wearable electromyography sensor that will detect true muscle fatigue. Over the course of my research I will develop algorithms that solve complex signal processing problems using only a small, battery-powered device. Complex signal processing occurs in many IoT systems where a sensor remotely streams data to a server for processing. My solution will bring machine learning onto the sensor’s microcontroller and allow for low-power sensors to perform classification and initial processing locally before attempting to connect with a remote server.  This project is very unique as there has been no push in industry to develop on-chip ML solutions. I believe that the applications of this toolset would allow for the development of IoT and wearable technology that can be used by the medical profession, military and athletes.

Kuan (Vic) Hsuan Yeh (2016-17)

Researched neural network and isomorphic techniques to develop keystroke dynamics to secure personal data online.
Mentor: Venky Harinarayan
Year: Senior
Major: Computer Science and Physics

Hongyi Zhang (2018-2019)
Empowering the newsroom: Tech for local journalism
Mentor: Jayathi Murthy
Year: Senior
Major: Computer Science

The local newspaper, once the bedrock of communities large and small all over America, is under siege. Declining ad revenue and an inability to adapt to a digital-first news environment has resulted in many struggling to stay afloat. While this is a multifaceted problem that does not present any easy solutions, one small part of the issue is that these newsrooms lack the resources and expertise to leverage modern technology and tools that other modern, well-funded news outlets utilize and thus harming their competitiveness. As I would subsequently explain, I believe local newspapers matter, and I want to help research and build easy to use open source tools that utilize modern technologies and machine intelligence from NLP to aid in the operation of small newsrooms, and help drive their engagement with local readers. The project seeks to understand the pain points and needs of these organizations, starting from campus newspapers, and then working to build a suite of open source micro-services that help to tackle problems from comments filtering to content management to social media management. These tools are currently expensive or entirely proprietary, and this project aims to make them available and help even the playing field.

Pei Zhou (2018-2019)
Fairness in Online Natural Language Processing Systems
Mentor: Amit Sahai
Year: Senior
Major: Mathematics of Computation

Online Natural Language Processing (NLP) systems like sentiment analysis, language identification, and visual tagging have been used by millions of people everyday. However, reports have found that some systems like Google’s Cloud Natural Language API and IBM’s Watson Natural Language Understanding are biased and some words like “Jew” and “homosexual” are interpreted to be negative. Researchers have also found racial disparity in language identification for tweets and gender biases for image tagging. This project will investigate different kinds of biases in NLP algorithms and propose computational models to reduce biases in various applications. Specifically, the project will first find sources of biases and quantify them in major NLP systems. Then it will improve current methods in NLP for tasks like sentiment analysis so that fairness is ensured. Possible ways of improvements are imposing constraints on the training corpora, and calibration on some certain variables including gender, race, and sexuality. This project is unique because although fairness in Machine Learning (ML) is getting more attention lately, fairness in NLP is still an issue not tackled by researchers. The project will benefit all users (especially minorities) of NLP systems on the Internet, which are almost everywhere, including Twitter, Facebook, Google, etc.

Results: Pei Zhou Report

David Zhu (2017-18)
Project: Blockchain technologies for the future of finance
Mentor: Lilian Coral
Year: Senior
Major: Philosophy

Bitcoin is revolutionizing the way the world sees money, utilizing the instant transactions that can be sent from one side of the world to another, without the need for any third party exchange such as a bank or Foreign Exchange. However, the real ingenuity behind this is Blockchain technology, which is an unalterable public database accessible by anyone with Internet connection. Currently, the technology is in its infancy, and its real world applications for businesses and consumers have not been realized in the market yet. Many established large corporations as well as startup tech companies are jumping on this chance to incorporate Blockchain technology into their every day operations. I am researching user-friendly financial applications for this groundbreaking technology.

Output: QuadChartPresentationDavidZhu