Student Track: CSLS
Advisor(s): Horn, Michael
Cohort: September 2018
Email Nicholas

Student Track: Systems
Research Area: Programming Languages
Advisor(s): Dimoulas, Christos
Cohort: September 2018
Expected Graduation Date: December 2023
Research Statement: I’m interested in Programming Languages approaches to make programming accessible and practically useful for human beings. People and their programs are imperfect, so one part of that interest is in linguistic tools that support program robustness and debugging; my ongoing work on contract systems and gradual typing centers around evaluating how these specification tools, intended to improve robustness, may or may not assist with debugging. Relatively few people are programmers, however, so another part of my interest is understanding how and why everyone else might find value in programming; my current work in this direction explores languages, domains, and settings which enable novices to use computing as a useful tool, while simultaneously providing a rich setting for digging deeper into foundational computing concepts. I work on and use the Racket programming language as a concrete setting for most of my research.
Lukas' Website
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Student Track: Systems
Research Area: High Performance Computing
Advisor(s): Choudhary, Alok; Liao, Wei-Keng
Cohort: September 2019
Expected Graduation Date: June 2025
Research Statement: Claire is a Ph.D. student studying the intersection of High Performance Computing (HPC) and Machine Learning (ML) in the CUCIS lab. She is also a recipient of the NSF GRFP fellowship program.
Claire's Website
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Student Track: Interfaces
Research Area: Robotics
Advisor(s): Argall, Brenna
Cohort: September 2018
Email Jongmin

Student Track: Systems
Research Area: Networking
Advisor(s): Kuzmanovic, Aleksandar
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: My research interests are general Networking topics including cloud computing and virtualization. I want to develop networked systems that focus on three perspectives: reducing latency, preserving privacy and utilizing edge servers. Currently, I am working on reducing web page loading time by moving the process of fetching web content from the remote servers to the edge servers.
Yanzhi's Website
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Student Track: Systems
Research Area: Databases
Advisor(s): Rogers, Jennie
Cohort: June 2021
Expected Graduation Date: June 2026
Research Statement: Broadly speaking, my research interests focus on security and privacy of computer science including verifiable query evaluation (DB), privacy-preserving machine learning (PPML), etc. In addition, my research heavily relies on cryptographical primitives and protocols from secure multiparty computation and zero knowledge proof.
Xiling's Website
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Student Track: TSB
Cohort: September 2017
Email Hanlin

Student Track: Artificial Intelligence
Research Area: Time Series Prediction, Deep Learning Systems
Advisor(s): Liu, Han
Cohort: September 2019
Expected Graduation Date: June 2025
Research Statement: My research interest is focused on large-scale multi-resolution and multi-horizon time series prediction. More specifically, I am interested in creating generic deep learning models that generate accurate predictions in various time series task settings and deep learning systems that power rapid computational experiments on super large scale time series data.
Weijian's Website
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Student Track: Systems
Research Area: Compilers
Advisor(s): Campanoni, Simone
Cohort: September 2022
Email Jasper

Student Track: Artificial Intelligence
Research Area: Robotics
Advisor(s): Liu, Han
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research interests lie in the general area of Robotics, particularly in Reinforcement Learning, Motion Plan and Cloud Robotics System.
Qinjie's Website
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Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: January 2022
Expected Graduation Date: June 2024
Research Statement: I am a PhD student at Northwestern University. I am fortunate to be advised by Dr. Xinyu Xing. My Research focuses on OS exploitation and defense. I love hacking in the real world. I have demonstrated many Linux kernel exploitation on Google's products (COS) through KCTF and latest version of kernel in Ubuntu at Pwn2Own. For those 0days I found, I responsibly disclosed them and have contributed many security fixes to improve the security of Linux kernel. I am also a CTF player and won 7th at DEF CON CTF 2021 Finals.
Zhenpeng's Website
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Student Track: Artificial Intelligence
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research interest lies in Computer Science and Cognitive Science, and I'm interested in understanding how the human brain works so that we can learn how to build an intelligent system that can be beneficial to human beings. In addition, I am also interested in thinking about how technology can be beneficial for people's well-being.
Chenghong's Website
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Student Track: Systems
Research Area: Networking
Advisor(s): Kuzmanovic, Aleksandar
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research interests lie in computer networks and systems. Specifically, I currently focus on optimizing public-facing services through developing novel mechanisms applied to legacy network protocols.
Sen's Website
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Student Track: Theory
Advisor(s): Liu, Han
Cohort: September 2022
Email Erzhi

Student Track: Theory
Research Area: Algorithimic Game Theory
Advisor(s): Hartline, Jason
Cohort: September 2020
Expected Graduation Date: June 2026
Research Statement: I am broadly interested in topics that lie at the intersection between theoretical computer science and economics. I also like to think and reason about HCI through a more formal lense.
Sheng's Website
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Student Track: CSLS
Cohort: September 2021
Email Alexandros

Student Track: TSB
Research Area: HCI
Advisor(s): Zhang, Haoqi
Cohort: September 2017
Expected Graduation Date: June 2023
Research Statement: Ryan is an HCI PhD student in Technology and Social Behavior, a joint program between the Computer Science and Communication departments. In his graduate work, Ryan is interested in how to design social technologies that support meaningfully connecting across distance that conveniently fits into users daily lives. To tackle this problem, he is designing and research technologies that identify opportunistic moments to engage in shared experiences and activities and facilitate social connecting interactions in those moments. To prototype his ideas, he develops computational platforms that support the implementation and execution of these opportunistic, structured social interactions. He identifies as an HCI researcher who uses social science theories to craft his designs and AI techniques to forge the systems he builds. Before Northwestern, he studied at Olin College where he received a B.S. in Engineering with a Concentration in Robotics.
Ryan's Website
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Student Track: Artificial Intelligence
Research Area: Foundation Model
Advisor(s): Liu, Han
Cohort: September 2022
Expected Graduation Date: June 2027
Research Statement: Are you supersize the performance of the ChatGPT? Foundation model change our life, and AI generation make the deep learning going to a new epoch. My research focuses on foundation model and multimodal data processing. I work with professor Han to do some foundation model, such as prompt engineering, text generation, financial foundation model. Also, I work on some hyperparameters optimization research.
Haozheng's Website
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Student Track: Theory
Advisor(s): Hartline, Jason
Cohort: September 2017
Email Michail

Student Track: Graphics and Interactive Media
Research Area: Computational Optics
Advisor(s): Katsaggelos, Aggelos; Cossaiart, Oliver; Willomitzer, Florian
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My name is Manuel Ballester and I am currently a Ph.D. candidate at Northwestern University in the department of computer science. I am a member and collaborator of two research groups: the Computational Photo Lab (CPL), and the Image-Video Processing Lab (IVPL). I have a broad academic interest and background in mathematics (bachelor's degree), physics (master's degree), and computer science (pursuing doctorate). I intend to apply novel computational techniques from optimization and machine learning to the fields of optics and imaging. My main project focuses on the optical characterization of semiconductors (CZT and Silicon) to improve the performance of sensors using physics-based machine learning approaches. I also collaborate on other projects, such as digital holographic displays and 3D image reconstruction.
Manuel's Website
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Student Track: Systems
Research Area: Compilers
Advisor(s): Campanoni, Simone
Cohort: September 2020
Expected Graduation Date: 2025
Research Statement: I study compilers, specifically looking into new intermediate representations and abstractions. My research aims to broaden the optimization space of compilers through intermediate representations that grant empowering degrees of freedom through strong guarantees. I am also interested in static analysis, runtime system co-design, programming languages, and memory models.
Tommy's Website
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Student Track: CSLS
Advisor(s): Worsley, Marcelo
Cohort: September 2019
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Student Track: Computer Engineering
Research Area: Machine Learning
Advisor(s): Zhu, Qi
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I am a second-year PhD student in Computer Engineering and a part of IDEAS Lab at Northwestern University, advised by Dr. Qi Zhu. I am interested in developing learning methods for real-world non-manicured data, especially time-series data. I also want to improve inclusivity in technology. In some of my past works I have developed algorithms to improve the participation of disfluent speakers in voice-assisted technology. During my Masters I also developed hardware support for optical sensors in wearable devices to perform consistently for users of all skin-tones. I have a solid background in IC designing for a large semiconductor company, healthcare technology, and algorithms & machine learning.
Payal's Website
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Student Track: Graphics and Interactive Media
Research Area: Audio Generation
Advisor(s): Pardo, Bryan
Cohort: September 2018
Expected Graduation Date: December 2023
Research Statement: I am a Ph.D. candidate in the Interactive Audio Lab at Northwestern University advised by Professor Bryan Pardo. My research involves applications of machine learning for audio technology. My specific interests include generative modeling and deep learning. I am most interested in applications of this technology that enable more intuitive and efficient workflows for audio engineers, sound designers, dialogue editors, and other creative professionals. Before beginning my doctoral research, I attended the University of Michigan and obtained Bachelor's degrees in Computer Science and Performing Arts Technology.
Maxwell's Website
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Student Track: Systems and Networking
Advisor(s): Dinda, Peter
Cohort: September 2022
Email Kirill

Student Track: Artificial Intelligence
Research Area: Natural Language Processing
Advisor(s): Forbus, Kenneth
Cohort: September 2016
Expected Graduation Date: August 2023
Research Statement: My research aims to make Natural Language systems easier to debug by having the system ask the user diagnostic questions in natural language. Through a series of such questions, the system will be able to locate the error in its linguistic knowledge and correct it, allowing non-expert users to help improve the system's understanding. I have also done research on cognitively plausible models of reference resolution, and I help maintain the Qualitative Reasoning Group's information kiosk.
Constantine's Website
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Student Track: TSB
Research Area: HCI
Advisor(s): Hullman, Jessica
Cohort: September 2019
Research Statement: I create tools for engaging a wide range of stakeholders in reasoning about societal tradeoffs implicated by algorithmic systems. Specifically, I’ve spent much of the past few years thinking about how various stakeholders reason about differential privacy, including in the context of the 2020 U.S. Census.
Priyanka's Website
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Student Track: TSB
Research Area: HCI
Advisor(s): Diakopoulos, Nicholas
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: I study and design interactive systems for information seeking and decision making in the newsroom. Specifically, I work at the intersection of Human-computer Interaction (HCI), Natural Language Processing, and Machine Learning, and build configurable and transparent AI tools to help journalists discover + understand newsworthy stories from domain-specific documents, to support decisions about what makes the news.
Sachita's Website
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Student Track: Artificial Intelligence
Research Area: Machine Learning for Audio
Advisor(s): Pardo, Bryan
Cohort: September 2020
Expected Graduation Date: June 2024
Research Statement: I'm a doctoral student in the Department of Computer Science at Northwestern University and a member of the Interactive Audio Lab. I received a BA in Mathematics and Music from Carleton College and an MS in Computer Science from the University of Illinois at Chicago. My research interests include adversarial robustness for audio interfaces, music information retrieval, and machine learning techniques for controllable audio generation.
Patrick's Website
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Student Track: TSB
Advisor(s): Horvat, Emoke-Agnes
Cohort: September 2020
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Student Track: Artificial Intelligence
Research Area: Machine Ethics, Reasoning Systems, Machine Learning
Advisor(s): Forbus, Kenneth
Cohort: September 2018
Expected Graduation Date: June 2024
Research Statement: I find our ability to recognize acceptable and unacceptable behaviors quite fascinating. During a basketball game, how do you know that it would be strange to whisper to your teammate? What about playing your favorite rap song at a funeral? I am currently exploring ways of formally modeling how we reason (or how we want our machines to reason) about norms like these, as well as those with greater moral implications. I am also currently creating algorithms that allow machines to learn such norms from natural modalities such as dialogue.
Taylor's Website
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Student Track: Artificial Intelligence
Advisor(s): Hammond, Kristian
Cohort: September 2018
Email Andrew

Student Track: Systems
Advisor(s): Campanoni, Simone
Cohort: September 2022
Email Atmn

Student Track: Artificial Intelligence
Research Area: AI/ML, Deep Learning
Advisor(s): Choudhary, Alok
Cohort: September 2022
Alec's Website
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Student Track: Systems and Networking
Advisor(s): Campanoni, Simone
Cohort: September 2022
Email Bang-yen

Student Track: Systems and Networking
Advisor(s): Bustamante, Fabian
Cohort: September 2022
Email Michael

Student Track: Artificial Intelligence
Research Area: Agent-based modeling, genetic programming, evolutionary computation, artificial life, game theory
Advisor(s): Wilensky, Uri
Cohort: September 2018
Expected Graduation Date: June 2024
Research Statement: I am interested in exploring the use of genetic programming in evolutionary agent-based models. The adversariality and cooperativity inherent in multi-agent settings could potentially lead to new practical discoveries in the area of evolutionary computation. Additionally, the use of adaptive learning mechanisms in multi-agent settings can be a powerful tool for exploring behavioral ecologies. Adaptive evolutionary models can also be leveraged to gain new insights into general evolutionary processes.
Leif's Website
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Student Track: Artificial Intelligence
Research Area: AI/ML
Advisor(s): Hammond, Kristian
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research focuses on developing solutions to improve the generalization of neural networks in noisy/random, high-dimensional, supervised learning environments (typically involving time-series data), solving real-world problems in industries such as brain science, health, sustainability, and social justice. I find interest in developing machine learning systems/methods that augment human intelligence and creativity while maintaining an ethical, reliable, fair, and responsible standard.
Alex's Website
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Student Track: Artificial Intelligence
Research Area: Natural Language Understanding
Advisor(s): Forbus, Kenneth; Downey, Douglas
Cohort: September 2017
Expected Graduation Date: June 2023
Research Statement: The goal of my research is to build intelligent systems that are able to incorporate knowledge and reasoning when processing natural language, either by enhancing current NLP systems or by creating innovative ways of learning and applying knowledge to solve language tasks.
Danilo Neves' Website
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Student Track: Interfaces
Research Area: Human-Computer Interaction
Advisor(s): Hester, Josiah
Cohort: September 2021
Expected Graduation Date: June 2025
Research Statement: Blaine’s research focuses on programming interfaces and sensing pipelines for the development of wearable health and other IoT devices.
Blaine's Website
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