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PhD Students

PhD Students: A - K

Student Track: Interfaces
Research Area: Mobile Heath
Advisor(s): Alshurafa, Nabil
Cohort: June 2017
Email Rawan Mansour S

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
Email Khalil

Student Track: Systems
Advisor(s): Bustamante, Fabian
Cohort: September 2022
Email Zafir

Student Track: Graphics
Advisor(s): Alexander, Emma
Cohort: September 2022
Email Kerem

Student Track: Systems
Research Area: Embedded Systems
Advisor(s): Hester, Josiah
Cohort: June 2018
Email Abu

Student Track: TSB
Research Area: HCI
Advisor(s): Diakopoulos, Nick
Cohort: September 2018
Expected Graduation Date: May 2023
Research Statement: My research focuses on ethics and accountability for algorithmic communication platforms like Facebook, Twitter, and TikTok.
Jack's Website
Email Jack

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: CSLS
Advisor(s): O'Rourke, Eleanor
Cohort: September 2016
Email Jamie

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
Email Herminio

Student Track: TSB
Advisor(s): Piper, Anne Marie
Cohort: September 2017
Email Katya

Student Track: CSLS
Advisor(s): Horn, Michael
Cohort: September 2020
Email Maddie

Student Track: Artificial Intelligence
Research Area: Natural Language Processing
Advisor(s): Birnbaum, Lawrence
Cohort: September 2017
Expected Graduation Date: November 2022
Research Statement: My research is broadly focused on the computational modeling of human conversations, lying mainly in the subfield of Natural Language Processing but also interfacing with Human-Computer Interaction, Recommender Systems, Information Retrieval, and Machine Learning.
Victor Soares' Website
Email Victor Soares

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
Email Sayak

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
Email Peter

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
Email Connie

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: Artificial Intelligence
Advisor(s): Forbus, Kenneth
Cohort: September 2016
Email Kezhen

Student Track: CSLS
Cohort: September 2019
Email Yuehan

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

Student Track: Theory
Research Area: Algorithms
Advisor(s): Vijayaraghavan, Aravindan
Cohort: June 2017
Expected Graduation Date: August 2023
Research Statement: Aidao is broadly interested in Theoretical Computer Science. Currently, his work focuses on extracting hidden information from (potentially noisy) data in a provable manner.
Aidao's Website
Email Aidao

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
Email Melissa

Student Track: Artificial Intelligence
Research Area: Computational Biology
Advisor(s): MacIver, Malcolm; Argall, Brenna
Cohort: January 2016
Expected Graduation Date: March 2023
Research Statement: I create biological planning models using AI techniques.
Angel Espinosa's Website
Email Angel Espinosa

Student Track: Artificial Intelligence
Advisor(s): Birnbaum, Lawrence
Cohort: September 2013
Email Jason

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
Email Chris

Student Track: TSB
Advisor(s): Shaw, Aaron
Cohort: September 2020
Expected Graduation Date: 2025
Carl's Website
Email Carl

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
Email Yuan

Student Track: Artificial Intelligence
Research Area: Natural Language Processing
Advisor(s): Downey, Douglas
Cohort: September 2018
Expected Graduation Date: December 2023
Research Statement: My research focus is primarily in natural language processing and machine learning This includes commonsense reasoning and active learning, and more recently I am exploring large-scale mining and analysis of entities from scientific documents to both generate new research ideas and detect methodological pitfalls in papers.
Michael's Website
Email Michael

Student Track: TSB
Advisor(s): Horvat, Emoke-Agnes
Cohort: September 2018
Email Henry Kudzanai

Student Track: TSB
Research Area: HCI
Advisor(s): Gergle, Darren; Piper, Anne Marie
Cohort: June 2021
Expected Graduation Date: August 2022
Research Statement: My doctoral research focuses on understanding and designing for accessible collaborative content production in ability-diverse teams, i.e., teams involving people with and without disabilities. In this space, I have investigated how accessibility is created and negotiated in the contexts of collaborative writing, creative making, and remote work; in teams of blind and sighted individuals as well as among neurodivergent professionals. I take a human-centered, community-based research approach combining in-depth qualitative studies (e.g., contextual interviews, ethnographic field observations) with iterative system building and evaluation. Some examples of my work include developing new auditory techniques for enhancing accessibility in asynchronous and synchronous collaborative writing, an audio-enhanced loom for accessible weaving, and an audio-tactile tool for accessible drafting of fabric patterns. I also draw on Disability Studies literature to critically interrogate what roles technologies play in reshaping group dynamics and redistributing the labor of creating access in ability-diverse teams.
Maitraye's Website
Email Maitraye

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
Email Govinda

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: Systems
Research Area: Compilers
Advisor(s): Campanoni, Simone
Cohort: March 2016
Expected Graduation Date: June 2023
Research Statement: I am interested in how compilers can take advantage of programs' properties to generate novel code optimizations and transformations. Specifically, I have worked on STATS; a compiler for nondeterministic programs that takes advantage of their randomization property to automatically parallelize them. I am also interested in how the synergy between compilers and runtimes can lead us to the creation of effective developer tools to better understand the properties and behavior of programs.
Enrico Armenio's Website
Email Enrico Armenio

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
Email Walker

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: Systems
Research Area: Parallel Systems, High Performance Computing
Advisor(s): Dinda, Peter
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: Griffin is a Computer Science Ph.D.Student at Northwestern University. He is part of the Prescience Lab at Northwestern, led by Peter Dinda. Broadly, his interests lie in the realm of high-performance computing, extremely heterogeneous systems, and performance portability. More specifically Griffin is interested in improving the utilization of diverse hardware resources within/across systems by looking at solutions bridging layers of the hardware-software stack.
Griffin's Website
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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
Email Glenn

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
Email Chongyang

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
Email Hugo Flores

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
Email Radhika

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
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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: Multi-Agent Systems, Robotics
Advisor(s): Zhu, Qi
Cohort: September 2021
Expected Graduation Date: June 2026
Research Statement: I am now studying adaptation in multi-agent systems. Prior to joining Northwestern, my work focused on cyber-physical systems and swarm robotics.
Anthony'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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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: Computer Engineering
Research Area: Architecture
Advisor(s): Hardavellas, Nikos
Cohort: September 2015
Email Haiyang

Student Track: Artificial Intelligence
Research Area: Agent-Based Modelling
Advisor(s): Wilensky, Uri
Expected Graduation Date: June 2023
Research Statement: I research and develop tools and techniques for simulating and analyzing complex systems. In particular, my work focuses on extending the capabilities of traditional agent-based modeling, analyzing agent-based models with machine learning, and incorporating machine learning techniques into the behaviors of agents.
Bryan's Website
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Student Track: CSLS
Research Area: HCI
Advisor(s): Kay, Matthew
Cohort: September 2019
Expected Graduation Date: June 2024
Email Maryam

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: Computer Engineering
Research Area: High-Performance Computing
Advisor(s): Choudhary, Alok
Cohort: September 2016
Expected Graduation Date: December 2022
Research Statement: My research focus on parallel I/O performance on large scale super computers. Most of my projects are about improving the I/O performance and efficiency in high-level parallel I/O libraries.
Kai-Yuan's Website
Email Kai-Yuan

Student Track: Artificial Intelligence
Research Area: Machine Learning
Advisor(s): Liu, Han
Cohort: September 2021
Expected Graduation Date: 2026
Research Statement: My primary research interests lie at the intersection of modern artificial intelligence, physics, and mathematics.
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
Email Evey

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
Email Zanhua

Student Track: CSLS
Advisor(s): Horn, Michael
Cohort: September 2020
Email Ayse

Student Track: TSB
Cohort: June 2022
Email Monisola Mercy

Student Track: Computer Engineering
Research Area: Machine Learning
Advisor(s): Zhu, Qi
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: I mainly focus on machine learning and its application in autonomous driving, including perception, prediction and planning modules. My research contains both system-level design with an emphasis on safety and connectivity and ML algorithm level design with emphasis on generative models and adversarial robustness.
Ruochen's Website
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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: Systems
Research Area: Networking
Advisor(s): Bustamante, Fabian
Cohort: September 2017
Email Byungjin

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
Email Negar

Student Track: Computer Engineering
Research Area: Architecture
Advisor(s): Hardavellas, Nikos
Cohort: January 2018
Expected Graduation Date: December 2023
Research Statement: My current research interests are at the intersection of computer architecture and compilers for energy-efficient high-performance computing. My earlier PhD work include AccelWattch, a power modeling framework for modern GPUs and ST2GPU, an energy-efficient GPU Architecture Design.
Vijay's Website
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Student Track: Interfaces
Research Area: Robotics, Graphics
Advisor(s): Cossairt, Oliver Strides
Cohort: September 2018
Expected Graduation Date: 2023-2024
Research Statement: I have a broad interest in artificial intelligence and its applications. Previously, my research focused on 2nd generation neural networks – ANNs, including numerical analysis and their applications in recommender systems and computer vision. And my current research focuses on 3rd generation neural networks – SNNs and their event-driven neuromorphic applications in vision, audio, and robotic learning. I believe building SNNs with the lessons from ANNs can lead us to energy-efficient human-like artificial intelligence.
Peng'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

Cohort: September 2021
Email Aman

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: Interfaces
Research Area: Data Visualization
Advisor(s): Hullman, Jessica
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: My research interests include responsive visualization, visualization retargeting, and design research. Responsive visualization refers to adapting visualizations for different devices, such as desktop/laptop, smartphone, etc., to address recent increases in mobile readers to web-based data visualizations. My current work focuses on mixed-initiative systems to support an author choosing among responsive transformations given a source visualization. In a broader sense, I am interested in tools for retargeting data visualizations for different audience, context, and goals. Lastly, I collaborate on various design research projects for sexual violence survivors, caregivers for people with dementia, and novice researchers.
Hyeok's Website
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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: Computer Engineering
Research Area: Embedded Systems
Advisor(s): Dinda, Peter; Hester, Josiah
Cohort: September 2019
Email Chris

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.
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Student Track: TSB
Research Area: HCI
Advisor(s): O'Rourke, Eleanor
Cohort: September 2019
Expected Graduation Date: June 2024
Research Statement: Learning how to program is hard, and many students in introductory computer science courses struggle to overcome programming challenges on their own. As computer science courses continue to grow in size, however, it becomes increasingly important for students to be able to do so. In order for students to tackle problems in these self-directed ways, they need to "learn how to learn" by developing important metacognitive learning skills such as planning, reflecting, and seeking help, which allow students to regulate their learning process. In my research, I explore the learning struggles that students face in computer science, and build tools to help support their process of monitoring, diagnosing, and addressing the underlying issues behind them.
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