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.

Results:  Anshul Aggarwal’s quad chart

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.

Results: Oluwatomi Balogun’s Quad Chart

Rohan Bansal (2020-2021)
Online Learning: Is There a Better Way?
Mentor:  Jayathi Murthy
Major: Mathematics of Computation/Film and Television
Year: Junior

Digital Learning is here to stay. But given the amount of content online, people are inundated with choices about the best path to learn. This project explores the question of which education method(s) are most effective when studying online. For different different fields and different individuals it is likely that these methods will vary. But, by conducting primary research on students this project hopes to find and generalize the digital study methods that they most respond to with respect to different types of subjects. Further, by consulting education professionals and professors at different institutions we will create a guided course of exploration and skill-development in different disciplines, optimized for online learning. This guided course would be in the form of a website and the student-study in the form of a paper. This not only means providing recommendations about specific resources, but also on the specific educational practices that one should institute while learning these subjects. This helps people who are exploring a subject or those who want to develop skills for their career. In either case, it makes access to higher education more accessible and equitable for people around the world.

Rohan Bansal’s final presentation

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.

Results: Byron Briones’ Quad Chart

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

Results:  Sarah Brown’s Quad Chart

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.

Results: Alexander Chen’s Quad Chart

Zixuan  Chen (2020-2021)
TactileSoccer: A Haptic Device Helping Blind People Understanding the Spatial Information in Soccer
Mentor: Peter Reiher
Year: Junior
Major: Linguistics and Computer Science

When Blind people watch a soccer game with friends, they can only depend on voice commentary to “watch” a soccer game. However, the spatial information, like the ball’s moving trajectory and where players running at, is often impossible to understand without others helping. Without spatial information, a fierce soccer game may become a tedious report. To solve this problem, we introduce TactileSoccer, a device to help blind people understanding what’s really happening in the court. Our device consists of two handles and one plate representing the soccer court. First, we use computer vision technique to convert a soccer match into spatial time-series data, and secondly, we map the data to our haptic handle. User’s left hand holds the guest team handle, and right hand holds the home team handle. The handles will keep moving, synchronized with real players moving, and they will give kinesthetic feedbacks according to player’s move, e.g, pass, shoot, out-of-bounds… Especially, when a player is passing a ball 45 degree from the north, the linear actuator will popup in the same direction to show where the ball is moving.

Results: Zixuan Chen’s Quad Chart

  Rhea Churi (2021-2022)
  IRIS by The H.E.A.L.L Initiative
  Mentor: Jayathi Murthy
  Year: Senior
  Major: Neuroscience/Global Health

 Problems of inequality within the healthcare system are often overlooked. We expect the doctors, nurses, and other medical practitioners are doing the best of their ability to treat us. However, for many marginalized communities, this is far from the truth. As of right now, we can see how the COVID-19 pandemic, which was thought to be ‘the great equalizer’ has instead highlighted discrimination within the medical sphere. The H.E.A.L.L (Health Equity and Accessibility for ALL) Initiative aims to combat this through the innovative new IRIS app/website. IRIS is a patient advocacy forum that would function as a public reviewal tool of hospitals in your area to share instances of medical racism/sexism/homophobia and more. People would be able to rate and share their own reviews of their hospital visit and access and support resources that reduce healthcare disparities. This project is unique because it publicizes the voices of underrepresented patients and shares their experiences of medical discrimination to the general population. It will draw awareness to those who suffer from institutionalized violence in medicine and promote activism and change for a better, egalitarian healthcare system in the United States.

Hanna Co (2021-2022)
Lack of Care in the Computer Science Community
Mentor: Lillian Coral
Year: Junior
Major: Computer Science

For the purpose of this project, care is defined as recognizing, acknowledging, and attempting to address systemic issues faced by certain marginalized communities. As I become more integrated into the computer science community, what has become increasingly more obvious is the lack of care in the computer science community. Many classmates I have interacted with aren’t aware of injustice or ethical issues society faces today, or don’t see its significance. My proposed project attempts to address this issue by researching its “severity”, as well as outlining solutions that could be implemented here at UCLA, through courses or modules integrated into existing curriculums. My hope is to address this issue at its core by bringing to light the importance of being a socially aware computer scientist. There have been attempts to integrate ethics into computer science curriculums, but many of those are newly developed, and seem surface level. My project is unique in the sense that I am able to have unfiltered interactions with aspiring computer scientists, and find the root cause of this issue.

Kaushik Devireddy (2021-2022)
Crypto Firewalls: Secure Standards for Connected Cryptocurrency Wallets
Mentor: Venky Harinarayan
Year: Sophomore
Major: Computer Science

Crypto wallets were designed to be used by the individual in an air-gapped hardware wallet. However, as enterprises begin accepting cryptocurrencies as payment over the internet, and building programmable APIs and applications on top of crypto wallets (banking, custody, trading, etc.), these wallets will increasingly require connectivity to other wallets through full nodes and application servers. This brings along a slew of security challenges unique to connected crypto wallets: ensuring an infected application server can’t exfiltrate wallet funds, enforcing white/blacklists for transaction types and destinations, creating access-control lists for cold-storage transfers, etc. My project focuses on developing a set of open firewalling standards for the Bitcoin and Ethereum protocol to solve these challenges, and implementing them in software as an open-source project. This is unique as current network security solutions do not take into context the transaction-level details to protect wallets. This work will result in greater adoption of cryptocurrency for individuals and enterprises, as well as usher in the era of programmable, crypto-finance applications.

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.

Results: Abineet Das Sharma’s Quad Chart

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

Results: Jeremy Giampaoli’s Quad Chart

Naomi Golin (2020-2021)
The Global Digital Divide: Electronic Colonization and Gender Inequalities
Mentor: Jeff Burke
Year: Junior
Major: International Development Studies

Around the world, technology is seen as a method of increasing gender equality, providing women the opportunity to receive an education and join the workforce. While this may be the case, however, women in developing nations are failing to achieve equality at the same rate as their global north counterparts. Following the independence of colonized nations, a development discourse has emerged pinpointing neoliberal globalization as the only path to achieving development. Scholars have argued, however, that this Western-dominated framework has caused nations in the global south to regress. The development of technology has further aggravated this, leading to postcolonial theorists to declare that we have entered a period of “electronic colonization”. Despite technology’s significance, however, scholarship has yet to be produced on how this inhibits gender equality. While early movements have argued how structural inequalities are a major barrier, modern investigations have yet to be undergone on how technological advancements play a role. Thus, the aim of my project is to investigate how the injection of technology in the form of aid is exacerbating gender inequalities in the education, healthcare, and work sector in developing nations. I will be focusing on three specific regions: India, Sub-Saharan Africa, and Latin America.

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.

Results: Miguel Gutierrez’ quad chart

Zifan He (2021-2022)
P2P File Backup on Data Transmission and Storage Trading
Mentor: Leonard Kleinrock
Year: Junior
Major: Computer Science

As the development of cloud storage leading by Google and iCloud, backup on Internet become more and more popular. However, it has several disadvantages. First and foremost, you have to pay for these services, which may be a significant budget when backing up large data file. Second, the speed of downloading your stored file is mainly dependent on the distance between cloud server (affect latency) and PC and the bandwidth. Third, privacy concerns still occur. In the proposed project, utilizing P2P technology, it is possible to store backups on the nearest computers, and upload/download process would be faster correspondingly. To download files, an idea similar to mapReduce can be used, where file segments can be processed between computers and aggregate onto user’s PC. Although there is a company called BuddyBackup working on the similar project, the proposal will focus on how to efficiently segregate files and distribute them, collect and combine files during download, and an ecosystem that allows users to trade unused disk storage. All of these have not been accomplished by BuddyBackup. If the project were accomplished, users can backup files with relative low price or even free, and the disk restoration would be quite fast.

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

 

Results: Michael Ho’s Quad Chart

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.

Results: HowardDemo, Canaan Howard’s Quad Chart

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

Results:  Ashley Hoffman’s Quad Chart

Jason Huan (2020-2021)
Private Cryptocurrency Transactions Using Rollups
Mentor: Amit Sahai
Year: Senior
Major: Computer Science

My project provides the utility for anyone to send cheap private transactions on the Ethereum network using rollups. One issue that has been plaguing widely-adopted blockchain networks is the high transaction fees that can occur as a result of demand for block-space outpacing available bandwidth. Rollups are blockchain mechanisms that allow for transactions to happen off-chain, by having users deposit funds into a smart contract which is managed by a different set of nodes reaching consensus from the mainnet. These off-chain transactions are executed by having the users sign and broadcast the transactions to the rollup nodes, which then later batch the transaction data into merkle witnesses which are pushed to mainnet for finality. This allows for cheaper transaction costs as the inputs are stored on rollup nodes instead of mainnet ones, while still maintaining verifiability through the witnesses. My research looked into open-source zk-SNARK-based private transaction smart contracts to provide anonymity, and the process of deploying them to a rollup and creating an interface for them.

Results: Jason Huan’s final presentation

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.

Results: HuangDemo, Howard Huang’s Quad Chart

Megha Ilango (2020-2021)
Bias in Social Media Moderation and Evaluation of Bias Prevention Methods
Mentor: Ninez Ponce
Year: Senior
Major: Computer Science

Gender and racial disparities exist in schools, governments, and workplaces across the United States. In the past several years, social media platforms have increasingly played a role in political and advocacy based efforts to express views on or combat discrimination in the real world. However, both human and artificial intelligence based content and advertising moderation practices on such platforms have demonstrated bias based on content creators’ racial, gender, or political identities. In this study, I will conduct an analysis of existing literature to determine the scale and impact of algorithmic bias on internet platforms, and follow with a technical evaluation of various bias recognition and prevention methods. Using this research, I will recommend an appropriate technical and policy-based approach to combat social injustice caused by such algorithmic biases.

Results: Megha Ilango’s final presentation

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

Results: Ryou Kato’s Quad Chart

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.

Results: IngramDemo, Zoe Ingram’s Quad Chart

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

Results: David Khachatrian’s Quad Chart

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

Results: Annita Kuo’s Quad Chart

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.

Results: Daniel Seung Lee’s Quad Chart

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

Results:  Cheechee Lin’s Quad Chart

Olivia Loh (2021-2022)
Gesture-Controlled Automation for Remote Filmmaking
Mentor: Jeff Burke
Year: Senior
Major: Computer Engineering

Social distancing due to the pandemic poses a great challenge to the film industry, a highly social, collaborative, and practical field. Due to social-distancing regulations, film production teams have resorted to remote filmmaking to limit the number of people on set. This would allow for a majority of the crew to work from home, as remote filmmaking software facilitates high-quality end-to-end live streaming service. Nevertheless, there are still some limitations to remote filmmaking, such as the lack of direct interaction between filmmakers and the physical set. I would like to propose a project that can improve on existing remote filmmaking technology by introducing a gesture-control component to live streaming. Filmmakers can make hand signals through their webcam (interpreted by a gesture-recognition machine learning model) and certain equipment on set will react accordingly, as if the filmmakers were actually present at the set. Smart gesture control has not been fully incorporated in remote production as of now. Incorporating gesture control can bring more convenience to the workflow of the set, as the nature of filmmaking is literally “hands-on” and production crews often rely on direction through hand signals. Furthermore, such gesture-control automation technology can apply to and benefit many other fields that require remote work as well.

Natasha Lum (2019-2020)
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.

Results:  Natasha Lum‘s quad chart, Natasha Lum’s presentation

 

Ellen Mei (2019-2020)
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.

Results:  Ellen Mei’s Quad Chart

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 difficult 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.

Results: Angelo Mendoza’s quad chart

Ethan Mitchell (2019-2020)
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.

Results:  Liam Monninger’s Quad Chart

Results: 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.

Results: Inesa Navasardyan’s Quad Chart

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.

Results: David Nguyen’s Quad Chart

Niyati Patel (2016-17)

Mentor: Ellen Levy
Year: Senior
Major: Economics and Human Biology and Society

Researched the Internet of Things and Big Data’s impact on existing public infrastructure, workforce development and civic engagement in Los Angeles.

Elishka Patockova (2020-2021)

Social Implication of Online Anonymity in Quantum Networks
Mentor: Leonard Kleinrock
Year: Junior
Major: Mathematics of Computation

Quantum internet is one of the most exciting technologies being currently developed. As with every new technology, there are social consequences of its integration into daily life. As we approach the release of quantum internet, it is essential to address the moral issues it brings about in order to adequately guard, and possibly legislate, against undesirable use. There is a plethora of issues that yearn for attention but due to the impeccable encryption that quantum internet provides, complete anonymity immediately stands out. Because the properties of quantum bits can not be measured without changing their state, quantum information cannot be extracted from them without leaving a trace. This sharply contrasts with the system that is in place today: much of internet activity is traceable and, consequently, the deep web contains much of the world’s online data. How will the introduction of quantum internet change the behavior of whistle blowers, online criminality, and ordinary users? The large social phenomenon of anonymity which has been largely introduced by the contemporary internet will reach new heights with the introduction of quantum internet and it is vital to consider its consequences before it is widely used.

Results: Eliska Patockova’s final presentation

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.

Maya Raman (2021-2022)
Improved Load-Balancing Algorithms for efficient energy usage in Data Centers
Mentor: Rajit Gadh
Year: Junior
Major: Computer Science/Environmental Systems and Society

As the world’s use of the Internet increases, the data centers our daily actions rely on are using more and more energy. Most data centers only operate at less than 50% capacity, wasting energy that could be saved if idle servers were turned off. In my project, I want to explore the best load-balancing algorithms for data centers to serve requests efficiently and turn off unused machines to save energy, while maintaining an acceptable quality of service. I will split the algorithms into those used for large-scale (Google, Facebook, etc.) and small-scale data centers. While the topic of efficient load-balancing algorithms has been extensively studied, this project is unique because it explores the best algorithms for differently-scaled data centers, and considers the benefit of turning off machines. I will first conduct a literature review to determine these algorithms, and will then simulate them using CloudSim software with variables such as amount of traffic, amount of virtual machines, and amount of off servers, to determine which algorithms save the most energy for each type of data center. Finally, I will propose mechanisms for how data centers can implement these energy-saving changes based on their scale and load.

 

Emir Izat Rashid (2021-2022)

Misunderstood Information: Grassroots, Public Figures, and Behavioral Interventions in Misinformation.
Mentor: Amit Sahai
Year: Senior
Major: Applied Mathematics

Social media has transformed how societies communicate and interact with each other. Although social media undoubtably has led to great strides in connecting the world, it also ushered in an age of mass misinformation – shaping a significant component of public discourse largely based on untruthful claims. Contemporary literature on misinformation observed the spread of misinformation through two approaches, the bottom-up approach, i.e misinformation propagated by participatory actors, and the top-down approach, i.e misinformation spread by public figures or institutional actors. However, there is still an unclear methodology on measuring the impact of top-down involvement on grassroots driven misinformation or vice-versa, identifying key agents responsible for different forms of misinformation spread, and analyzing the impact of behavioral interventions on misinformation such as tagging some posts as harmful. This study will investigate these unanswered questions by integrating social network analysis and information retrieval techniques to :- a) observe the relationship between online discourse and user-based construction of social networks, b) identify key agents by measuring centralities on user-based social networks and their associated impacts on discourse, and c) evaluate the impact of behavioral interventions on social networks, whether it strengthens or weaken misinformation-driven networks.

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.

Results: Devin Reeh’s Quad Chart

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.

Results:  Sahen Rai’s Quad Chart

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.

Results: 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.

Results: Sydney Richter’s Quad Chart

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

Results: Shanmukha Srinivas’ Quad Chart

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.

Results: Avirudh Theraja’s Quad Chart

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.

Results: Nephele Troullinos’ Quad Chart

Suraj Vathsa (2020-2021)
Deep Learning models that can be used to provide preliminary diagnosis for respiratory conditions using audio recordings of breaths and coughs
Mentor: Lilian Corral
Year: Sophomore
Major: Computer Science

With the growth of 5G and the internet, the ability to stream data from remote parts of the globe is more possible than ever before. One such type of data could be audio recordings of coughs and breathing sounds of patients suffering from respiratory conditions in remote regions. With the help of deep learning models, one can tap into the potential that this data carries and help provide some preliminary diagnosis for these patients after which they can take the necessary steps to visit the nearest local hospital or be scheduled to meet with a pulmonologist remotely.

Audio recordings of breaths and coughs can be represented as succinct time-series data when sampled in blocks effectively. We can employ sequential deep learning models to create latent representations of these data points. Further, we can also employ convolutional models to create representations of MFCC plots (as has been done in prior works on the topic). This data can also be combined with demographics and air quality data to create latent representations that can then be subject to classification using a variety of deep learning and statistical machine learning models. Based on a literature review, the target tasks could be a classification of adventitious sounds or detection of obstructive or restrictive patterns which can then be associated with diseases. The model, once trained and tested can be deployed in the cloud and can be served as a simple mobile application to patients/primary care physicians.

Results: Suraj Vathsa’s final presentation

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.

Results:  William Whitehead’s Quad Chart

Results: Segmentation With Fovea-magnifying Warped Crops

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.

Results: Video of Rhiannon Wilson’s project

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

Results:  Kuan Hsuan Yeh’s Quad Chart

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.

Results: Charles Zaloom’s Quad Chart

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.

Results: Hongyi Zhang’s Quad Chart

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’s Quad Chart

Results: Pei Zhou’s 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.

Results: David Zhu’s Quad Chart