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PhD Students
PhD Students: S - Z

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Abir Saha

Student Track: TSB
Advisor(s): Piper, Anne Marie
Cohort: September 2018
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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.
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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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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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Leesha Shah

Student Track: TSB
Advisor(s): Zhang, Haoqi
Cohort: September 2016
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Anant Shah

Student Track: Theory
Advisor(s): Hartline, Jason
Cohort: September 2021
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Farzad Shahabi

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

Student Track: Theory
Advisor(s): Makarychev, Konstantin
Cohort: September 2018
Expected Graduation Date: August 2023
Research Statement: My research interests include approximation algorithms, graph theory, and algorithmic game theory. The aim of my research is to design algorithms for data analysis and decision-making in real-world problems. I currently work on many clustering and graph partitioning problems.
Liren's Website
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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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Wenxuan Shi

Student Track: Security and Privacy
Advisor(s): Xing, Xinyu
Cohort: September 2022
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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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Tanmay Kumar Sinha

Student Track: Theory
Cohort: September 2024
Expected Graduation Date: August 2029
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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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Donghyun Sohn

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

Student Track: Artificial Intelligence
Advisor(s): Subrahmanian, VS
Cohort: September 2022
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Federico Sossai

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

Student Track: Systems
Research Area: Parallelizing Compilers, Runtime Techniques, Heterogeneous Systems
Advisor(s): Campanoni, Simone
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: Yian is a fourth-year PhD candidate in Computer Science at Northwestern University, working with Professor Simone Campanoni in the ARCANA Lab. He researches compilers and runtime techniques for parallel and heterogeneous systems. His work focuses on enabling developers to write high-level, architecture-agnostic parallel programs while generating efficient and portable binaries across diverse hardware platforms. He builds compiler infrastructures and scheduling frameworks that lower the barrier to performance portability, making high-performance computing more accessible to a broader range of programmers and researchers. His broader interests include parallelizing compilers, static and dynamic program analysis, and compiler optimizations designed to scale with growing program complexity and hardware diversity.
Yian's Website
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Pattara Sukprasert

Student Track: Theory
Research Area: Algorithms
Advisor(s): Khuller, Samir
Cohort: June 2019
Expected Graduation Date: 2023
Research Statement: I have broad interests in topics related to graph theory. Most of my works are related to graphs in one way or another. I worked and am interested in working on topics related to graph algorithms, approximation algorithms, dynamic algorithms, online algorithms, clustering, fairness, and stability. While most of my works focus on the theoretical side, I am delighted that I have a paper on cancer research, which is arguably closer to practical usage.
Pattara's Website
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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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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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Madhav Suresh

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

Student Track: Theory
Research Area: Algorithms and Machine Learning
Advisor(s): Makarychev, Konstantin; Vijayaraghavan, Aravindan
Cohort: September 2018
Expected Graduation Date: June 2023
Research Statement: My research interests are mainly in the design and analysis of algorithms for computationally hard problems, especially those which arise in the context of large scale machine learning.
Aravind Reddy's Website
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Alex Tang

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 include the first constant approximation guarantee for agnostic learning biased neurons using gradient descent and a novel tensor 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
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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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Kedar Thiagarajan

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

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
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Jacoya Thompson

Student Track: Graphics and Interactive Media
Research Area: HCI
Advisor(s): Worsley, Marcelo
Cohort: September 2016
Expected Graduation Date: June 2023
Research Statement: My research interests lie at the intersection of Human-Computer Interaction (HCI), Data Science, and Education. My research seeks to understand how to design tools and activities to support learners in developing data science skills.
Jacoya's Website
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Brandon Tiedeman

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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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Deniz Ulusel

Student Track: Computer Engineering
Advisor(s): Memik, Gokhan
Cohort: September 2020
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Gustavo Umbelino

Student Track: TSB
Advisor(s): Gerber, Elizabeth; Easterday, Matthew
Expected Graduation Date: 2019
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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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Nicholas Vincent

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
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Matthew vonAllmen

Student Track: Theory
Advisor(s): Hartline, Jason
Cohort: January 2021
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Adia Wallace

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
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Yixue Wang

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
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Xijun Wang

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.
Xijun's Website
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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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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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Jiayi Wang

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

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

Student Track: Artificial Intelligence
Advisor(s): Liu, Han
Cohort: September 2018
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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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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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Boyang Wei

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

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
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Michael Wilkins

Student Track: Computer Engineering
Research Area: Architecture, Parallel Systems
Advisor(s): Dinda, Peter; Hardavellas, Nikos
Cohort: September 2019
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Panitan Wongse-Ammat

Student Track: Systems
Advisor(s): Joseph, Russell
Cohort: March 2016
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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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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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Yuhang Wu

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

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
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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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Shichao Xu

Student Track: Computer Engineering
Research Area: Artificial Intelligence
Advisor(s): Zhu, Qi
Cohort: June 2018
Expected Graduation Date: June 2023
Research Statement: Shichao Xu is a fourth-year Ph.D. candidate in the Computer Science Department at Northwestern University, and his advisor is Prof Qi Zhu. He received his undergraduate degree from Shanghai Jiao Tong University (ACM Honors Class) in 2018. His current research interests mainly focus on Learning from Limited or Imperfect Data, especially for dealing with the problem of data insufficiency, and poor data quality. The related topics include deep representation learning, domain adaptation, self/weakly/semi-supervised learning, transfer learning, and reinforcement learning with application to vision, multimodal, and control problems.
Shichao's Website
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Bingjie Xu

Student Track: Interfaces
Research Area: Computational Imaging
Advisor(s): Tumblin, Jack
Cohort: September 2018
Expected Graduation Date: June 2023
Research Statement: I am working on using 3D surface and subsurface imaging techniques and building portable optical systems to solve practical questions in cultural heritage and VR applications. I am interested in 3D imaging systems from micro-scale OCT to macro-scale Deflectometry, photometric stereo, and single-pixel imaging. I am also interested in interdisciplinary projects, which combine imaging results with other kinds of information, such as material composition from XRF results to get a better understanding of objects.
Bingjie's Website
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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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Ye Xue

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

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

Advisor(s): Liu, Han
Cohort: September 2021
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Dongping Zhang

Student Track: TSB
Advisor(s): Hullman, Jessica
Cohort: September 2018
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Richard Zhang

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

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

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

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
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Kexin Zhao

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

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

Student Track: Artificial Intelligence
Research Area: Multimodal Reasoning, Cognitive Modeling
Advisor(s): Forbus, Kenneth
Cohort: September 2024
Expected Graduation Date: June 2029
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Photo of Zhihan Zhou

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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Yufeng Zou

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