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PhD Students

PhD Students: A - K

Student Track: TSB
Advisor(s): Diakopoulos, Nick
Cohort: September 2021
Email Mowafak

Student Track: Artificial Intelligence
Research Area: HCI
Advisor(s): Worsley, Marcelo
Cohort: September 2018
Expected Graduation Date: 2024
Research Statement: Interests in how Machine Learning can help augment, not necessarily replace, humans in tasks and jobs such as driving, learning, manufacturing, and many other areas. My current research focuses on HCI and Multi-Modal Analytics. In these areas, I hope to analyze and change the different ways Multimodal Analytics is currently approached to better integrate the wants and needs of those who are participating in collection. In doing this I hope to develop new algorithms and interactions that combine different modalities that aid in serving those needs we see from the participants.
Khalil's Website
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Student Track: Graphics
Advisor(s): Alexander, Emma
Cohort: September 2022
Email Kerem

Student Track: Interfaces
Research Area: Robotics
Advisor(s): Dr. Michael Rubenstein
Cohort: 2023
Expected Graduation Date: 2028
Maryam's Website
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Student Track: TSB
Research Area: Algorithmic Ethics and Transparency
Advisor(s): Diakopoulos, Nick
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research interests lie in algorithmic ethics and transparency, ethical AI, NLP applications in social contexts, and the intersection of machine learning and music.
Julia's Website
Email Julia

Student Track: Artificial Intelligence
Research Area: NLP
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My primary research interests center around converting information represented in an unstructured format, such as raw text, to a more structured machine-ingestible format. Specifically, I'm currently focusing on extracting entity-to-entity relationships from document corpora and representing them in knowledge graphs, lending such documents to availability as a source for a variety of search applications (e.g., question answering systems)
Cameron's Website
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Student Track: Artificial Intelligence
Advisor(s): Birnbaum, Lawrence
Cohort: September 2022
Expected Graduation Date: June 2027
Email Simon

Student Track: TSB
Research Area: HCI & Learning Sciences
Advisor(s): Worsley, Marcelo
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: I am researching learning in complex spaces. As part of this work, I design learning environments and artifacts, and use various qualitative and quantitive methods to evaluate my designs.
Herminio's Website
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Student Track: CSLS
Advisor(s): Horn, Michael
Cohort: September 2020
Email Maddie

Research Area: Perception
Advisor(s): Sam
Cohort: 2024
Research Statement: I am passionate about understanding perception, particularly vision and hearing, at the intersection of computer science and neuroscience. My work focuses on leveraging insights from the brain and human behavior to advance the development of more effective algorithms and robotics, while also exploring how machine learning can unveil new perspectives on human cognition. I am open to collaborations and welcome any opportunities for research overlap。
Yuchen's Website
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Student Track: Theory
Cohort: September 2024
Email Matthew

Student Track: Theory
Research Area: Combinatorial Statistics
Advisor(s): Racz, Miklos
Cohort: September 2022
Research Statement: My research interests lie in the intersection of statistics and theoretical computer science. I am currently working on graph matching and community detection problems on random graph. I am also interested in reliable machine learning.
Shuwen's Website
Email Shuwen

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

Student Track: Theory
Research Area: Algorithms
Cohort: September 2021
Expected Graduation Date: June 2025
Research Statement: I am a Ph.D. student in the Department of Computer Science at Northwestern University.
Sayak's Website
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Cohort: September 2019
Research Statement: Peter is a Law & Science Fellow and a JD-PhD student working at the intersection of Computer Science and Law. He is interested on his research from two angles: 1) applying advancement in computer science to policy problems, and 2) devising effective regulations for the safe deployment of new technologies.
Peter's Website
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Student Track: TSB
Research Area: HCI
Advisor(s): Jacobs, Maia
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I am an interdisciplinary HCI researcher whose work applies critical theory and participatory research methods to develop technologies that support care work and provide equitable health outcomes for marginalized communities. My interests include the design of mental & physical health technologies, sociotechnical opportunities to facilitate healing & resilience for trauma survivors, and community-based research.
Connie's Website
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Student Track: CSLS
Research Area: Computer Science Education
Advisor(s): Marcelo Worsley
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: Victoria is broadly interested in computer science education, accessibility, civic technology, and social justice. Most of their research interests stem from asking "How can we make Computer Science a safe and joyous experience for Black, Disabled, Indigenous, and Latinx college students?"
Victoria's Website
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Student Track: CSLS
Advisor(s): Wilensky, Uri
Cohort: September 2019
Email John

Student Track: CSLS
Cohort: September 2019
Email Yuehan

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

Student Track: Interfaces
Research Area: HCI and Computing Education
Advisor(s): O'Rourke, Eleanor
Cohort: September 2022
Research Statement: I am interested in designing interventions to support beginner programming students' self-efficacy.
Melissa's Website
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Student Track: Security and Privacy
Advisor(s): Xinyu Xing
Cohort: September 2023
Expected Graduation Date: December 2025
Email Zelei

Student Track: Artificial Intelligence
Research Area: Statistical Language Modeling
Advisor(s): Downey, Douglas
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research attempts to understand the strengths, curiosities, and weaknesses of large-scale pre-trained language models. Specifically, I'm fascinated by the limitations and learning mechanisms of transformer-based architectures in the context of commonsense reasoning, constraint satisfaction, and knowledge acquisition. Currently, some approaches that I'm interested in are: multitask learning and knowledge transfer techniques; analysis of learned embedding spaces and hidden state representations; statistical tools for interpreting the importance of specific parameters and training examples.
Chris' Website
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Student Track: TSB
Advisor(s): Shaw, Aaron
Cohort: September 2020
Expected Graduation Date: 2025
Carl's Website
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Student Track: Interfaces
Research Area: Data Visualization
Advisor(s): Kay, Matthew
Cohort: September 2020
Expected Graduation Date: 2026
Research Statement: My research interests lie at the intersection of computer science and behavioral sciences. I'm currently exploring the broad world of algorithms, data visualization, and machine learning. I hope to better understand and guide system design with tools from these disciplines to bring positive social impact to the world we live in.
Yuan's Website
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Student Track: Interfaces
Research Area: HCI
Advisor(s): Zhang, Haoqi; O'Rourke, Eleanor
Cohort: September 2018
Expected Graduation Date: June 2023
Research Statement: My research investigates how we can take readily available open source codebases (i.e. GitHub, web source code) and convert them into opportunities for novices and intermediate developers to learn about how design patterns and architectures are applied in practice. By comparing novice use of both debugging tools (i.e. Chrome DevTools) and graphical tools (i.e. call graph visualization tools, I have found that tools can significantly shape the ways novices explore professional code, and their focus and learnings. We have introduced Scaffolded Exercises, a tool that scaffolds novices as they understand Javascript variable transformation that leads to DOM changes, and Knowledge Maps, a tool that helps novices compare and contrast examples to understand conceptual differences between techniques and build out a map of their CSS knowledge. Finally, we are actively developing RALE Modules (Readily Available Learning Experiences), a process management system which highlights and annotates design patterns and architectures (i.e. MVC, Mixins) in professional python codebases, and generates a series of diagrams and activities that help intermediate developers understand how and why particular patterns are applied in particular professional use cases.
Govinda's Website
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Student Track: Computer Engineering
Research Area: Machine Learning and High-Performance Computing
Advisor(s): Choudhary, Alok
Cohort: September 2020
Expected Graduation Date: August 2025
Research Statement: I am currently pursuing interdisciplinary research projects at the intersection of machine learning and high-performance computing. My research group, the Center for Ultra-Scale Computing and Information Security (CUCIS), specializes in both of these areas under the supervision of Professor Alok Choudhary. I am currently working with a group in the Materials Science and Engineering Department to characterize nanoparticle images and accelerate their acquisition and analysis turnaround times. I have an undergraduate degree in physics with a math minor from Wellesley College, and am also an NSF Graduate Research Fellow.
Alexandra's Website
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Student Track: Artificial Intelligence
Research Area: Machine Learning, Computer Vision, Natural Naguage Processing
Advisor(s): V.S. Subrahmanian
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I am a second-year Ph.D. student in Computer Science at Northwestern University, advised by Dr. V.S. Subrahmanian. My primary research focuses are Machine Learning, Computer Vision, and Natural Language Processing. Before joining Northwestern, I was a Master's (thesis-based) student in Computer Science at the University of New Hampshire. I spent Summer 2021 at the Center for Coastal and Ocean Mapping/NOAA-UNH Joint Hydrographic Center, working on Unsupervised Semantic Segmentation under Dr. Yuri Rzhanov and Dr. Kim Lowell. Before that, I was a Research Associate (full-time) at the Artificial Intelligence and Cybernetics (AGenCy) Lab, Independent University, Bangladesh. I was supervised by Dr. Amin Ahsan Ali, Dr. A K M Mahbubur Rahman, and Dr. Iftekhar Tanveer. Some notable projects are Diversity in English Video Captioning, Video Captioning in the Bengali Language, and Scalable Bengali Speech-to-Text. My research interest evolved since my Undergrad at North South University. One of my key projects was PATRON. I was blessed with excellent advisors, Dr. Mohammad Rashedur Rahman, Mr. Adnan Firoze, and Dr. Mohammad Ashrafuzzaman Khan.
Tonmoay's Website
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Student Track: Artificial Intelligence
Research Area: N/A
Advisor(s): Forbus, Kenneth
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: I’m currently working on methods for scaling symbolic knowledge representations. I also have interest in Natural language understanding.
Walker's Website
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Student Track: Artificial Intelligence
Advisor(s): Subrahmanian, VS
Cohort: September 2022
Email Natalia

Student Track: Computer Engineering
Advisor(s): Campanoni, Simone
Cohort: September 2022
Email David

Student Track: Artificial Intelligence
Research Area: Applied AI
Advisor(s): Hammond, Kristian
Cohort: September 2019
Expected Graduation Date: 2025
Research Statement: My research interests lie in the area of artificial intelligence for social good, mainly in analytics and education, where I strive to bridge the information gap between data and educational stakeholders by automating data science techniques. I believe that data-driven education will be the next big step in education, and want to be in the forefront of that development as it moves forward. Recently I have been working with CASMI and underwriters laboratories on a project aimed to build a framework for how to make predictive policing systems safe and equitable for society.
Alexander's Website
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Student Track: Systems
Research Area: Programming Languages
Advisor(s): Dimoulas, Christos
Cohort: January 2021
Email Tochukwu

Student Track: Graphics and Interactive Media
Research Area: HCI
Advisor(s): Alshurafa, Nabil
Cohort: September 2020
Expected Graduation Date: 2025
Research Statement: PhD Student in Computer Science, working with HABits Lab at the intersection of Computer Science and Preventive Medicine. My research revolves around user centric design and evaluation of end-to-end mobile health systems, which involves the integration of technology, healthcare and data science.
Glenn's Website
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Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Wang, Xiao
Cohort: September 2020
Email Nicholas

Student Track: Interfaces
Research Area: Computer Vision
Advisor(s): Subrahmanian, VS
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I am a Ph.D. student at Northwestern University and I am interested in computer vision, NLP, and V-L Tasks. I have published several papers related to image captioning and text few-shot learning.
Chongyang's Website
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Student Track: Artificial Intelligence
Research Area: HCI
Advisor(s): Pardo, Bryan
Cohort: September 2020
Expected Graduation Date: 2025
Research Statement: Hugo is a Ph.D. student in Computer Science at Northwestern University, working under Prof. Bryan Pardo in the Interactive Audio Lab. Hugo's research interests lie at the intersection of machine learning, signal processing, and human computer interaction for music and audio. Hugo has previously worked on a deep learning framework for Audacity, an open source audio editor, and will be a research intern at Spotify and Descript during the latter half of 2022. Hugo holds an B.S. in Electrical Engineering from Georgia Southern University (2020). He is a jazz guitarist, and can be seen playing with various groups local to the Chicago area. Hugo enjoys augmenting musical instruments with technology, as well as making interactive music and art in SuperCollider and Max/MSP.
Hugo Flores' Website
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Student Track: TSB
Advisor(s): Zhang, Haoqi; Gergle, Darren
Cohort: September 2018
Email Kapil

Student Track: Security and Privacy
Research Area: Applied Cryptography
Advisor(s): Wang, Xiao
Cohort: September 2022
Research Statement: My research interests lie in applied cryptography, focusing on Secure Multi-Party Computation and homomorphic encryption.
Radhika's Website
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Student Track: Interfaces
Research Area: HCI and Information Visualization
Advisor(s): Kay, Matthew
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research interests are broadly within HCI and information visualization. Specifically, I'm interested in visualization literacy and taking a more comprehensive look at ways we can better assess people's abilities to reason about and critically interpret visualizations. In addition to understanding people's ability to read from visualizations, it is also necessary to better understand the ability to identify erroneous and misleading visualizations, which may be present in instances of visualization misinformation. Furthermore, I'm interested in how visualizations can assist in the decision-making and problem-solving process.
Lily's Website
Email Lily

Student Track: Artificial Intelligence
Research Area: Machine Learning
Advisor(s): Liu, Han
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research interests are convex, non-convex optimization. More specifically, I aim to solve sequential decision making problems by formulating them into convex optimization problems. Regarding non-convex optimization, my research is focused on bilevel optimization, an application of which is hyperparameter tuning.
Ammar's Website
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Student Track: Computer Engineering
Research Area: Systems
Advisor(s): Campanoni, Simone
Cohort: September 2022
Nathan's Website
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Student Track: Theory
Research Area: Theoretical machine learning and high-dimensional statistics.
Advisor(s): Aravindan Vijayaraghavan
Cohort: September 2023
Expected Graduation Date: June 2028
Research Statement: During my undergraduate time, I worked on a practice-inspired graph algorithm, which can be used to optimize version control systems.
Bob's Website
Email Bob

Research Area: HCI
Advisor(s): Hullman, Jessica
Email Ziyang

Student Track: Artificial Intelligence
Research Area: Agent-Based Modeling
Advisor(s): Wilensky, Uri
Cohort: September 2017
Expected Graduation Date: December 2023
Research Statement: My research is about combining multi-agent systems with open-ended neuro-evolutionary processes, that is building open-ended multi-agent systems where each interacting agent has evolving neural nets that can increase arbitrarily in complexity, in order to understand the nature and evolution of intelligence better as well as finding novel machine learning technologies using this approach.
Can's Website
Email Can

Student Track: Artificial Intelligence
Advisor(s): Forbus, Kenneth
Cohort: September 2017
Email William

Student Track: CSLS
Research Area: HCI
Advisor(s): Kay, Matthew
Cohort: September 2019
Expected Graduation Date: June 2025
Maryam's Website
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Student Track: CSLS
Advisor(s): O'Rourke, Eleanor
Cohort: September 2017
Email Garrett

Student Track: Artificial Intelligence
Cohort: September 2017
Email Samuel

Student Track: Systems
Research Area: Compilers
Advisor(s): Campanoni, Simone
Cohort: September 2020
Expected Graduation Date: May 2025
Research Statement: My research is focused on addressing the challenges involved with generating effective parallelism. I'm developing compiler abstractions to leverage automatic parallelization while capturing the semantics of explicitly parallel applications. These abstractions enable decisions about the parallelism of an application to be determined within the compiler enabling more performance, scalable parallelism.
Brian's Website
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Student Track: Artificial Intelligence
Research Area: AI/ML
Advisor(s): Hammond, Kristian
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: I work in the Cognition, Creativity, and Communication (C3) Lab, lead by Professor Kristian Hammond. My research interest is in developing human-centered AI applications.
Donna's Website
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Student Track: Artificial Intelligence
Research Area: Machine Learning; Foundation Model; AI/ML for Science
Advisor(s): Liu, Han
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: My research focuses on developing theoretical foundations and principled methodologies for Large Language Models, Foundation Models and Generative AI. My long-term goal is to leverage machine learning to tackle important scientific and societal challenges. Recently, I have focused on understanding inference and learning in large pretrained models through the dual lens of statistics and neuroscience. This unique (model-based) perspective allows me to explore (i) Computational and statistical properties of pretrained transformer and diffusion models for pretraining, inference, fine-tuning, compression and alignment, and (ii) New methodological and algorithmic designs, with theoretical guarantees to ensure their practical optimality.
Jerry Yao-Chieh's Website
Email Jerry Yao-Chieh

Student Track: TSB
Research Area: HCI
Advisor(s): Gerber, Ellizabeth; Easterday, Matthew
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research interest lies at the intersection of HCI, AI, and education. I use design research methods to design and build mixed-initiative human-AI systems that can support coaching and learning in real-world, ill-defined domains like design education and entrepreneurship.
Evey's Website
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Student Track: Computer Engineering
Research Area: HPC
Advisor(s): Choudhary, Alok
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: My research interests lie in large-scale applications in parallel and distributed environments with a focus on parallel file I/O, distributed storage system design, and communications.
Zanhua's Website
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Student Track: CSLS
Advisor(s): Horn, Michael
Cohort: September 2020
Email Ayse

Student Track: TSB
Cohort: June 2022
Email Monisola Mercy

Student Track: CSLS
Research Area: anti-Blackness and Computing
Advisor(s): Worsley, Marcelo
Cohort: September 2018
Stephanie's Website
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Student Track: Theory
Research Area: Theoretical Machine Learning and Optimization
Advisor(s): Vijayaraghavan, Aravindan
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I have broad interests in various aspects of theoretical computer science and mathematics. My research focuses on the mathematical foundations of machine learning and optimization, especially in random graphs theory, deep learning theory, and distributed optimization. My research aims to design efficient algorithms with provable performance guarantees for various learning problems.
Nirmit's Website
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Student Track: Theory
Research Area: Machine Learning
Advisor(s): Makarychev, Konstantin; Vijayaraghavan, Aravindan
Cohort: September 2018
Expected Graduation Date: December 2023
Research Statement: Working on It
Sanchit's Website
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Student Track: Interfaces
Research Area: HCI
Advisor(s): Hullman, Jessica
Negar's Website
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Student Track: Systems
Research Area: Security and Privacy
Advisor(s): Chen, Yan
Cohort: September 2017
Expected Graduation Date: December 2022
Research Statement: My area covers many aspects of security practices. From configuration, to data collection, detection, forensics and remediation.
Mohammad's Website
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Student Track: Interfaces
Advisor(s): Hullman, Jessica; Hartline, Jason
Cohort: September 2018
Expected Graduation Date: June 2024
Email Paula Patricia Ogol

Student Track: Interfaces
Research Area: Theory
Advisor(s): Khuller, Samir
Cohort: September 2021
Email Yiduo

Student Track: CSLS
Advisor(s): Wilensky, Uri
Cohort: September 2018
Email Jacob

Student Track: Artificial Intelligence
Advisor(s): Forbus, Kenneth
Cohort: September 2024
Email Omar

Student Track: Artificial Intelligence
Research Area: AI/ML, Computer Vision
Advisor(s): Choudhary, Alok
Cohort: September 2022
Expected Graduation Date: June 2026
Research Statement: I am M. N. Talha Kilic, a first year AI/ML Ph.D. student in Computer Science at Northwestern University. I have the privilege of being advised by three esteemed faculty members, namely, Prof. Alok Choudhary, Prof. Ankit Agrawal, and Prof. Wei-Keng Liao, who have been instrumental in shaping my research interests and career goals. Prior to joining the Ph.D. program, I worked in the petroleum and satellite industries for a combined period of almost four years. During this time, I honed my skills in microcontroller, circuit, and PCB design, as well as embedded coding and optimization, which have been invaluable in my academic pursuits. I completed my Master's degree in Electronics Engineering from Istanbul Technical University, where I conducted research on "Classification of Chest X-Rays using Divergence-Based Convolutional Neural Network" as part of my thesis. Currently, I am a member of the research group, the Center for Ultra-Scale Computing and Information Security (CUCIS), which aims to bridge the gap between AI and material science by proposing AI-based models to accelerate the creation of new microstructures while minimizing time and cost.
Muhammed Nur Talha's Website
Email Muhammed Nur Talha

Student Track: TSB
Research Area: HCI
Advisor(s): Kay, Matthew
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: I am interested in leveraging NLP/ML models to resolve problems in human-human communication. I design, build, and evaluate systems to encourage people to share affirmative emotions. Recently, I am working on designing systems for supporting the mental health of caregivers of a person with dementia.
Taewook's Website
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Student Track: Systems
Research Area: Computer Networks, Distrubuted Systems
Cohort: September 2024
Expected Graduation Date: June 2029
Email Santiago

Student Track: Computer Engineering
Research Area: Scheduling of distributed heterogeneous systems
Advisor(s): Peter Dinda
Cohort: January 2023
Expected Graduation Date: March 2028
Research Statement: David Krasowska is a Ph.D. candidate at Northwestern University, advised by Dr. Peter Dinda. His research journey began during his undergraduate studies at Clemson University where he collaborated with Argonne National Laboratory to explore lossy compression for optimizations in HPC scientific applications. He received the DOE Computational Science Graduate Fellowship to fund his graduate studies. Currently, he is exploring scheduling applications across distributed heterogeneous systems with Dr. Pat McCormick and Dr. Li Tang at Los Alamos National Laboratory.
David's Website
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Student Track: Systems
Research Area: Networking
Advisor(s): Bustamante, Fabian E,Kuzmanovic, Aleksandar
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research focuses on the trends towards and the implications of third-party and centralization on the Internet, developing approaches to characterize these trends and potentially addressing their impact. I am currently looking at these trends globally, across services like DNS, content and hosting infrastructure, and developing client-based solutions for DNS centralization.
Rashna's Website
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Student Track: Artificial Intelligence
Research Area: Natural Language
Advisor(s): Forbus, Kenneth
Cohort: September 2020
Expected Graduation Date: June 2025
Research Statement: My research interests currently revolve around NLU and commonsense reasoning. The project I am currently working on involves generating qualitative representations of the entries in the ATOMIC dataset, which focuses on capturing social commonsense knowledge. These representations can then be used as a library of knowledge for use in analogical chaining, which entails starting with a representation of a person’s current state of knowledge and using analogy to integrate this knowledge with past experiences. The result of the repeated chaining can be both explanations for an observation and inferences that follow from an observation. I believe this project can lead to better QA systems and provide more insight into the distinctions between quantitative and qualitative approaches to commonsense reasoning.
Mukundan's Website
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