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PhD Students

PhD Students: L - R

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

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
Email Claire

Student Track: Interfaces
Research Area: Computational Imaging, Computational Photography, Computer Vision
Advisor(s): Alexander, Emma
Cohort: September 2023
Expected Graduation Date: 2028
Research Statement: My research interest is in the field of computational imaging, which lies at the intersection of optics, signal processing, computer vision, computer graphics, and machine learning. Specifically, I enjoy solving inverse problems using domain-specific knowledge (e.g., optics and geometry) in computational photography, medical imaging, and scientific imaging.
Tianao's Website
Email Tianao

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
Email Yanzhi

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
Email Xiling

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
Email Weijian

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
Email Qinjie

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.
Email Chenghong

Student Track: Systems
Research Area: Networking
Advisor(s): Kuzmanovic, Aleksandar
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research centers on multidimensional network traffic optimization, with an emphasis on enhancing end-user experience in media streaming and data center networks. I design and develop protocols and systems that optimize network performance holistically.
Sen's Website
Email Sen

Student Track: Theory
Research Area: Scheduling algorithms
Advisor(s): Samir Khuller
Cohort: September 2023
Research Statement: I am interested in studying scheduling problems. Meanwhile, I am curious about learning more theoretical computer science and related math.
Mozhengfu's Website
Email Mozhengfu

Student Track: Theory
Advisor(s): Liu, Han
Cohort: September 2022
Email Erzhi

Student Track: Interfaces
Research Area: Information Visualization
Advisor(s): Kay, Matthew
Cohort: September 2020
Expected Graduation Date: June 2026
Research Statement: I am interested in (i) taking interdisciplinary best practices toward experiment design and formally modeling human behavior when they interact with novel interfaces/information visualizations, and (ii) leveraging machine learning, specifically transfer learning techniques, to automate the process of evaluating and enhancing user experiences when interacting with novel interfaces/information visualizations.
Sheng's Website
Email Sheng

Student Track: CSLS
Cohort: September 2021
Email Alexandros

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
Email Haozheng

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
Email Manuel

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
Email Tommy

Student Track: CSLS
Advisor(s): Worsley, Marcelo
Cohort: September 2019
Email Natalie

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
Email Payal

Student Track: CSLS
Cohort: 2022
Expected Graduation Date: 2027
Kritphong'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
Email Constantine

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
Email Sachita

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
Email Patrick

Student Track: TSB
Advisor(s): Horvat, Emoke-Agnes
Cohort: September 2020
Email Katherine

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
Email Taylor

Student Track: Artificial Intelligence
Research Area: Large Language Model, Diffusion Model, Graph Neural Network
Advisor(s): Liu, Han
Cohort: September 2024
Expected Graduation Date: March 2029
Zhenyu's Website
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Student Track: Systems
Advisor(s): Hardavellas, Nikos
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
Email Alec

Student Track: Systems
Advisor(s): Dinda, Peter
Cohort: September 2022
Expected Graduation Date: June 2027
Michael's Website
Email Michael

Student Track: Theory
Email Phawin

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
Email Leif

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
Email Blaine