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. |
| Daniel Krutz | Quantum Computing | Quantum computing | Machine learning background; Quantum is desired but not required. |
| Rui Li | ML, Optimization | New AI models and algorithms in deep learning and optimization theory | Strong backgrounds in statistics, optimization, or related areas |
| 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. |
| 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). |
| 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. |
| 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. |
| 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. |
| 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. |