LIMITS Lab
Limits of Information and Trusted Distributed Systems
Research in information theory, communication, learning, inference, and optimization for distributed systems under communication and adversarial constraints.
We develop theory and algorithms for distributed learning and inference under communication constraints, adversarial behavior, and structured models (e.g., sparsity and low rank).
About
- PI: Prof. Mayank Bakshi
- Office: SICCS 221, Flagstaff, AZ
- Research interests: information theory; distributed systems; learning and inference under communication and adversarial constraints
- Email: mayank.bakshi@nau.edu
Research
My work studies fundamental limits and practical algorithms for learning, inference, and optimization in networked systems with communication constraints and adversarial uncertainty.
- Distributed learning under adversaries: Byzantine-robust and poisoning-resilient methods; limits and tradeoffs.
- Adversarial sensing/estimation: robust detection and hypothesis testing with worst-case channel/state variation.
- Coding for learning and inference: error correction ideas for reliability and efficiency in distributed pipelines.
- Structured recovery: sparse recovery and low-rank recovery; structured estimation and inference.
- Physical-layer security: adversarial channel models and information-theoretic security.
- Optimization over networks: communication-efficient distributed optimization and statistical limits.
Openings
Fully funded PhD position (Fall 2026). Prospective students with strong preparation in mathematics and an interest in theory-driven research are encouraged to apply.
- Background: EE/CS/Math (or related). Solid preparation in probability, linear algebra, and optimization.
- What you get: close mentorship, collaboration opportunities across NAU and with other universities, and support for conference travel.
- How to apply: apply via NAU Engineering and email me your CV + a short intro.
Teaching
- Fall 2025: EE 443/543 — Foundations of Intelligent Systems / Pattern Recognition
- Spring 2026: EE 448 — Digital Signal Processing
- Spring 2026: EE 436/536 — Communication Systems
Contact
Email is the best way to reach me.
- Email: mayank.bakshi@nau.edu
- CV: CV_Mayank_Bakshi.pdf
- Google Scholar: scholar.google.com
- Address: School of Informatics, Computing, and Cyber Systems, Room 221 (SICCS), Northern Arizona University, Flagstaff, AZ, USA