Ashikur Nobel

Ph.D. Student in Computer Science, Yeshiva University

I am a Ph.D. student and Research Assistant in Computer Science at Yeshiva University in New York. My research develops explainable AI for longitudinal health data — fuzzy-measure and Choquet integral models for survival analysis, and digital twins that forecast health biomarker trajectories. I also work on physical-layer key generation for secure wireless and IoT communication. I hold an M.S. in Cybersecurity from Southeast Missouri State University.

anobel@mail.yu.edu nobel.cse.16@gmail.com GitHub

Experience

June 2026 – Aug 2026
Adjunct Faculty
Yeshiva University, New York, NY
  • Taught the Model Context Protocol (MCP) for AI Agents course.
  • Helped students build portfolios with multi-agent, tool-based applications.
Jan 2024 – Present
Research Assistant
Yeshiva University, New York, NY
  • Conducting research on time-series and longitudinal health data trajectories.
  • Improving explainability of biomedical AI models.
Aug 2023 – Dec 2023
Graduate Assistant
Southeast Missouri State University, Cape Girardeau, MO
  • Helped faculty members with academic responsibilities.
  • Created educational materials for various courses.
Jan 2023 – June 2023
Student Worker (GRFC Grant)
Southeast Missouri State University, Cape Girardeau, MO
  • Developed a semi-automated system for student advisors to advise students based on preferences and performance.
  • Created a system for course rosters to analyze and summarize student information.

Education

In progress
Ph.D. in Computer Science
Yeshiva University, New York, NY
Dec 2023
M.S. in Cybersecurity
Southeast Missouri State University, Cape Girardeau, MO

Publications

Journal Articles

  1. Y. Liu, H. Wang, Y. Xie, and A. Nobel, “When drone-vehicle networks meets mmWave communications: Current status, challenges, and future research directions,” IEEE Wireless Communications, vol. 33, no. 4, pp. 128–136, Aug. 2026, doi: 10.1109/MWC.2026.3665474.

Conference Papers

  1. A. Liu, A. Nobel, and H. Wang, “Towards low-cost privacy preserving human pose modeling from Wi-Fi channel state information,” in Proceedings of the IEEE International Conference on E-health Networking, Application & Services (HealthCom), New York, NY, USA, 2026, to appear.
  2. A. Nobel, H. Wang, and H. Fang, “Towards eavesdropper awareness in CSI-based key generation,” in Proceedings of the IEEE International Conference on Future and Intelligent Networking (FINE), Osaka, Japan, 2026, pp. 144–151, doi: 10.1109/FINE71157.2026.00035.
  3. A. Lai, A. Nobel, H. Wang, and J. Fang, “DietTreeTalk: Translating single decision tree rules into LLM reasoning for explainable diet quality-driven diabetes prediction,” in Proceedings of the IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Pittsburgh, PA, USA, 2026, pp. 147–151, doi: 10.1109/CHASE69719.2026.00021.
  4. A. Nobel, Z. Li, H. Wang, and H. Fang, “Towards scalable low-cost framework for Wi-Fi 6 packet capture,” in Proceedings of the International Conference on Intelligent Multimedia, Networking, and Security (IMNS), Atlanta, GA, USA, 2026, pp. 1–6, doi: 10.1109/IMNS67862.2026.11655256.
  5. A. Nobel, Z. Li, H. Fang, and H. Wang, “Improving key randomness in physical-layer wireless security via semi-synchronized RSSI and cubic spline projection,” in Proceedings of the IEEE International Conference on Communications (ICC), Glasgow, United Kingdom, 2026, pp. 1–6, doi: 10.1109/ICC59461.2026.11588063.
  6. A. Cai, A. Nobel, and H. Wang, “An efficient multi-action recognition with feature selection using WiFi channel state information,” in Proceedings of the IEEE International Conference on Communications Workshops (ICC Workshops), Glasgow, United Kingdom, 2026, pp. 1–6, doi: 10.1109/ICCWorkshops63917.2026.11586305.
  7. A. Nobel, J. Matos, H. Wang, and H. Fang, “iDT-diet: Toward personalized health forecasting — An intelligent digital twin model for diet-influenced biomarker trajectories (student abstract),” in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-26), Singapore, 2026, vol. 40, no. 48, pp. 41334–41336, doi: 10.1609/aaai.v40i48.42260.
  8. A. Nobel, H. Wang, and H. Fang, “Smart ring based digital twin for healthcare application,” in Proceedings of the IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), London, United Kingdom, 2025, pp. 1–2, doi: 10.1109/INFOCOMWKSHPS65812.2025.11152985. (Best Poster Award)

Presentations

  1. A. Nobel, J. Fang, and H. Wang, “Decoding feature interactions in harmonized longitudinal data with Choquet-LASSO survival analysis,” presented at the Joint Statistical Meetings (JSM), Boston, MA, USA, Aug. 2026.

Research Projects

Diet Quality based Fuzzy Measure Models
Jan 2024 – Ongoing

Fuzzy measure-based feature aggregation and selection for non-linear survival models, tested on longitudinal health biomarker and diet quality data. Improves explainability through the Choquet fuzzy integral and LASSO selection.

Related: [10]
iDT-Diet: Intelligent Dietary Digital Twin
Aug 2025 – Dec 2025

A digital twin correlating diet quality with physiological biomarkers, integrating nutrition intake, metabolic indicators, and AI-based personalized nutrition prediction into biomarker trajectory data.

Related: [8]
Digital Twin for Smart Rings
Dec 2024 – Jan 2025

A real-time digital twin framework integrating wearable sensor data (HRV, temperature, motion) to model user health states, enabling predictive analytics for sleep, stress, and wellness monitoring.

Related: [9]
Physical-Layer Key Generation in Static Environments
Jan 2024 – Aug 2024

Methods to enhance randomness in static wireless scenarios using cubic projection, improving secure key generation for IoT systems through entropy extraction.

Related: [6]
Attacks against Wireless Reciprocity
June 2023 – Dec 2023

Experiments across wireless hardware and software configurations analyzing the effects of attacks against wireless reciprocity from internal and external interference.

Professional Service

Web Chair

Peer Review

Skills

Languages
Python, C/C++, Java, JavaScript
AI/ML
PyTorch, TensorFlow, Fuzzy Models
IoT & Hardware
Arduino, ESP32, 3D Printing

Contact

University
anobel@mail.yu.edu
Personal
nobel.cse.16@gmail.com
GitHub
github.com/anoted
Location
New York, NY