PhD Students

 

  • Research Interests: Large Language Models (LLMs), AI for Network Security, Machine Learning, Computer Vision.
    Personal website: https://alialfatemi.github.io/
    Contact: [email protected]

  • Research Interests: Blockchain, AI, Cybersecurity.
    Contact: [email protected]

  • Research Interests: Computer Vision, Control Systems, and Robotics.
    Website: https://storm.cis.fordham.edu/~cking74
    Contact: [email protected]

  • Research Interests: Trustworthy Machine Learning, AI Security, and Privacy
    Personal Website: https://jessegator.github.io/
    Contact: [email protected]

  • Bio: Naseem Machlovi is a first-year Ph.D. student at Fordham University. He received his Master’s Degree in Data Science from Fordham University with a thesis on the interpretability and explainability of LLM models. He has extensive experience ranging from academic teaching to working with industry professionals. His research interests focus on the trustworthiness of LLMs and modern AI tools while maintaining a high level of transparency. He enjoys hiking trails, playing ping pong, and socializing. Contact: [email protected]

  • Research Interests: Deep Reinforcement Learning, Representation Learning, AI for Science.

    Personal Website: https://fernandoml.me/

    Contact: [email protected]

  • Bio: Miguel Palma is a first-year PhD student at Fordham University. He finished his Bachelors in Computer Science in Ateneo de Manila University and then worked as a data analyst and cloud software developer for 6 years. His main research interests are in algorithms, graph theory, and computational geometry and is currently looking to enter the intersection of distributed systems and quantum computing research. His hobbies include self-studying higher mathematics, playing badminton, as well as playing and programming video games.

  • Bio:  Nasim Paykari, a third-year PhD candidate in computer science at Fordham University, is interested in a variety of research topics, including robotics, blockchain, computer vision, and artificial intelligence. He is highly committed to both research and teaching and finds joy in multiple-disciplinary work! Furthermore, he has over 12 years of industry experience, mostly in control system engineering, with knowledge in a wide range of FGS, ESD, DCS, and PLC technologies.

    Contact:  [email protected]

  • Bio:  Yuanhong Wu is a second-year PhD student at Fordham University. Before he came to Fordham, he studied statistics in the Statistics and Data Science department at University of Texas at El Paso for his Master's degree. His research interests mainly focus on Statistics, Machine Learning, and Natural Language Processing. In his leisure time, he likes lifting weights, cooking, and playing ping pong and badminton.

  • Contact: jxu246@fordham.edu

    Personal Webpage: https://storm.cis.fordham.edu/~jxu246

  • Bio:  Zihan Zhang is a PhD student in Computer Science at Fordham University. Her research areas of interest include the Design and Analysis of Algorithms and Computational Complexity, more specifically, algorithms related to the disjunctive normal forms of Boolean functions. She is actively open to scientific collaborations. 

    Contact: [email protected]

  • Bio: Panayiotis is a third-year Ph.D. student in Computer Science at Fordham University conducting research in system design. He holds a B.Sc. in Applied Physics and Mechanical Engineering and an M.Sc. in Computer Engineering from NYU. His research primarily focuses on quantum computing systems and artificial intelligence, including optimized implementations using CUDA libraries, simulations and simulators, and safety and control layers designed to support deterministic safety and auditability. He approaches research from a systems perspective, with an emphasis on thorough analysis and creative engineering solutions.
    Research Interests: System Design, Quantum Computing Systems, Artificial Intelligence, CUDA, Simulation, Safety and Control Systems.
    Personal website: https://www.linkedin.com/in/panayiotis-christou/
    Contact: [email protected]

  • Bio: Zefan Du is a Ph.D. student in Computer Science at Fordham University. He holds a B.S. in Mathematics from Purdue University and an M.S. in Data Science from Fordham University. His research focuses on quantum computing systems, including hardware-aware quantum compilation, distributed and modular quantum compilers, and neutral-atom architectures. He develops compiler techniques for circuit optimization, calibration-aware qubit mapping, cross-layer gate scheduling, and communication management to improve execution efficiency under hardware constraints. His work takes a systems perspective, connecting quantum algorithms with the practical challenges of scalable quantum computing.
    Research Interests: Quantum Computing Systems, Quantum Compiler Design, Hardware-Aware Compilation, Distributed Quantum Computing, Qubit Mapping and Gate Scheduling, Neutral-Atom Architectures, Quantum–Classical Hybrid Systems.
    Contact: [email protected]

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  • Bio: Jinsheng Luo is a Ph.D. student in Computer Science at Fordham University. His research interests lie at the intersection of machine learning and computational neuroscience. His current work focuses on computational modeling and analysis of Drosophila neural circuits.
    Contact: [email protected]

  • Bio: Evans Owusu is a Ph.D. candidate in Computer Science at Fordham University. His research interests include cybersecurity, intrusion detection systems, artificial intelligence, machine learning, large language models, agentic AI, ensemble learning, data and information fusion, and change-point detection. His current research focuses on developing intelligent and adaptive approaches that leverage information fusion and agentic AI to detect and respond to complex denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks. He holds two master’s degrees—one in Computer Science from Fordham University and the other in Applied Mathematics from Gaziantep University, Turkey—and has extensive industry experience in software engineering.

    Contact: [email protected]

  • Bio: Eric is a Ph.D. candidate in Computer Science at Fordham University working on physics-informed computer vision. His research focuses on 2D-to-3D super-resolution, denoising, and reconstruction for applications in scientific simulations.
    Research Interests: Physics-Informed Computer Vision, 2D-to-3D Super-Resolution, Denoising, Scientific Reconstruction, Scientific Simulations.
    Contact: [email protected]

  • Bio: Maryam is a Ph.D. candidate in Computer Science at Fordham University whose research lies at the intersection of trustworthy artificial intelligence, uncertainty quantification, and machine learning. Her work focuses on understanding and measuring uncertainty in large language models, with particular attention to how different sources of uncertainty influence model confidence, reliability, and decision-making. She develops methods that enable AI systems to better recognize the limits of their knowledge, assess when their predictions can be trusted, and identify when human oversight may be necessary. Her broader research goal is to advance reliable AI systems capable of supporting informed decision-making in uncertain and high-stakes environments.

    Contact: [email protected]

  • Bio: Lesther Santana is a Ph.D. student in Computer Science at Fordham University. His research focuses on multi-agent systems, machine learning for cyber-physical systems, and energy-aware computing at the edge. He holds an M.S. in Data Science from Fordham University and a bachelor’s degree in Economics from Instituto Tecnológico de Santo Domingo (INTEC).
    Research Interests: Multi-Agent Systems, Machine Learning for Cyber-Physical Systems, Energy-Aware Edge Computing.
    Contact: [email protected]

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  • Bio: Yunshuo (Kyle) Tian is a Ph.D. student in Computer Science at Fordham University. He received his M.S. in Data Science from Fordham University.
    Research Interests: Reinforcement Learning, Contrastive Learning.
    Personal website: https://www.linkedin.com/in/kyle-t-102bb428b/
    Contact: [email protected]

  • Bio: Sifat Nawrin Nova is a Ph.D. student in Computer Science at Fordham University. Her research focuses on cybersecurity, security and privacy, distributed computing, and trustworthy AI/ML. Her previous research has explored privacy leakage in machine learning models, security in decentralized federated learning, fault-tolerant distributed systems, and privacy-preserving technologies. She has an academic background in Computer Systems and Networks and Information and Communication Engineering. Her broader research interests include developing secure, privacy-preserving, and resilient intelligent systems.
    Research Interests: Cybersecurity, Security and Privacy, Distributed Computing, Trustworthy AI/ML, Federated Learning, Privacy-Preserving Technologies.
    Personal website: Google Scholar
    Contact: [email protected]