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PhD Students

PhD Students: S - Z

Student Track: TSB
Advisor(s): Piper, Anne Marie
Cohort: September 2018
Email Abir

Student Track: Artificial Intelligence
Research Area: Qualitative Reasoning
Advisor(s): Forbus, Kenneth
Cohort: June 2021
Expected Graduation Date: June 2026
Research Statement: Expanding knowledge in artificial intelligence systems is one of the fundamental requirements to improve dialog or reasoning systems. Previous research has demonstrated that a system can learn new information by reading analogies in instructional texts. Based on this insight, my current research lies in exploring how a system can identify analogies to acquire new knowledge during a conversation in a spoken dialog system.
Roberto Carlos' Website
Email Roberto Carlos

Student Track: Interfaces
Research Area: HCI
Advisor(s): Hullman, Jessica; Kay, Matt
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: Broadly, I am interested in studying how people make sense of uncertainty information which arise in a typical data analysis pipeline. This includes developing tools which surfaces uncertainty in the data analysis process itself, such as the multiverse R library, or studying how users interpret uncertainty visualisations in missing data contexts or multiple comparisons scenarios.
Abhraneel's Website
Email Abhraneel

Student Track: Graphics
Research Area: Computational Imaging and Display
Advisor(s): Cossairt, Oliver Strides
Cohort: September 2018
Expected Graduation Date: December 2023
Research Statement: My work focuses on computational photography and display, which combines expertise in physics/optics, image processing, computer vision, machine learning, and computer graphics. I design, model, and build end-to-end systems that combine sensors, displays, and novel optical elements. Current applications of my research are found in medicine, VR/AR/MR, robotics, industrial inspection, remote sensing, biology, and cultural heritage preservation. For my Ph.D. thesis, I investigate novel algorithms for Computer Generated Holography that will enable the next-generation Near-Eye Display (VR/AR) with the ultimate goal of passing the "Visual Turing Test." In other words, I want to make the metaverse a reality by creating a display where - to the human eye - the virtual world becomes indistinguishable from the real world.
Florian Andreas' Website
Email Florian Andreas

Student Track: Computer Engineering
Advisor(s): Hardavellas, Nikos
Cohort: September 2022
Email Connor

Student Track: Artificial Intelligence
Research Area: AI and Law, Deep Learning, Natural Language Processing
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: December 2023
Research Statement: Sergio's research is primarily focused on the intersection of machine learning and law. Specifically, his work explores how large language models can be used to extract information and reason over legal documents.
Sergio's Website
Email Sergio

Student Track: TSB
Advisor(s): Zhang, Haoqi
Cohort: September 2016
Email Leesha

Student Track: Theory
Advisor(s): Hartline, Jason
Cohort: September 2021
Email Anant

Student Track: Graphics and Interactive Media
Research Area: Mobile Health
Advisor(s): Nabil Alshurafa
Cohort: September 2020
Email Farzad

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Chen, Yan
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research focuses on end-point detection of Advanced Persistent Threat (APT) on Linux systems. Specifically, I study threat modeling of APTs and using machine learning in threat detection.
Xiangmin's Website
Email Xiangmin

Student Track: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: September 2022
Email Wenxuan

Student Track: Computer Engineering
Research Area: Energy Harvesting
Advisor(s): Hester, Josiah
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: The fundamental goal of my research is to use technology to do the most good for people, and in particular, for the marginalized communities that the STEM fields and the people who control them have failed and exploited throughout history. I focus on designing robust and accessible systems that empower these groups to monitor their homes and communities for environmental pollution. This data can be used to hold corporations to account for the damage they cause, and also to target mitigation strategies where they will be most effective.
Alexis' Website
Email Alexis

Student Track: CSLS
Research Area: Sports, Technology, and Learning
Advisor(s): Worsley, Marcelo
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: Michael Smith is a Computer Science and Learning Sciences PhD student at Northwestern University, and a National GEM Consortium PhD Fellow. Some of his research and project interests include exploring the intersections of technology & education, formal and informal learning, computing culture, new media and community, and games.
Michael's Website
Email Michael

Student Track: Systems and Networking
Advisor(s): Rogers, Jennie
Cohort: September 2022
Email Donghyun

Student Track: Artificial Intelligence
Advisor(s): Subrahmanian, VS
Cohort: September 2022
Email Lirika

Student Track: Systems and Networking
Advisor(s): Campanoni, Simone
Cohort: September 2022
Email Federico

Student Track: Theory
Research Area: Algorithms
Advisor(s): Vijayaraghavan, Aravindan
Cohort: September 2021
Expected Graduation Date: Unknown
Research Statement: Vaidehi is a Ph.D. student in the theory group, advised by Aravindan Vijayaraghavan. She is interested in designing and analyzing simple algorithms that are practical for real-world input. She has worked on designing prediction algorithms that use significantly less memory than the previous state of the art [in STOC '22], and analyzing the Burer-Monteiro method, a practical and popular heuristic used in many machine learning applications. Before Northwestern, she earned her B.S. in Computer Science at Carnegie Mellon University, and was a Fulbright visiting student at the University of Vienna in the Theory and Applications of Algorithms group. Sie spricht auch gerne Deutsch!
Vaidehi's Website
Email Vaidehi

Student Track: Artificial Intelligence
Research Area: Natural Language Processing
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My field of research is natural language processing, with a focus on language understanding, question answering, and information retrieval. In particular, I work on building systems that can effectively break a question down into its logical parts and use that in order to automatically perform the required data retrieval and analysis against heterogeneous data sources including unstructured text, knowledge graphs, and relational databases. My ultimate goal is to develop methods that enable non-technical users to better interact with the ever growing body of data that is at their fingertips, but which is not always easily accessible due to the time constraints required to search through this data and the technical expertise required to write database queries. Rather, these systems should be able to meet the users on their terms and have the rich information contained within the data be accessible via a natural language interface that any person can interact with.
Marko's Website
Email Marko

Student Track: Systems
Research Area: Parallelizing Compilers and Runtime Scheduling Techniques
Advisor(s): Campanoni, Simone
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: Yian Su is a third-year Ph.D. candidate in Computer Science, advised by Simone Campanoni at Northwestern ARCANA Lab. His primary research interest lies in advancing the field of parallel processing via compiler support and multi-threaded scheduling techniques. His research aims to enable programmers to write generic parallel programs while producing portable and performant binaries for various parallel architectures and heterogeneous systems. He is also interested in parallelizing compilers, code analysis, and compiler optimizations.
Yian's Website
Email Yian

Student Track: Graphics and Interactive Media
Research Area: Computational Photography
Advisor(s): Cossairt, Oliver Strides
Cohort: January 2021
Expected Graduation Date: June 2027
Research Statement: Jipeng Sun is a Ph.D. student in the CS Department working in the Computational Photography Lab at Northwestern University. He is interested in building machines that enhance the human visual system and empowering machine intelligence with biological-inspired neural networks. His research interests include light-field microscopy, computer-generated holography display, and AR system. Jipeng is currently working on imaging live zebrafish brain neuron firing patterns using programmable 3D light-field microscopy. He received his Master degree in Computer Science from Northwestern University, US, and Bachelor degree with honor in Software Engineering from Shandong University, China. Before coming to Northwestern, Jipeng worked full-time in the Institute of Automation, Chinese Academy of Sciences (CASIA) on brain-inspired robotics bodily-self model project during 2019-2021.
Jipeng's Website
Email Jipeng

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Wang, Xiao
Cohort: June 2021
Expected Graduation Date: 2026
Research Statement: My research interests mainly focus on security and privacy. I am working on oblivious transfer, multi-party computation, and zero-knowledge proof to propel them into practical use in systems.
Yunqing's Website
Email Yunqing

Student Track: Systems
Research Area: Databases
Advisor(s): Hartline, Jason D; Naughton, Jeffrey
Cohort: September 2016
Email Madhav

Student Track: TSB
Research Area: Computational Social Science; Human-AI teams
Advisor(s): Contractor, Noshir
Cohort: June 2022
Vsevolod's Website
Email Vsevolod

Student Track: Theory
Research Area: Machine Learning Algorithms & Applications
Advisor(s): Vijayaraghavan, Aravindan
Cohort: September 2019
Expected Graduation Date: 2024
Research Statement: My research focuses on the design & analysis of efficient machine learning algorithms for neural networks. Current results includethe first constant approximation guarantee for agnostic learning biased neurons using gradient descent and a noveltensor decomposition-based algorithm for learning two-layer neural networks, which also establishes under the smoothed-analysis paradigm such neural networks can be learned in polynomial time under non-degenerative conditions.
Alex's Website
Email Alex

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

Student Track: Artificial Intelligence
Research Area: Graph Structure Learning
Advisor(s): Liu, Han
Cohort: September 2019
Expected Graduation Date: March 2024
Research Statement: My research looks at how we can learn interpretable graph structures directly from data without relying on heuristics that simplify (or, in most cases, obfuscate) the structure-learning signal. I'm currently working on GNN-based methods with applications in drug discovery.
Mattson's Website
Email Mattson

Student Track: Interfaces
Research Area: HCI
Advisor(s): Jacobs, Maia
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research focuses on designing novel strategies and interventions that support youths' mental wellbeing within computer science education environments. The objective of my work is to build digital mental health interventions that are co-designed with youth and address their unique support needs. I also aim to provide CS educators with tools to better support the wellbeing of students, with a particular focus on supporting underrepresented students. Another of my research interests focuses on studying the sociotechnical challenges machine learning tools face when being embedded into real-world, medical settings. My goal is to co-design solutions to these challanges with the intended user, so that their ideas and needs are valued and a key component of the tool's development.
Mara's Website
Email Mara

Student Track: Computer Engineering
Advisor(s): Memik, Gokhan
Cohort: September 2020
Email Deniz

Student Track: TSB
Advisor(s): Gerber, Elizabeth; Easterday, Matthew
Expected Graduation Date: September 2019
Email Gustavo

Student Track: Graphics and Interactive Media
Research Area: Applied Machine Learning
Advisor(s): Alshurafa, Nabil
Cohort: March 2021
Expected Graduation Date: N/A
Research Statement: Soroush’s research is focused on human activity recognition using wearable devices such as wearable cameras. Specifically, he is interested in detecting activities that has implications for human health such as eating and smoking. Recently, he worked on addressing privacy aspects of wearable cameras using image obfuscation techniques. Prior to joining Northwestern University, Soroush got a Bachelor of Science in Computer Engineering from the University of Tehran.
Soroush Shahi's Website
Email Soroush Shahi

Student Track: TSB
Research Area: Human-Centered Machine Learning
Advisor(s): Hecht, Brent
Cohort: September 2017
Expected Graduation Date: August 2022
Research Statement: My research focuses on studying the dependence of modern computing technologies, including the broad set of systems called "AI", on human-generated data, with the goal of mitigating negative impacts of these technologies. I am especially interested in research that (1) makes people aware of the value of their data and (2) helps people leverage the value of their data. My work relates to concepts such as "data dignity", "data as labor", "data leverage", and"data dividends". My research is rooted in the hypothesis that, with better-designed systems, AI can mitigate inequalities in wealth and power rather than exacerbate them.
Nicholas' Website
Email Nicholas

Student Track: Theory
Advisor(s): Hartline, Jason
Cohort: January 2021
Email Matthew

Student Track: Interfaces
Advisor(s): Horn, Michael
Cohort: September 2016
Email Izaiah

Student Track: CSLS
Research Area: Interfaces
Advisor(s): Worsley, Marcelo
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: My research interests include culturally-responsive-sustaining K12 CS education, computer science teacher development, makerspaces, and creative applications of AI. (I have not officially begun research yet since CS+LS students have a little more leeway in exploring).
Adia's Website
Email Adia

Student Track: Theory
Research Area: algorithmic game theory, mechanism design
Advisor(s): Hartline, Jason
Cohort: September 2023
Chang's Website
Email Chang

Advisor(s): Liu, Han
Cohort: September 2021
Email Jiayi

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

Student Track: Computer Engineering
Research Area: Security and Privacy
Advisor(s): Wang, Xiao; Zhu, Qi
Cohort: January 2021
Expected Graduation Date: August 2025
Research Statement: I aim to create socially responsible machine learning (ML) models, i.e., ML models that can protect the privacy of their training data and minimize the chance of being misused. In particular, to ensure privacy protection, those models must be resistant to various privacy attacks. To prevent harmful social impacts from the misuse of ML models, their generalization ability on unintentional data domains and tasks must be reduced. To achieve these goals, I have been developing novel ML models and tools with a diverse set of techniques in Optimization Theory, Information Theory, and Cryptography. Greater ability comes with greater responsibility, and this applies equally to ML technology. ML models with social responsibility can protect data privacy and prevent serious consequences caused by the harmful use of models, such as teenagers obtaining violent information from recommendation systems or criminals using ML models to engage in criminal activities.
Lixu's Website
Email Lixu

Student Track: Interfaces
Research Area: Robotics, Graphics
Advisor(s): Cossairt, Oliver Strides
Cohort: January 2019
Expected Graduation Date: December 2023
Research Statement: I'm working on using Machine Learning and deep learning methods to solve computer vision and video/image processing problems, for example, activity classification, object detection, and super-resolution.
Email Xijun

Student Track: Systems
Advisor(s): Chen, Yan
Cohort: September 2020
Email Lingzhi

Student Track: TSB
Research Area: HCI
Advisor(s): Diakopoulos, Nicholas
Cohort: September 2017
Expected Graduation Date: August 2023
Research Statement: As a researcher in HCI, computational journalism, and social science, I analyze human behavioral data as a means to enhance diversity, maintain civility, and eliminate biases. I am specifically interested in promoting online deliberation, supporting journalistic sourcing practices via online comments, and designing article-level news personalizations. I am advised by Nicholas Diakopoulos in the Computational Journalism Lab.
Yixue's Website
Email Yixue

Student Track: Artificial Intelligence
Advisor(s): Liu, Han
Cohort: September 2018
Email Ning

Student Track: Systems
Research Area: Operating Systems, Parallel Systems, High Performance Computing
Advisor(s): Dinda, Peter
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: My research falls broadly into the category of kernel support for specialized application requirements and parallelism. I enjoy finding novel ways of enabling new programming models by adding support at the lowest levels of the operating system kernel.
Nick's Website
Email Nick

Student Track: Interfaces
Research Area: Mobile Health
Advisor(s): Alshurafa, Nabil
Cohort: September 2020
Email Boyang

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Wang, Xiao
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research lies in cryptography with focus on secure multi-party computation and zero-knowledge proofs. I use cryptographic techniques to provide security and privacy in real-world scenarios involving data sharing.
Chenkai's Website
Email Chenkai

Student Track: Computer Engineering
Research Area: Architecture, Parallel Systems
Advisor(s): Dinda, Peter; Hardavellas, Nikos
Cohort: September 2019
Email Michael

Student Track: Systems
Advisor(s): Joseph, Russell
Cohort: March 2016
Email Panitan

Student Track: Theory
Research Area: Economics
Advisor(s): Liang, Annie
Cohort: September 2020
Expected Graduation Date: December 2025
Research Statement: My research interest is the applications of Computer Science in Economics. I apply data science and machine learning techniques to problems in decision theory and network of economics, especially for model building and evaluation.
Chaofeng's Website
Email Chaofeng

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: March 2022
Email Yuhang

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: January 2022
Email Xian

Student Track: Theory
Research Area: Economics
Advisor(s): Hartline, Jason D
Cohort: September 2020
Expected Graduation Date: 2025
Research Statement: Yifan Wu's research interest lies in the intersection of economics and computation. Currently, her work focuses on the design of optimal scoring rules in mechanism design, with applications to other areas such as machine learning and visualization studies in human-computer interaction.
Yifan's Website
Email Yifan

Student Track: Systems
Research Area: Networking
Advisor(s): Kuzmanovic, Aleksandar
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: I am broadly interested in computer networks and distributed systems. My current work focuses on network measurement and edge network design.
Yunming's Website
Email Yunming

Student Track: Artificial Intelligence
Research Area: Cognitive Systens
Advisor(s): Forbus, Kenneth
Cohort: June 2021
Expected Graduation Date: June 2026
Research Statement: My primary research interests focus on analogical reasoning and learning, natural language understanding, and interactive task learning. I’m exploring the general methods for the AI system to learn tasks via interactions with humans, including task-independent natural language and demonstrations, and accumulate knowledge that can be operationalized in the task environment or transferred in future learning. I’m also investigating analogy as a core mechanism for acquiring the underlying task concepts and procedures and adapting and grounding them in novel situations.
Wangcheng's Website
Email Wangcheng

Student Track: Artificial Intelligence
Advisor(s): Trajcevski, Goce; Klabjan, Diego
Cohort: September 2016
Email Ye

Student Track: Artificial Intelligence
Research Area: Robotics
Advisor(s): Liu, Han
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research interest lies on the intersection of the robotic learning and cloud robotics. I am interested in the Multi-agent Reinforcement Learning, Cloud Robotics, Differentiable Robot Simulation.
Guo's Website
Email Guo

Student Track: Systems
Research Area: Programming Languages
Advisor(s): Findler, Robby; Dimoulas, Christos
Cohort: September 2016
Expected Graduation Date: August 2023
Research Statement: I am interested in the theory and the design of programming languages. More specifically, I design language features that provably enforce correctness properties on programs. I currently work on the theoretical foundation of contract systems to enable the modular specification of contract monitoring strategies.
Shu Hung's Website
Email Shu Hung

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: January 2022
Expected Graduation Date: June 2026
Research Statement: My research interests focus on utilizing deep learning to address the issues in security and privacy. In addition, I work on explainable machine learning to help understand the machine learning model and trust the behavior.
Jiahao's Website
Email Jiahao

Student Track: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: September 2022
Email Zheng

Student Track: TSB
Advisor(s): Shaw, Aaron; Horvat, Emoke-Agnes
Cohort: September 2021
Email Richard

Student Track: TSB
Advisor(s): Hullman, Jessica
Cohort: September 2018
Email Dongping

Advisor(s): Liu, Han
Cohort: September 2021
Email Zhi

Student Track: Theory
Research Area: Game Theory
Advisor(s): Hartline, Jason D; Dimoulas, Christos
Cohort: September 2018
Chenhao's Website
Email Chenhao

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Rogers, Jennie
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I have a broad interest in the area of security and privacy. More concretely, I have been working on improving the security and privacy guarantees of database management systems with differential privacy mechanisms and cryptographic primitives such as oblivious computation and zero-knowledge proof. I’m also interested in adversarial and backdoor attacks on deep learning models and systems.
Zheng's Website
Email Zheng

Student Track: Security and Privacy
Advisor(s): Wang, Xiao
Cohort: September 2022
Email Wenhao

Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Chen, Yan
Cohort: September 2018
Email Guannan

Student Track: Artificial Intelligence
Research Area: Digitization of Government
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My main research focus is modernizing our political systems through AI. I am focused on developing human-centered AI that provides that access and improves, in that order, the transparency, accountability, and efficiency of government. The technical work involves building systems that can understand vaguely-articulated questions, obtain the correct data analysis, and identify the most appropriate representation of that analysis. Additionally, I am working on the more human-centered issues related to understanding users, their needs, and how they are impacted by these systems. Through this balanced approach, I believe that true accessibility of political information, regardless of users’ technical or political knowledge, can be achieved.through AI/ML.
Andong Li's Website
Email Andong Li

Student Track: Artificial Intelligence
Advisor(s): Liu, Han
Cohort: September 2020
Expected Graduation Date: December 2024
Research Statement: My research focuses on the modeling of sequential and graphical data using deep learning techniques. I am especially interested in applying large language models to solve real-world and science problems such as dialogue understanding and genome analysis.
Zhihan's Website
Email Zhihan

Student Track: Artificial Intelligence
Advisor(s): Liu, Han
Cohort: September 2022
Email Yufeng