Center for Undergraduate Research in Viterbi Engineering (CURVE)

 

Overview

The Center for Undergraduate Research in Viterbi Engineering (CURVE) provides a centralized resource for undergraduate students to explore research opportunities in Viterbi. The goals of CURVE are to provide all Viterbi students access to research, prepare students to engage in research and mentoring communities, and provide funding for the experience.

CURVE matches Viterbi undergraduate students with research positions in labs. Students will be given the opportunity to assist faculty on a research project while receiving paid hourly wages for their work.

Program benefits, eligibility and requirements:

  • All Viterbi undergraduate students are eligible to apply.
  • Each undergraduate student funded by the program will receive hourly wages to help support their research positions, typically over two semesters.
  • Students will work 5-10 hours per week with a faculty advisor and/or PhD mentor.
  • Participating students will present their research at the Viterbi Research Symposium.
  • Additional benefits include professional development seminars on topics such as conducting literature reviews, delivering effective presentations, designing technical posters, best practices in research, writing scientific abstracts, applying to PhD programs and more.

Important Note
Due to current COVID-19 restrictions, undergraduate research must be conducted remotely. Students currently residing outside of the United States are not eligible to apply for funding.

How to Apply

Next Steps

  • Read through the Overview and FAQs to learn about CURVE.
  • Read through the Research Positions to determine which ones interest you the most.
  • Attend as many Faculty information sessions as you like in order to find out more information about specific research projects (check back the week of September 7th for dates and times under Faculty Information Sessions).
  • Make sure to apply by the September 20th deadline.

Timeline

September 4 Application Opens

September 11 Faculty-led Research Info Session

September 18 Faculty-led Research Info Session

September 20 Application Deadline

Week of September 28 – Award Notifications Sent

CURVE will facilitate the matching process between you and an open research position. To help you decide which lab you would like to apply for, be sure to attend the faculty-led information sessions where you can learn about the research projects and the role of  undergraduate research assistants. These info sessions will also give you a chance to ask questions and talk with faculty (virtually!) face-to-face before applying for the position.

  • Information sessions will be held on Friday, September 11th, and Friday, September 18th. You are welcome to attend as many sessions as you like. Please note some sessions may be running concurrently. 
  • Check back the week of September 7th for the zoom links and calendar of information sessions.

CLICK TO APPLY

Research Positions

Aerospace and Mechanical Engineering Department

Project Titles

Virtual Experiments on Low Reynolds Number Wings

Lab: Dryden Wind Tunnel

Faculty Mentor: Geoffrey Spedding

Research Project Description: We will examine various software solutions to investigating the effect of shape on wing performanxce at small scale.  Most simple codes break down at some minimum Re and we will compare apparent solutions wityh existing experimental data.

Develop rapid control system development framework

Lab: Aircraft Dynamics, Controls, and Cooperation Lab

Faculty Mentor: John McArthur

Research Project Description: We will work on designing a framework in Matlab for determining gains for setting control system to match desired aircraft dynamics.

Development of real-time flight simulator for flexible body aircraft

Lab: Aircraft Dynamics, Controls, and Cooperation Lab

Faculty Mentor: John McArthur

Research Project Description: We will use Git and C++ and/or SImulink to develop a real time flight simulator capability for demonstration purposes. This will include visualizations of the dynamics.

Value function maximization for waypoint placement

Lab: Aircraft Dynamics, Controls, and Cooperation Lab

Faculty Mentor: John McArthur

Research Project Description: Placing waypoints for optimal acquisition of value across a number of entities.

*Not accepting freshmen at this time

Robotic Hand with Variable Compliance

Lab: Center for Advanced Manufacturing

Faculty Mentor: Satyandra Gupta

Research Project Description: This project is focussed on developing a robotic hand for performing material handling and assembly tasks. This hand will have variable compliance to ensure safety and be able to exert force to manipulate heavy objects. The goal is to develop a low-cost design that can be easily deployed on factory floors.

Website: http://cam.usc.edu/

*Not accepting freshmen at this time

Machine Learning for Improving Outcomes in Healthcare

Lab: Computation and Data Driven Discovery

Faculty Mentor: Asasd Oberai

Research Project Description: I am looking for students with interest and background in machine learning and deep learning to develop and apply algorithms to improve outcomes in healthcare. These include (a) better diagnosis of renal cancer, (b) better predictions of the benefits of surgery in bladder cancer, (c) prediction of the severity of COVID-19 based on initial medical biomarkers, and (d) development of new algorithms that require less data.,

Website: https://sites.usc.edu/oberai/

Learning and Control of Legged Robots

Lab: Dynamic Robotics and Control Laboratory

Faculty Mentor: Quan Nguyen

Research Project Description: We have several open positions on reinforcement learning, robot control, and robot design of legged robots.

Website: https://sites.usc.edu/quann/
*Not accepting freshmen at this time

Mathematical modeling and engineering devices to COVID-19 response; Fluid transport experiments and simulations related to glaucoma

Lab: Transport processes in biological and integrated systems. Implantable medical devices

Faculty Mentor: Anita Penkova

Research Project Description: 1. Design of medical devices, masks and respirators;

  1. Finger tracking technology
  2. Remote monitoring of patients
  3. Convection based perfusion experiments and modeling in ex-vivo and in-vivo animal models

Website: https://viterbi.usc.edu/directory/faculty/Penkova/Anita
*Not accepting freshmen at this time

Microstructure-Property Relations in Materials

Lab: Solids and Materials Labs

Faculty Mentor: Professor Renuka Balakrishna

Description: Every few years, we notice a drop in our phone’s battery capacity, we run out of memory storage space on laptops, and we observe a decline in the processing power of our computers. Eventually, we need to replace these devices, which is not only expensive but also depletes earth’s reserves of rare elements. Researchers have discovered materials with enhanced performance, either by chemical synthesis of new compounds and/or computational prediction of new materials. Despite these advances, our technological needs are outpacing research and development in energy and electronics industries, making it important to find novel ways of enhancing material properties and lifespans. As an alternative to chemical synthesis and computational predictions, we engineer material microstructures and crystallography to improve its reversibility and energy storage capacity. We use a combination of theory and computation to investigate microstructure-property relations in materials. 

Website: https://ananyabalakrishna.github.io/

*Not accepting freshman at this time

Astronautics and Space Technology Department

Project Titles

Hydrogen Powered Urban Aerial Mobility

Lab: Anita Sengupta

Faculty Mentor: Anita Sengupta

Research Project Description: Urban Air Mobility is an up and coming sector of transportation around the globe. Existing electric aviation platforms have explored the use of batteries for stored energy resulting in very limited range platforms. We will explore the use of hydrogen fuel cells to power electric aircraft. Specifically a systems engineering study of of aircraft performance and optimization of its design for a hydrogen based power plant.

Sonic Boom Mitigation by Compression Wave Reflection Techniques for Commercial Supersonic Aircraft

Faculty Mentor: Anita Sengupta

Research Project Description: A method for sonic boom mitigation has been proposed to NASA ULI call that utilizes wing placement relative to engine nacelle exhaust to reflect the primary wing compression shockwave. A supersonic experimental program is proposed to quantify parametric dependencies, explore fundamental physics, and inform the design of technology that can be implemented on commercial aircraft. The proposed effort will validate CFD simulations to enable computer aided design, optimization, and assessment of far field affects, i.e. acoustic disturbance on the ground.

*Not accepting freshmen at this time

Computational Studies in Astronautical Engineering

Lab: Simulations of Spacesuit Charging/Discharge on Lunar Surface/Simulations of Spacecraft Contamination and Spacecraft-Plasma Interactions

Faculty Mentor: Joseph Wang

Research Project Description:Simulations of Spacesuit Charging/Discharge on Lunar Surface. The objective of this study is to investigate charging and electrostatic discharge risks for astronauts at the lunar terminator and far-side.
2) Simulations of Spacecraft Contamination and Spacecraft-Plasma Interactions. The objective of this study is to quantify plasma interaction and self-contamination effects for spacecraft under various orbital environments and operation scenarios.

Biomedical Engineering Department

Project Titles

Signal Processing for Optical Coherence Tomography Imaging of the Ear

Lab: Applegate Research Group

Faculty Mentor: Brian Applegate

Research Project Description: Several signal processing projects are available. One is to implement digital adaptive optics approaches to enhance the image quality in Optical Coherence Tomography images of the cochlea. These digitally compensate for the aberration induced by the optical system and sample. Another is to develop digital windowing techniques to improve the axial (depth) resolution of the imaging system. We are using a window averaging approach to optimize the trade-off between axial resolution and signal side-bands. Finally, we are implementing statistical approaches to measuring blood flow for high-resolution angiography in the ear.

Website: applegatelab.org

Improving MATLAB Code for Traction Force Microscopy Analysis of Engineered Cardiac TIssues

Lab: Laboratory for Living Systems Engineering

Faculty Mentor: Megan McCain

Research Project Description: The students will work together to optimize and improve our existing MATLAB code for analyzing contractile forces generated by engineered cardiac tissues. The students will then use the code to help analyze data collected by postdocs and graduate students in the lab,

Website: livingsystemsengineering.usc.edu

*Not accepting freshmen at this time

Design and Evaluation of Orthopaedic Implants

Lab: J. Vernon Luck, Sr. Orthopaedic Research Center

Faculty Mentor: Edward Ebramzadeh Abrams

Research Project Description: Design, Evaluation, Development and Preclinical testing of Orthopaedic Implants, devices and instrumentation, including fracture fixation devices, devices for soft tissue repair, and joint replacement devices for arthroplasty.

Website: jvlresearch.org

*Not accepting freshmen at this time

Sleep-related disordered patterns of breathing in children with Down Syndrome

Lab: Cardiorespiratory Sleep Lab

Faculty Mentor: Michael Khoo

Research Project Description: Almost 60% of children with Down Syndrome (DS) develop symptoms of obstructive sleep apnea (OSA) by the time they are 4 years old. Even though many of these individuals undergo surgical treatment through removal of their tonsils or adenoids, OSA persists in a large proportion of them.  Those who are prescribed continuous positive airway pressure therapy are generally not compliant. Working with our clinical collaborators at Children’s Hospital Los Angeles, we are employing bioengineering techniques to determine whether supplemental oxygen delivered via nasal cannula can improve OSA severity in DS individuals.

Website: https://www.crsl.usc.edu

*Not accepting freshmen at this time

Multi-Scale Modeling of the Hippocampus for Electrical Stimulation

Lab: Institute for Technology and Medical Systems Innovation (ITEMS)

Faculty Mentor: Professor Jean-Marie Bouteiller

Research Position Description: A multi-scale computational model of the hippocampus is being developed to help us better understand the impact of electrical stimulation on neurons. Though the field of neural prostheses such as deep brain stimulation devices have shown great clinical success, there is a lack of fundamental understanding on how electrical stimulation affects the activity of a neural population and neural circuits. To address this gap in understanding, the model of a rat hippocampus is being developed to predict spiking neural response to extracellular electrical stimulation caused by implanted electrodes. The admittance method is used to simulate the electrical field in the brain created by stimulation and heterogenous tissue properties. The NEURON simulation environment is then used to simulate the subsequent neural response. Within this environment, individual neurons are represented using compartmental models with realistic morphologies and biophysics.

Website: https://itemsusc.org/

Civil and Environmental Engineering Department

Project Titles

Water desalination and wastewater reclamation

Lab: Childress

Faculty Mentor: Amy Childress

Research Project Description: tbd – I am happy to work with student and see where their interests intersect with my research team projects

Website: amyechildress.com

Climate and air pollution

Lab: Climate and air pollution lab

Faculty Mentor: George Ban-Weiss

Research Project Description: Various projects related to climate change and air pollution from neighborhood to global scales

Website: https://sites.usc.edu/banweiss/

Statistical predictions and machine learning

Lab: uncertainty quantification group

Faculty Mentor: Roger Ghanem

Research Project Description: In my group we develop predictive models for complex systems. Here are examples of a few recent applications:

  1. from observing the micro constituents of a composite material, assess the overall stress of the material.
  2. conversely, from observing the overall strength, assess the properties of micro constituents.
  3. from observing the number of COVID-19 cases over a the past week period, predict the number of cases over the following week.
  4. from observation of flow inside a jet engine under one set of laboratory conditions, predict the flow under operational conditions.
  5. from observation of oil slick size and spread along the Gulf Coast, assess the size of an offshore oil spill and its l likely social consequences.

We are extending the above capabilities to be more accurate, more useful, and applicable to a broader set of problems.

Website: http://hyperion.usc.edu

Root-cause analysis of Covid-19 and World Health Organization organizational system failures

Lab: Meshkati Complex Systems Research Group

Faculty Mentor: Najmedin Meshkati

Research Project Description: We have been working on two intertwined, related projects:

1- Investigating the Origins of the Covid-19 Outbreak Using AcciMap Framework: Safety records and lapses at the BSL-4 facilities and possible accidental release from the Wuhan Institute of Virology

2-A Root-Cause Analysis of the World Health Organization’s (WHO) organizational systems failures and their impact on the COVID-19 pandemic using the AcciMap Framework.

Website: https://viterbi-web.usc.edu/~meshkati/

Chemical Engineering and Materials Science Department

Project Titles

Optical materials and diagnostics

Lab: Armani Lab

Faculty Mentor: Andrea Armani

Research Project Description: Develop advanced materials and integrated optical devices that can be used in portable disease diagnostics and telecommunications.

Website: https://armani.usc.edu/

*Not accepting freshmen at this time

Advanced Oxide and Chalcogenide Materials for Electronics, Photonics and Energy Applications

Lab: Laboratory for Complex Materials and Devices

Faculty Mentor: Jayakanth Ravichandran

Research Project Description: Our group is interested in developing new materials for electronic, photonic and energy technologies. For example, we are interested in developing new chalcogenides that can be ultrathin and still be able to absorb the solar spectrum for producing electricity (solar cells), and also as efficient photodetectors etc. We use a variety of growth and characterization methods to understand these materials including several advanced thin film growth methods.

Website: http://alchemy.usc.edu

Catalyst design using quantum chemistry and machine learning

Lab: Sharada lab

Faculty Mentor: Shaama Mallikarjun Sharada

Research Project Description:

Website: https://sharada-lab.usc.edu/

Smart 3D Printer and AI Enabler

Lab: AI for Manufacturing

Faculty Mentor: Qiang Huang

Research Project Description: Build an AI-enabled smart 3D printers with self-learning and correction capabilities for precision 3D printing

Website: huanglab.usc.edu

Gerontology Department

Project Titles

Brain MRI analysis, connectomics and machine learning for neuroscience knowledge discovery

Lab: Irimia Laboratory

Faculty Mentor: Andrei Irimia

Research Project Description: The past few decades have witnessed remarkable progress on elucidating the disease mechanisms of the aging brain. Imaging now facilitates mapping of neural network dynamics in exquisite detail, with noteworthy consequences for medicine and society. We are a group of interdisciplinary scientists who leverage neuroimaging, electrophysiology, machine learning, and computational approaches to study brain aging and degeneration in traumatic brain injury, Alzheimer’s disease and related dementias. The laboratory has made contributions to mapping the reorganization and of brain connections after trauma and to understanding the relationship between neural injury and Alzheimer’s disease. The laboratory seeks motivated undergraduate students interested in contributing to this exciting field of knowledge at the frontier of neuroscience.

Website: www.andrei-irimia.com

Computer Science Department

Project Titles

Optical materials and diagnostics

Lab: ACT Lab

Faculty Mentor: Nora Ayanian

Research Project Description: Coming up with control or output trajectories that are provably safe in partially known dynamic environments is a central problem for multi robot teams. To solve this problem, we developed a real-time trajectory re-planning algorithm for cooperative multi robot teams. We want to extend the implementation(in C++) of our algorithm within this project.

Website: act.usc.edu

LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation

Lab: Intelligent and Knowledge Discovery Research (INK) Lab

Faculty Mentor: Xiang Ren

Research Project Description: We introduce an open-source web-based Label Efficient AnnotatioN framework for sequence labeling and classification tasks. Our framework enables annotator to provide labels for a task, but also enables LearnIng From Explanations for labeling decision with an easy-to-use UI.

LEAN-LIFE differentiates itself from other frameworks in these ways:

  1. Improved Model Training: Leveraging annotator-provided-explanations to weakly label unlabeled instances, our framework is able to train models with fewer data-points and improve model performance; hence reducing future annotations costs via better recommendations.
  2. Multiple supported tasks: We support both sequence labeling (named entity recognition) and sequence classification (relation extraction, sentiment analysis) tasks. All tasks can incorporate our improved model training if the annotator wishes so.
  3. Explanation dataset creation: We enable the building of a new type of dataset, one that consists of triples of: text, labels, and labeling explanations. We have shown improvements in common NLP tasks using these triples and hope the community will build upon our work by utilizing these triples.

Website: http://inklab.usc.edu/hiexpl/

Post-hoc Explanation Demo for Deep Learning Models in Natural Language Processing Lab: Intelligent

Lab: Intelligent and Knowledge Discovery (INK) Research Lab

Faculty Mentor: Xiang Ren

Research Project Description: We will develop a web demo for “model interpretation”, a system that explains to users how a black-box Natural Language Processing (NLP) model, such as sentiment analysis or hate speech detection model, reaches its predictions. The system aims at providing an easy-to-use interface for even layman users to understand model predictions and analyze harmful model behaviors.

Website: http://inklab.usc.edu/hiexpl/

Machine Commonsense Reasoning

Lab: Intelligent and Knowledge Discovery (INK) Research Lab

Faculty Mentor: Xiang Ren

Research Project Description: We are recruiting undergraduate students for developing a website for demonstrating our research projects on “machine commonsense reasoning” (https://www.darpa.mil/program/machine-common-sense). We aim to use the website to show we build our systems and resources that can make machines think as humans with commonsense knowledge.

The website will include the introduction, the demo application, competition leaderboard (if applicable), with decent visualization. Most of the pages will be static except for the demonstration and leaderboard pages. The main textual content of the introduction will be provided.

Website: https://inklab.usc.edu/CommonGen/

Computational Socially Assistive Robotics

Lab: Interaction Lab

Faculty Mentor: Maja Mataric

Research Project Description: Interaction Lab is a pioneer of socially assistive robotics: developing systems capable of aiding people through social interactions that combine monitoring, coaching, motivation, and companionship. The research focuses on the development of human-robot interaction algorithms (involving control and learning in complex, dynamic, and uncertain environments by integrating on-line perception, representation, and interaction with people) and software for providing personalized assistance in convalescence, rehabilitation, training, and education. To address the inherently multidisciplinary challenges of this research, the work draws on theories, models, and collaborations from neuroscience, cognitive science, social science, health sciences, and education.

Website: https://research.usc.edu/covid19-rampup/

Cognitive Learning for Vision and Robotics Lab

Lab: CLVR

Faculty Mentor: Joseph Lim

Research Project Description: The Cognitive Learning for Vision and Robotics lab (CLVR) at the University of Southern California is led by Professor Joseph J. Lim. Our goal is to develop intelligent systems that are capable of not only perceiving the world but also reasoning and interacting with it. We are especially interested in building a cognitive model that can learn to make plausible decisions given multi-modal data from the surroundings. Our research spans topics like robotics, computer vision, reinforcement learning, and deep learning.

Website: https://www.clvrai.com/

Multi-Agent Path Planning

Lab: Intelligent Decision Making Lab

Faculty Mentor: Sven Koenig

Research Project Description: Consider several agents (such as robots or game characters) that need to move from their current locations on a grid with blocked and unblocked cells to given goal locations without obstructing each other. This problem is faced by warehouse robots (like those from Amazon Robotics, that are used in the warehouses of Amazon) and requires path planning but, different from single-agent path planning, is NP-hard to solve optimally and thus requires extremely smart algorithms to result in good performance, see mapf.info for more information. We are looking for students who are interested in helping us to develop the next generation of such algorithms. (This is not a robotics project and does not use robot hardware. Rather, it uses a gridworld simulation where each robot can move in one of the four main compass directions.)

Website: http://idm-lab.org/project-p.html

*Not accepting freshmen at this time

Garage

Lab: Robotic Embedded Systems Lab

Faculty Mentor: Gaurav Sukhatme

Research Project Description: garage is a toolkit for developing and evaluating reinforcement learning algorithms, and an accompanying library of state-of-the-art implementations built using that toolkit.

The toolkit provides wide range of modular tools for implementing RL algorithms, including:

Composable neural network models

Replay buffers

High-performance samplers

An expressive experiment definition interface

Tools for reproducibility (e.g. set a global random seed which all components respect)

Logging to many outputs, including TensorBoard

Reliable experiment checkpointing and resuming

Environment interfaces for many popular benchmark suites

Supporting for running garage in diverse environments, including always up-to-date Docker containers

Website: https://github.com/rlworkgroup/garage#garage

*Not accepting freshmen at this time

Community Framework for Enabling Scientific Workflow Research and Education

Lab: SciTech

Faculty Mentor: Rafael Ferreira da Silva

Research Project Description: Scientific workflows are a cornerstone of modern scientific computing. They are used to describe complex computational applications that require efficient and robust management of large volumes of data, which are

typically stored/processed at heterogeneous, distributed resources. The workflow research and development community has employed a number of methods for the quantitative evaluation of existing and novel workflow

algorithms and systems. In particular, a common approach is to simulate the execution of actual or synthetic workflows. In this work, we target the development of WorkflowHub, a community framework that provides a

collection of tools for analyzing workflow execution traces, producing realistic synthetic workflow traces, and simulating workflow executions.

Website: https://workflowhub.org

ML and Optimization for ``AI in Society`` Projects

Lab: USC Center for AI in Society

Faculty Mentor: Bistra Dilkina

Research Project Description: USC Center for AI in Society has several research projects that can successfully engage undergraduates:

1) Using ML to predict key factors driving Substance Use and Relapse: skillsets required are Machine Learning, Python, Data Cleaning

2) Using ML and Optimization to inform Wildlife Conservation: skillsets required are geospatial data processing and visualization (mapping and web interface), literature review on wildlife poaching and camera traps

3) DL for Satellite Data: projects around land cover mapping, disasters

4) Optimization for Sustainable Water Systems – skillsets required are Genetic Algorithms and Python

5) COVID-19 Testing sites optimization (help LA decide better where to open additional testing sites to provide equitable and fair coverage for at risk and vulnerable communities): skillsets require are Web Interface for Map data, data scraping, ML, Python

6) Disaster resilience of critical infrastructures: build data that help urban planners decide where to upgrade water and transportation infrastructure for earthquake and flooding disasters: skillsets required are geospatial data processing, machine learning or algorithms, Python

Website: https://cais.usc.edu/projects/

Various Distributed Machine Learning Projects

Lab: SCIP Lab

Faculty Mentor: Murali  Annavaram

Research Project Description: Various projects on distributed machine learning relating to security and privacy of machine learning, high performance computing

Website: scip-lab.usc.edu

*Not accepting freshmen at this time

Human centered Signal Processing and Machine Intelligence Research and Applications

Lab: Signal Analysis and Interpretation Laboratory

Faculty Mentor: Shrikanth (Shri) Narayanan

Research Project Description: The Signal Analysis and Interpretation Laboratory (sail.usc.edu) has several interdisciplinary research projects that are ongoing that welcome undergraduate researchers as a part of the teams. Three specific research teams with openings include

  1. Computational Media Intelligence (MICA) [sail.usc.edu/mica]

R&D on a  wide variety of media related tasks including the analysis of media content (film, television, ads, music)  to answer questions ranging from representations and portrayals of individuals, and their interactions, especially from a diversity and inclusion lens, to understanding the impact on people (e.g., emotions, behavior trends) and society  (e.g.., predicting commercial impact/outcome of content).

  1. Behavioral Machine Intelligence for Health [sail.usc.edu/bsp; sail.usc.edu/care]

R&D on a variety of topics in signal processing and computing related to health research and applications in domains such as Autism, Depression, and Addiction

  1. Speech Production and Articulation Knowledge Group [sail.usc.edu/span]

R&D on novel imaging and modeling of human speech and song production, and applications in biometric and speech recognition technology development, and clinical applications (head/neck cancer).

Website: sail.usc.edu

Interaction-aided robot sensing, locomotion and navigation

Lab: RoboLAND

Faculty Mentor: Feifei Qian

Research Project Description: The project explores how robots can exploit different features of their physical environments to achieve desired movements. Can multi-legged robots and snake-like robots intelligently collide with obstacles on purpose to robustly move towards desired directions? Can a robot effectively turn itself by jamming the soft sand with its tail? In this project we will perform robot locomotion experiments to understand the complex interactions between robots and their environments, and use these interaction models to create novel strategies that can enable effective locomotion and navigation through challenging environments

Website: https://viterbi.usc.edu/directory/faculty/Qian/Feifei

Artificial Intelligence and Operations Research for Social Good

Lab: Data-Driven Decision-Making Research Group (part of Center for AI in Society)

Faculty Mentor: Phebe Vayanos

Research Project Description: We have three undergraduate research positions available in our group. The three successful applicants will be working on projects related to: a) fairness and robustness in machine learning with applications to housing policy design for people experiencing homelessness (2 positions), or b) biodiversity conservation to save species at risk of becoming extinct (1 position).

Website: https://sites.google.com/usc.edu/phebevayanos/

Interactive and Collaborative Autonomous Robotics lab

LabInteractive and Collaborative Autonomous Robotics lab

Faculty Mentor: Stefanos Nikolaidis

Research Project DescriptionThe mission of the Interactive and Collaborative Autonomous Robotics lab is to enable robots help people with everyday tasks. Our research reflects the belief that physical interaction is deeply entangled with robot intelligence. We focus on developing compact, flexible representations that capture the vast amounts of information that robots acquire by actively engaging in real-world interactions with humans and objects in the environment and by passively observing the vast amount of available online content. These representations are the building blocks of human-interpretable, executable programs that enable deployed robotic systems perform complex manipulation tasks for and in coordination with actual end-users.

Website: http://icaros.usc.edu/

Probabilistic AI Models for Understanding Human Discourse

Lab: JAUNTS
Faculty Mentor: Dr. Jay Pujara
Position Project Description: Humans communicate in rich, complex, and interesting ways that challenge the capabilities of traditional AI. The JAUNTS lab is working on cutting-edge techniques that understand the patterns of human communication, in various domains including American Sign Language (ASL), summarization of complex numerical datasets, or explaining scientific decision making. In each of these domains, an important consideration is *sense-making*: generating language that is coherent for the receiver. Coherency has long been a strength of probabilistic models which capture the deep interactions between pieces of information. Our group uses the latest language modeling techniques from the deep learning community alongside rich, scalable models built using probabilistic soft logic (PSL). Together, these techniques have created state of the art results in numerous tasks.

Website: https://www.jaypujara.org

Information Sciences Institute

Project Titles

A Framework for Enabling Encapsulating, Testing and Maintaining Scientific Software

Lab: Interactive Knowledge Capture and Discovery

Faculty Mentor: Daniel Garijo

Research Project Description: Scientific software is a key asset for reproducible scientific research, as it helps understand how a data product has been created or manipulated as part of a computational experiment or simulation. In this project, undergraduate students will learn AI techniques and expand our work to use existing scientific software 1) Analyzing and identifying current practices in scientific software repositories with respect to standard practices in Software Engineering; 2) Collaborating in the design and implementation of intelligent assistants and diagnosis tools to help scientists maintain and adopt best practices in their repositories (e.g., having releases to version their progress, proper separation and description of input/output, availability of test data, etc.) 3) Helping design an automated testing environment for maintaining scientific software and 4) Analyzing code automatically to find similarities among different scientific software. Students will be exposed to machine learning, data science, semantic Web, software engineering best practices and learn on reproducible research

Data Driven Cybersecurity (multiple projects)

Lab: Data Driven Cybersecurity @ ISI

Faculty Mentor: Jeremy Abramson

Research Project Description: The Data Driven Cybersecurity @ ISI group is looking for talented researchers to assist with the following projects:

 

Social Graph Analysis and Attribution of Software Exploit Contributors Using GitHub:

Attribution of threat actors is an increasingly important and difficult problem. One potential mitigation is the early detection of potential threat actors via analysis of open-source intelligence (OSINT). This project will analyze the social graph of users who contribute to, follow, star, and otherwise interact with proof-of-concept CVE implementations and other relevant potentially malicious (e.g. software vulnerability) repositories. Attribution of threat actors is an increasingly important and difficult problem. One potential mitigation is the early detection of potential threat actors via analysis of open-source intelligence (OSINT). This project will analyze the social graph of users who contribute to, follow, star, and otherwise interact with proof-of-concept CVE implementations and other relevant potentially malicious (e.g. software vulnerability) repositories.

 

Integration of Frame Semantics to Cyber Ontologies

Cyber ontologies such as STIX and ATT&CK can represent complex relationships between cyber threat actors, attacks and infrastructure.  While such representations are conducive to interoperability between systems, they are often unwieldy for human cyber analysts to deal with directly.  Conversely, Natural language generation (NLG) frameworks like FrameNet represent language in a structured manner, but frame specifications are often not specific enough for specialized domains (such as cyber security).  Leveraging and combining the semantic structure of both forms can create a tool that can translate cyber threat data in standard interoperable formats (such as STIX) to human-readable reports, via existing NLG frameworks.  Working on a project such as this provides an opportunity for significant impact, as the fusion of these two structures could greatly increase both the adoption and the utility of cyber threat ontologies.

 

Social Network Expansion: Construction of a human-subject spearphishing experiment:

Social Network Expansion (SNE) aims to explore the relationship between various factors of “cost” in creating social networking personas, and these personas’ efficacy in connecting and interacting with a target populace.  A more complete understanding of this relationship between required adversarial complexity/resources and connection/interaction efficacy will enhance our ability to detect and mitigate a number of threats, including (but not limited to) spearphishing, persona hijacking and the spread of fake news.

 

Textual, Structural and Semantic Analysis of Phishing Datasets

Phishing attacks – both specifically and broadly targeted – are an increasingly dangerous vector for malice. Because of the textual and semantic similarities between potentially malicious and benign emails, detection of subtle phishing attacks can be difficult. This project aims to provide a high-level textual and structural analysis of different phishing datasets to determine what features in a conversational chain may be useful in increasing detection of phishing attacks. Students will work on textual extraction of features (intent, sentiment, tone, etc.) and analysis of externally verifiable content (company affiliation, etc.)

 

Detecting Malware Campaign Lifecycles from Behavioral Analysis:

This project aims to detect and coalesce families of malware articles and campaigns by analyzing their behavior and interactions with the outside world. Features such as network activity, system component interactions and others can be used to cluster malware articles and determine the duration of malware campaigns otherwise thought to be independent. Students will work on Exploration of open-source malware API contents (e.g. VirusTotal), construction of malware behavioral data set, generation of similarity metrics (network traffic access patterns, system interactions, etc.) and analysis and clustering of malware articles and campaigns.

Website: https://www.isi.edu/people/abramson/data_driven_cybersecurity_isi

*Not accepting freshmen at this time

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy

Lab: Duncan

Faculty Mentor: Dominique Duncan

Research Project Description: The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a large, international, multicenter Center without Walls (CWOW) addressing the pressing need for antiepileptogenic therapy. The project combines studies of animals and patients with traumatic brain injury (TBI) leading to post-traumatic epilepsy (PTE) to develop the techniques and patient populations necessary to carry out future cost effective full-scale clinical trials of epilepsy prevention therapies.

Website: epibios.loni.usc.edu

Disruptive space engineering, research, and education

LabThe Space Engineering Research Center

Faculty Mentor: David Barnhart

Research Project DescriptionThe Space Engineering Research Center (SERC) is a joint venture between two components of the University of Southern California —the Information Sciences Institute and the Department of Astronautical Engineering. The Center is dedicated to disruptive space engineering, research, and education–including hands-on build, test and flight demonstrations of spacecraft and satellites. SERC seeks to challenge traditional methods of space R&D, manufacturing, and exploration with approaches that dramatically reduce costs, enable novel capabilities, and support vital democratization of the space domain.

Website: https://www.isi.edu/centers/serc/home

Electrical and Computer Engineering Department

Project Titles

Accelerating in Cloud Covid prediction application of ML

Lab: FPGA Lab Data Science Lab

Faculty Mentor: Viktor Prasannah

Research Project Description: Use of FPGAs to accelerate privacy preserving computations on the cloud

Interface design for COVID forecasting tool

Evaluating ML algorithms for system design

Website: fpga.usc.edu  dslab.usc.edu

AutoDrive: Formal Reinforcement Learning for Autonomous Driving

Lab: USC AutoDrive Lab

Faculty Mentor: Rahul Jain

Research Project Description: The USC AutoDRIVE Lab co-directed by Profs. Jain and Nuzzo focuses on Intelligent Autonomy capabilities for autonomous driving. It aims to develop planning and control algorithms that are provably safe using AI, specifically reinforcement learning algorithms. The project’s scope includes (i) software development of AI algorithms and their testing in a driving simulator, (ii) testing of developed software on a ground robotic vehicle (hardware) platform in a scaled urban traffic environment, and (iii) mathematical theory and algorithms for intelligent autonomy.

Website: https://viterbi-web.usc.edu/~rahuljai/Welcome.html

Graph Signal Processing

Lab: Signal Transformation, Analysis and Compression Group

Faculty Mentor: Antonio Ortega

Research Project Description: Recently developed graph signal processing (GSP) methods allow us to sample or filter data defined on irregular domains (described as graphs). We have been applying GSP to various types of data, in the context of image, video, point cloud processing, sensor network or machine learning applications. There are several possible projects which will involve a specific GSP tools and application domains (e.g., graph construction for image denoising). This will be defined based on student interests.

Website: http://biron.usc.edu/wiki/index.php/Signal_Transformation,_Analysis_and_Compression_Group

Covid-19 misinformation, SARS-CoV-2 viral analysis, complex networks, machine learning and artificial intelligence

Lab: CPS Group

Faculty Mentor: Paul Bogdan

Research Project Description: We have multiple research activities and projects related to COVID-19.

Website: https://cps.usc.edu/

Design, Optimization and Verification of Complex Systems

Lab: Shahin Nazarian’s Lab

Faculty Mentor: Shahin Nazarian

Research Project Description: We do a broad range of topics from system/spec level down to layout, but in general most of the work is related to algorithm design and optimization to solve a hard problem; and possibly implementing it in hardware. Please check my list of publications since 2016 to get a better idea what we do.

Website: http://sportlab.usc.edu/~shahin/Research.html

Memristive Neural Networks for Artificial Intelligence

Lab: Yang Research Lab

Faculty Mentor: Joshua Yang

Research Project Description: In the project, we are trying to build neural networks based on emerging electronic devices (e.g. memristors) beyond traditional silicon based CMOS technology. Such artificial neural networks are especially good in dealing with huge amount of data in the era of ‘big data’ and Internet of Things (IoT). As the building blocks, i.e., memristors, can resemble the behavior of biological synapses, neurons and dendrites, such artificial neural networks is capable of mimicking how the brain works, resulting in something close to natural intelligence and orders of magnitude improvement in energy and throughput over the traditional digital computing systems.

Website: http://www.ecs.umass.edu/ece/jjyang/

*Not accepting freshmen at this time

Various Distributed Machine Learning Projects

Lab: SCIP Lab

Faculty Mentor: Murali  Annavaram

Research Project Description: Various projects on distributed machine learning relating to security and privacy of machine learning, high performance computing

Website: scip-lab.usc.edu

*Not accepting freshmen at this time

Human centered Signal Processing and Machine Intelligence Research and Applications

Lab: Signal Analysis and Interpretation Laboratory

Faculty Mentor: Shrikanth (Shri) Narayanan

Research Project Description: The Signal Analysis and Interpretation Laboratory (sail.usc.edu) has several interdisciplinary research projects that are ongoing that welcome undergraduate researchers as a part of the teams. Three specific research teams with openings include

  1. Computational Media Intelligence (MICA) [sail.usc.edu/mica] R&D on a  wide variety of media related tasks including the analysis of media content (film, television, ads, music)  to answer questions ranging from representations and portrayals of individuals, and their interactions, especially from a diversity and inclusion lens, to understanding the impact on people (e.g., emotions, behavior trends) and society  (e.g.., predicting commercial impact/outcome of content).
  1. Behavioral Machine Intelligence for Health [sail.usc.edu/bsp; sail.usc.edu/care] R&D on a variety of topics in signal processing and computing related to health research and applications in domains such as Autism, Depression, and Addiction
  1. Speech Production and Articulation Knowledge Group [sail.usc.edu/span] R&D on novel imaging and modeling of human speech and song production, and applications in biometric and speech recognition technology development, and clinical applications (head/neck cancer).

Website: sail.usc.edu

Interaction-aided robot sensing, locomotion and navigation

Lab: RoboLAND

Faculty Mentor: Feifei Qian

Research Project Description: The project explores how robots can exploit different features of their physical environments to achieve desired movements. Can multi-legged robots and snake-like robots intelligently collide with obstacles on purpose to robustly move towards desired directions? Can a robot effectively turn itself by jamming the soft sand with its tail? In this project we will perform robot locomotion experiments to understand the complex interactions between robots and their environments, and use these interaction models to create novel strategies that can enable effective locomotion and navigation through challenging environments

Website: https://viterbi.usc.edu/directory/faculty/Qian/Feifei

Use of Emerging Memory Technologies for Novel Circuit Design

Lab: Akhilesh Jaiswal

Faculty Mentor: Akhilesh Jaiswal

Research Project Description: Emerging memory technologies like magnetic RAM, phase change memory and resistive RAM provide high density storage as well as non-volatility. The project aims to use such emerging devices to build new circuits for storage as well as compute operations.

Website: https://www.isi.edu/research_groups/asic/asic

*Not accepting freshmen at this time

Self-Driving Vehicle Testbed

Lab: Cyber-Physical System Design Lab (DesCyPhy)

Faculty Mentor: Pierluigi  Nuzzo

Research Project Description: The goal of this project is to build a software testbed to simulate or emulate realistic scenarios for self-driving vehicles and test the effectiveness of different driving algorithms. The testbed will target a traffic intersection and will include a set of scaled-down autonomous cars, a programmable traffic light sequencer to emulate the traffic and pedestrian signals, and a set of robots to emulate pedestrian traffic.

Website: https://descyphy.usc.edu/

Modeling Human Speech Production

Lab: Speech Production and Articulation Knowledge Group

Faculty Mentor: Asterios Toutios

Research Project Description: The undergraduate student will work on aspects of modeling human speech production on the basis of real-time MRI data of speech production. Our interests are on mappings between three modalities: I) speech audio (what we hear); ii) movements of speech articulators (how our tongues and lips move); iii) hypothesized cognitive language representations (the mental “programs” and “data structures” that are involved in the process). We will be exploring both machine learning mappings and more traditional knowledge-based ones.

Website: http://span.usc.edu

Methods and tools to accelerate discoveries

Lab: Methods and tools to accelerate discoveries

Faculty Mentor: Sandeep Gupta

Research Project Description: Applying our methods for discovery to new problems in digital hardware and software design. Our methods include a range of tools to help accelerate discoveries.

Fast electrodynamics solvers

Lab: Photonics in Complex Systems

Faculty Mentor: Professor Hsu

Project Description: Maxwell’s equations govern all electromagnetic waves. Efficient solvers for Maxwell’s equations are critical for state-of-the-art nanophotonic designs, imaging in complex/biological media, and many other applications. The student will help the development and benchmark of new Maxwell solvers that are capable of solving a massive number of electrodynamics problems simultaneously.

Website: https://sites.usc.edu/hsugroup/

Industrial and Systems Engineering Department

Project Titles

Creating the Innovative University

Lab: Randolph Hall

Faculty Mentor: Randolph Hall

Research Project Description: A national survey will be conducted in September among students affiliated with the Blackstone Launchpad program.  Students will be asked about their views on innovation culture within their universities, both respect to support provided to student entrepreneurs, and the receptivity of the institution to student views on innovation in university practices, particularly in education related programs.  The study aims to assess how universities support innovation as a comprehensive strategy.

Website: https://www.researchgate.net/profile/Randolph_Hall

*Not accepting freshmen at this time

Integrated Modeling of Healthcare Capacity and Patient Needs to Intervene Against Human Transmitted Viral Disease

Lab: Randolph Hall

Faculty Mentor: Randolph Hall

Research Project Description: The Covid-19 pandemic has challenged the world to reduce the presence and consequence of a highly contagious and severe disease, in the absence of vaccines and effective medical treatments.   Aggressive measures to isolate populations, and restrict movement, aim to reduce the number of Covid-19 cases, and to spread such cases over a longer period of time.  A benefit of this strategy is to reduce the rates at which patients present at hospitals for care, so that hospitals are better able to accommodate the flow of Covid-19 patients (i.e., so-called ⬠Sflattening the curve⬠_ so that the number of cases does not exceed hospital capacity).   The project will develop a comprehensive patient flow model to represent the interaction between the transmission of disease and the delivery of healthcare for afflicted patients.  We recognize that in a crisis strategies exist to dynamically supplement hospital capacity (e.g., transforming spaces to add bed capacity, expanding scope of responsibility, acquiring resources, optimizing discharge, etc.), diverting patients or

Website: http://covid19datasource.com/

*Not accepting freshmen at this time

Artificial Intelligence and Operations Research for Social Good

Lab: Data-Driven Decision-Making Research Group (part of Center for AI in Society)

Faculty Mentor: Phebe Vayanos

Research Project Description: We have three undergraduate research positions available in our group. The three successful applicants will be working on projects related to: a) fairness and robustness in machine learning with applications to housing policy design for people experiencing homelessness (2 positions), or b) biodiversity conservation to save species at risk of becoming extinct (1 position).

Website: https://sites.google.com/usc.edu/phebevayanos/

Digital Health Impact on Patient Safety and Quality of Care

Faculty Mentor: Yalda Khashe

Research Project Description: Digital health has been a developing area of healthcare delivery in recent years and the COVID-19 pandemic has significantly accelerated its expansion. Patient safety, as a major aspect of quality of care, is a top priority for healthcare delivery systems. However, addressing patient safety in virtual, or digitally delivered, care is not yet commensurate with the rapid growth of digital health driven by COVID-19. This research project is dedicated to providing comprehensive insight into the potential impacts of digital healthcare delivery on patient safety and unintended consequences.

Smart 3D Printer and AI Enabler

Lab: AI for Manufacturing

Faculty Mentor: Qiang Huang

Research Project Description: Build an AI-enabled smart 3D printers with self-learning and correction capabilities for precision 3D printing

Website: huanglab.usc.edu

Time Series Clustering - Survey Paper

Faculty Mentor: Bruce Wilcox

Research Project Description: Research and co-author an academic paper on the clustering of time series for submission for publication to ACM Computing Surveys or similar journal.  Based on and extending work done on my PhD thesis published in 2018.

Root-cause analysis of Covid-19 and World Health Organization organizational system failures

Lab: Meshkati Complex Systems Research Group

Faculty Mentor: Najmedin Meshkati

Research Project Description: We have been working on two intertwined, related projects:

 

1- Investigating the Origins of the Covid-19 Outbreak Using AcciMap Framework: Safety records and lapses at the BSL-4 facilities and possible accidental release from the Wuhan Institute of Virology

 

2-A Root-Cause Analysis of the World Health Organization’s (WHO) organizational systems failures and their impact on the COVID-19 pandemic using the AcciMap Framework

 

The following remarkable students have been working with me since mid June 2020 on the above projects and they have indicated that they would like to continue working to bring them to completion, submission and publications of two journal articles in the Journal of Biosafety and Biosecurity; and AAAS Science & Diplomacy journal.

Website: https://viterbi-web.usc.edu/~meshkati/

Faculty Information Sessions

CURVE will help facilitate matching you with an open research position. To help you select which lab you would like to join, we will be hosting faculty-led information sessions where you can hear from faculty members about the research projects they are working on and the role of an undergraduate research assistant in their lab. This also gives you a chance to ask questions and talk with faculty (virtually!) face-to-face before applying to work in their lab.

Information sessions will be held on Friday, September 11th and Friday, September 18th. You are welcome to attend as many sessions as you like. Please note some sessions may be running concurrently. 

Check back the week of September 7th for the zoom links and calendar of information sessions. Sessions and zoom links will continue to be added throughout the week. Please note not all faculty will be offering sessions.

Information sessions are allotted one hour, but students can expect the sessions to run for about 30 minutes.

Friday, September 11, 2020

Time

Host

Research Project

Zoom link

9:00 AM – 10:00 AM PDT

Professor Garijo, ISI

A Framework for Enabling Encapsulating, Testing and Maintaining Scientific Software

10:00 AM – 11:00 AM PDT

Professor Ravichandran, CHE

Advanced Oxide and Chalcogenide Materials for Electronics, Photonics and Energy Applications

10:00 AM – 11:00 AM PDT

Professor Ren, CS

Post-hoc Explanation Demo for Deep Learning Models in Natural Language Processing & Machine Commonsense Reasoning

2:00 PM – 3:00 PM PDT

Professor Mataric, CS

Computational Socially Assistive Robotics

4:00 PM – 5:00 PM PDT

Professor Duncan, INI

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy

Friday, September 18, 2020

Time

Host

Research Project

Zoom link

9:00 AM – 10:00 AM PDT

Professor Pujara, Computer Science

Probabilistic AI Models for Understanding Human Discourse

9:00 AM – 10:00 AM PDT

Professor Irimia, Gerontology

Brain MRI analysis, connectomics and machine learning for neuroscience knowledge discovery

9:00 AM – 10:00 AM PDT

Professor Jaiswal, ECE

Use of Emerging Memory Technologies for Novel Circuit Design

9:00 AM – 10:00 AM PDT

Professor Sengupta, ASTE

Hydrogen Powered Urban Aerial Mobility

10:00 AM – 11:00 AM PDT

Professor Barnhart, ISI

Disruptive space engineering, research, and education

10:00 AM – 11:00 AM PDT

Professor Nikolaidis, CS

Interactive and Collaborative Autonomous Robotics lab

10:00 AM – 11:00 AM PDT

Professor Gupta, AME

Robotic Hand with Variable Compliance

10:00 AM – 11:00 AM PDT

Professor Ebramzadeh Abrams, BME

Design and Evaluation of Orthopaedic Implants

10:00 AM – 11:00 AM PDT

Professor McArthur, AME

Various projects in Aircraft Dynamics, Controls, and Cooperation Lab

10:00 AM – 11:00 AM PDT

Professor Ortega, ECE

Signal Transformation, Analysis and Compression Group

10:00 AM – 11:00 AM PDT

Professor Sandeep Gupta, ECE

Methods and tools to accelerate discoveries

10:00 AM – 11:00 AM PDT

Professor Wilcox, ISE

Time Series Clustering – Survey Paper

2:00 PM – 3:00 PM PDT

Professor Annavaram, ECE

Various Distributed Machine Learning Projects

2:00 PM – 3:00 PM PDT

Professor Bouteiller, BME

Multi-Scale Modeling of the Hippocampus for Electrical Stimulation

2:00 PM – 3:00 PM PDT

Professor Ayanian, CS

Trajectory replanning for multirobot systems

2:00 PM – 3:00 PM PDT

Professor Hsu, ECE

Fast electrodynamics solvers

2:00 PM – 3:00 PM PDT

Professor Renuka Balakrishna, AME

Microstructure-Property Relations in Materials

2:00 PM – 3:00 PM PDT

Professor Hall, ISE

Creating the Innovative University & Integrated Modeling of Healthcare Capacity and Patient Needs to Intervene Against Human Transmitted Viral Disease

3:00 PM – 4:00 PM PDT

Professor Oberai, AME

Machine Learning for Improving Outcomes in Healthcare

3:00 PM – 4:00 PM PDT

Professor Toutios, ECE

Modeling human speech production

3:00 PM – 4:00 PM PDT

Professor Abramson, ECE

Data Driven Cybersecurity

3:00 PM – 4:00 PM PDT

Professor Applegate, BME

Signal Processing for Optical Coherence Tomography Imaging of the Ear

4:00 PM – 5:00 PM PDT

Professor Nuzzo, ECE

Self-Driving Vehicle Testbed

4:00 PM – 5:00 PM PDT

Professor Penkova, AME

Mathematical modeling and engineering devices to COVID-19 response; Fluid transport experiments and simulations related to glaucoma

4:00 PM – 5:00 PM PDT

Professor Bogdan, ECE

Covid-19 misinformation, SARS-CoV-2 viral analysis, complex networks, machine learning and artificial intelligence

4:00 PM – 5:00 PM PDT

Professor Dilkina, CS

ML and Optimization for “AI in Society” Projects

4:00 PM – 5:00 PM PDT

Professor Wang, ASTE

Computational Studies in Astronautical Engineering

Frequently Asked Questions

Am I guaranteed a research position by filling out the application?

Filling out an application does not guarantee a position. We will do our best to match students to appropriate positions based on availability. 

Do I need to have prior research experience?

Although some research positions do require prior experience or certain skills, there are also positions available for students with no prior experience. 

I already have a research position but it is unpaid. Can I apply to receive funding for my current position?

Yes, there is a section on the application to complete if you already have a research position for the year.

I already have a paid research position. Can I apply to receive additional funding?

If you are already receiving funding you will not be considered to receive additional funding. 

If I am an international student currently residing outside the United State, can I apply to this program?

Students residing outside the U.S. can apply but are not eligible to receive funding while abroad.

What class levels and majors are eligible to apply?

All declared Viterbi students and all class levels are able to apply. 

The second faculty-led information session is on September 18th. Can I wait until after the 18th to submit my application?

Yes, applications are not due until Sunday, September 20th. We encourage students to attend the sessions to help select their research labs.

Are on-campus research positions available?

All fall research positions with CURVE will be remote. 

Can I apply just for fall semester?

In order to get the most out of your research experience for both you and your faculty mentor, the positions are for the academic year. 

I am currently on or will be taking a Leave of Absence, am I eligible to apply?

This program is intended for students to participate in research for the entire academic year, so students currently on LOA or planning on taking an LOA in spring are not eligible to apply.

I am graduating in December 2020, can I apply to this program?

No, this program is intended for students who will be studying for the entire academic year.

What is the process to apply?

Identify the research labs that you would like to learn more about. Attend the information sessions for those labs during our Info Session days on Friday, September 11th and Friday, September 18th to learn more about the positions and meet the faculty mentor. Fill out the application by Sunday, September 20th and identify your top three research choices. Award notifications will be sent out the week of September 28th and positions will begin in October.

I am a Dean’s Research or Merit Research recipient, can I apply to this program to help match me with a research position?

Yes, you are welcome to apply and use the CURVE matching process to help you find a position in a lab.

Can I apply for a research position that is in a different department than my major?

Yes! You are welcome to apply for positions from different departments.

How many hours a week is this commitment?

Students can expect to work 5-10 hours per week.

Contact Us

Please contact viterbi.studentservices@usc.edu for more information about the application process.