People / PhD StudentsPhD Students: S - Z

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

Roberto Carlos Salas Damian
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
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Roberto Carlos

Abhraneel Sarma
Student Track: Interfaces
Research Area: HCI, Visualisation
Advisor(s): Kay, Matt; Jessica Hullman
Cohort: September 2019
Expected Graduation Date: June 2025
Research Statement: 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, or studying how we can improve uncertainty communication to help users take into account sources of uncertainty other than statistical variability
Abhraneel's Website
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Abhraneel

Florian Andreas Schiffers
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
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Florian Andreas

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

Sergio Servantez
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
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Sergio

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

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

Xiangmin Shen
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
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Xiangmin

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

Alexis Shuping
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
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Alexis

Tanmay Kumar Sinha
Student Track: Theory
Cohort: September 2024
Expected Graduation Date: August 2029
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Tanmay Kumar

Michael Smith
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
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Michael

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

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

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

Vaidehi Srinivas
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
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Vaidehi

Marko Sterbentz
Student Track: Artificial Intelligence
Research Area: Natural Language Processing
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: December 2025
Research Statement: My research focuses on leveraging AI and large language models (LLMs) to automate data science processes, enabling users to ask questions of their data and receive meaningful, contextualized insights.
Marko's Website
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Marko

Yian Su
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
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Yian

Jipeng Sun
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
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Jipeng

Yunqing Sun
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
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Yunqing

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

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

Yuanyang Teng
Student Track: TSB
Research Area: Human-Computer Interaction
Advisor(s): Darren Gergle
Cohort: September 2024
Expected Graduation Date: December 2029
Research Statement: My research brings together people with diverse abilities and perspectives through communication and collaboration, particularly in visual and spatial contexts. Before becoming a computer scientist and HCI researcher, I was an architect who designed spaces.
Yuanyang's Website
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Yuanyang

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

Mara Ulloa
Student Track: Interfaces
Research Area: Human-Computer Interaction (HCI)
Advisor(s): Jacobs, Maia
Cohort: September 2021
Expected Graduation Date: June 2027
Research Statement: Broadly, my research focuses on applying Human-Computer Interaction (HCI) methodologies to design and evaluate user-centered technologies. As part of my work, I co-design machine learning (ML) solutions for healthcare, emphasizing the end user's perspective. One of my current projects in this space involves co-design patient-facing ML for prenatal stress reduction.
Mara's Website
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Mara

Soroush Shahi Vernousfaderani
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
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Soroush Shahi

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

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

Qineng Wang
Research Area: Embodied Agent, Multi-Modality, Large Language Models
Advisor(s): Manling Li
Cohort: September 2024
Qineng's Website
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Qineng

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

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

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

Lixu Wang
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
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Lixu

Lingzhi Wang
Student Track: Systems
Research Area: Cyber Security, Advanced Attack Techniques, Threat Detection
Advisor(s): Chen, Yan
Cohort: September 2020
Expected Graduation Date: 2025
Research Statement: My research is centered around system security and cyberattacks, with a focus on developing and optimizing Endpoint Detection and Response (EDR) systems and Host Intrusion Detection Systems (HIDS) systems to detect and defend against Advanced Persistent Threats (APT). My research involves behavior analysis of software, AI security, and the development of the Knowledge Base to enhance our understanding of cyberattack techniques to improve system security and protect against evolving threats in the digital space.
Lingzhi's Website
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Lingzhi

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

Nick Wanninger
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
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Nick

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

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

Panitan Wongse-Ammat
Student Track: Systems
Advisor(s): Joseph, Russell
Cohort: March 2016
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Panitan
Dennis Wu
Student Track: Artificial Intelligence
Research Area: ML Theory
Advisor(s): Liu, Han
Cohort: September 2024
Research Statement: I do theories of ML
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Dennis

Chaofeng Wu
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
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Chaofeng

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

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

Yifan Wu
Student Track: Theory
Research Area: Economics and Computation
Advisor(s): Hartline, Jason D
Cohort: September 2020
Expected Graduation Date: 2026
Research Statement: Yifan Wu's research interest lies in the intersection of economics and computation. Currently, she work on topics related to trustworthy AI, from a decision-making perspective. Her research topics include information elicitation, calibration, and theoretical benchmark for human experiments.
Yifan's Website
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Yifan

Dawei Xie
Student Track: Interfaces
Research Area: HCI
Advisor(s): Jessica Hullman
Cohort: September 2024
Expected Graduation Date: June 2029
Research Statement: My research interest generally centers around human-AI interaction, with a primary focus on modeling, quantifying, and communicating uncertainty to support human decision making, as well as incorporating distribution-free statistical frameworks to calibrate and align AI models with human preferences.
Dawei's Website
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Dawei

Wangcheng Xu
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
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Wangcheng

Guo 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
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Guo

Shu Hung You
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
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Shu Hung

Jiahao Yu
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
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Jiahao

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

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

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

Zheng Zhang
Student Track: Systems
Research Area: Databases
Advisor(s): Crotty, Andrew
Cohort: September 2021
Expected Graduation Date: December 2026
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Zheng

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

Kexin Zhao
Student Track: Artificial Intelligence
Research Area: NLP, NLU
Advisor(s): Forbus, Kenneth
Cohort: September 2024
Expected Graduation Date: June 2029
Email
Kexin

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

Jiahong Zheng
Student Track: Artificial Intelligence
Research Area: Multimodal Reasoning, Cognitive Modeling
Advisor(s): Forbus, Kenneth
Cohort: September 2024
Expected Graduation Date: June 2029
Email
Jiahong

Zhihan Zhou
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
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Zhihan

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