Funded Ph.D. Studentship
Faculty Planning to Recruit PhD Students for Fall 2026
| Faculty Names | Research Areas | Specific Research | Expected Qualifications |
| Education, Algorithms | Computer science education and algorithms | BS or MS in Computer Science; Excellent math skills; Excellent English writing skills; Research experience; Software development experience. | |
| Zilin Bian | AI agent | AI-enabled multi-agent systems, with a primary focus on developing robust and scalable control and decision-making frameworks, with applications in automated driving, embodied robotic control etc. | MS or BS in engineering, computer science, or a related field. Preferred qualifications: proficiency in Python and modern ML frameworks (e.g., PyTorch/JAX); GPU computing (CUDA/NVIDIA stack); Strong background in machine learning (optimization, statistics, probabilistic modeling) and experience with simulation tools (SUMO, IsaacSim, CARLA); Familiarity with LLMs (e.g., training/fine-tuning workflows, data curation, and deployment). |
| Zilin Bian | GenAI: World Model | Generative World Models to simulate, predict, and reason about complex urban environments, bridging large-scale generative AI with real-world city data | MS or BS in engineering, computer science, or a related field. Preferred qualifications: proficiency in Python and modern ML frameworks (e.g., PyTorch/JAX); GPU computing (CUDA/NVIDIA stack); Strong background in machine learning (optimization, statistics |
| Lingwei Chen | Security, AI | Cybersecurity with AI/ML (data-driven methods for security applications), AI security (security of discriminative and generative AI), and resilient ML under challenging conditions and uncertainty (e.g., data imbalance, limited data, small models, training-free, multi-modal, and heterophilic structures) | Strong background in machine learning and deep learning (e.g., GNNs, LLMs, generative AI); Solid programming skills (e.g., Python, PyTorch); Familiarity with fundamental cybersecurity principles, including system, software, and AI-related security issues; Prior research experience or publications in related areas preferred. |
| Travis Desell | AI, Data Science | Time series forecasting/anomaly detection, neural architecture search, applied data science | Strong programming skills (esp. c++), software development experience, general machine learning background. |
| Yidan Hu | Security, AI | Data privacy, privacy-preserving ML, cybersecurity. | BS/MS degrees in computer science, cybersecurity, or applied mathematics; Good mathematical analysis capability and solid coding skills. |
| Matt Huenerfauth | HCI, Accessibility | HCI and accessibility, especially technology for people who are deaf or hard of hearing (DHH) | Especially interested in students who are ASL signers or who have prior experience in HCI. |
| Ashique KhudaBukhsh | AI Safety, LLM for scoail science | Verifiable social science using large language models and AI safety | Strong background in AI/ML, and a demonstrated interest in natural language processing. |
| Daniel Krutz | Quantum Computing | Quantum computing | Machine learning background; Quantum is desired but not required. |
| Yangming Lee | ML | Causal deep learning for visual perception | BS/MS in computer science or engineering; Good understanding of probabilistic theory and graph theory; Some understanding of robotic manipulators; Good programming skills in C++/Python; Good GPA or other proof of learning capability. |
| Rui Li | ML, Optimization | New AI models and algorithms in deep learning and optimization theory | Strong backgrounds in statistics, optimization, or related areas |
| Rui Li | ML, Optimization | New AI models and algorithms in deep learning and optimization theory | Strong backgrounds in statistics, optimization, or related areas |
| Pengfei Li | AI | AI-augmented online decision making at the intersection of AI and optimization | Strong mathematical skills and some familiarity with programming. |
| Pengfei Li | AI | AI-augmented online decision making at the intersection of AI and optimization | Strong mathematical skills and some familiarity with programming. |
| Yinxi Liu | Security, AI | Graph-based anomaly detection, probabilistic risk scoring, AI-driven smart contract security | Strong technical background with demonstrated experience in blockchain protocols and smart contract security; Foundational knowledge of data mining and graph-based machine learning is highly desirable to effectively tackle the project's core research problems. |
| Andy Meneely & Rajendra Raj & Sumita Mishra | Security, AI | Cybersecurity and/or AI | US citizenship required; Bachelor's in a computing-related discipline; Industry experience (including internships) is a plus. |
| Andy Meneely & Rajendra Raj & Sumita Mishra | Security, AI | Cybersecurity and/or AI | US citizenship required; Bachelor's in a computing-related discipline; Industry experience (including internships) is a plus. |
| Christian Newman | SE, Security | Program comprehension and cybersecurity, specifically exploring how developer comprehension causes or mitigates the introduction of vulnerabilities | Good background in software development; Optionally some experience in cybersecurity, user studies, and mining software repositories. |
| Tom Oh | Accessibility, AI, IoT | Assistive technology for deaf and hard of hearing | Degree(s) in engineering, CS, or HCI related fields. General AI/ML background. |
| Roshan Peiris | Accessibility | Exploring electrotactile technologies to implement assistive technologies for blind and low vision individuals | Hadrware and software skills (circuit and software design and prototyping). |
| M. Mustafa Rafique | Systems, AI | Improving the I/O path of supercomputers / High-Performance Computing (HPC) data centers for running AI and data-intensive workloads. | Excellent in operating systems, data structures, computing networks, and algorithms. |
| M. Mustafa Rafique | Systems, AI | Improving the I/O path of supercomputers / High-Performance Computing (HPC) data centers for running AI and data-intensive workloads. | Excellent in operating systems, data structures, computing networks, and algorithms. |
| Leon Reznik | AI, Security | Cybersecurity and AI | Degree in CS/SE/AI/Cybersec and strong research interests in the intersection of AI/ML and cybersecurity. |
| Carlos Rivero | AI, Theory | Study biases in datasets to evaluate link prediction over knowledge graphs. Apply information retrieval metrics to reduce these biases and improve link prediction evaluation. | MS in computer science; Excellent math skills, including graph theory, knowledge graphs and information retrieval; Excellent English writing skills; Research experience; Software development experience. |
| Ashique KhudaBukhsh & Naveen Sharma | AI, Urban science | Detecting, quantifying, and mitigating hallucinations in LLM-powered applications operating on city data | Strong background in AI/ML, and a demonstrated interest in natural language processing. |
| Hwan Shim | ML, NLP | Developing large language model (LLM)-based machine learning algorithms for applications across various scientific fields, including mapping from audio and text to EEG (electroencephalography) signals | Experience in audio/speech-related machine learning algorithms and large language models. |
| Hwan Shim | ML, NLP | Developing and implementing machine learning algorithms for the speech signal separation, transcription, and clustering | Experience in audio/speech-related machine learning algorithms and large language models. |
| Hwan Shim | ML, NLP |
EEG (electroencephalography) data analysis/processing related to auditory stimuli, designing EEG experimental paradigms and developing attention decoding algorithms for hearing-related applications with a focus on understanding auditory perception and cognitive processing. |
Strong background in neuroscience, psychology. Experience with EEG or MEG data collection and experimental design. Proficiency in EEG/MEG data analysis and signal processing. Programming skills in Python/MATLAB for data analysis and algorithm development. Interest in auditory neuroscience, attention mechanisms, and neurotechnology for hearing applications. |
| Yiming Tang | SE | Software engineering | Holder of both a Bachelor's (in computer science or software engineering) and a Master's degree. |
| Zhiqiang Tao | ML, Health | Generative AI (LLMs/LVLMs) for medical imaging and dermatology | Strong background in machine learning, computer vision, and LLMs; Experience with deep learning frameworks (PyTorch/TensorFlow) and Python programming; Interest in interdisciplinary research combining AI, biomedical imaging, and health care applications |
| Zhiqiang Tao | AI, Quantum imaging | AI-Driven Computational Imaging (quantum imaging) | Strong background in machine learning, computer vision, and LLMs; Experience with deep learning frameworks (PyTorch/TensorFlow) and Python programming; Interest in interdisciplinary research combining AI, biomedical imaging, and health care applications |
| John Thomas | AI | Artificial Intelligence, Large Language Models, Neural Signal Processing and Analysis, Biomedical Data Science, Brain-Computer Interfaces, Computational Neuroscience | Master’s degree in biomedical engineering/computing/AI/technology; Experience with developing AI-based biomedical systems; Experience with human bio-signals (EEG, EKG, EMG). |
| Alireza Vahid | Security | Security of integrated communication and sensing | Strong mathematical background, signal processing, and familiarity with remote sensing and machine learning. |
| Linwei Wang | ML, Health | AI for healthcare: utilizing AI and data mining tools for personalized healthcare | Backgrounds in biology, healthcare, data mining, and AI. |
| Linwei Wang | ML, Health | AI for healthcare: longitudinal disease progression and intervention effect modeling | Backgrounds in engineering, applied mathematics, or computer science; Strong in mathematics; Training in signal processing and/or machine learning is preferred; Certain programming experience. |
| Matt Wright | Security, AI | ML/AI applied to malware and cybersecurity problems | Strong ML skills, interest in cybersecurity. |
| Matt Wright | Security, AI | Agentic AI applied to media forensics: deepfake detection, training | Strong LLM skills, interest in applications, very strong communication skills. |
| Richard Zanibbi | AI, Document recognition | Document recognition: Models for recognition/extraction of diagrams in documents and handwriting (esp. math and chemistry) | Minimum undergrad degree in computer science with strong mathematical and programming foundations; Strong reading/writing, and communication skills ; Machine learning + Information Retrieval background helpful. |
| Richard Zanibbi | AI, Information retrieval | Multi-modal retrieval models for math, chemistry, and other modalities, including the use of LLM models for this purpose (machine learning models, human interfaces (HCI)) | Minimum undergrad degree in computer science with strong mathematical and programming foundations; Strong reading/writing, and communication skills ; Machine learning + Information Retrieval background helpful. |
| Xueling Zhang | SE, AR | Automated testing for augmented reality applications | Strong programming skills in Python and Java; Familiarity with mobile development and augmented reality (AR); Experience with software testing and automated testing tools; Experience using large language models (LLMs) and computer vision techniques to analyze images or AR outputs. |
| Xueling Zhang | SE, Security | Software privacy | Strong programming skills in Python and Java; Familiarity with mobile development and software testing; Experience with static or dynamic program analysis; Experience using large language models (LLMs) for code analysis. |
| Yiqin Zhao | Graphics, Vsion, Mobile | Computer graphics, computer vision, and mobile computing: generative models, 3D reconstructions, and inverse rendering. | Self-motivated; Prior research experiences and publication records would be a plus. |
| Derui Zhu | Security, AI | LLMs for software performance engineering | Background in machine learning, performance engineering, AI safety; solid programming skills (e.g., Python, Java); comfortable with ML frameworks such as PyTorch or TensorFlow; strong fundamentals in algorithms, data structures, and software design; excellent English writing and communication skills. Ideally experience with LLMs, peer review publications. |
| Chao Peng | Gamification, Security | Serious games and their applications in non-entertainment domains, with an emphasis on domain-oriented design, asset and data management, and related topics including but not limited to security (both user and memory access levels), gamification, and low-level computing systems. | Strong programming skills; Effective communication in interdisciplinary collaborations; Self-motivation in pursuing algorithmic and domain-specific challenges; Ability to adapt to evolving tools for proof-of-concept prototyping. |