Mahnoosh Alizadeh
UC Santa Barbara · Electrical & Computer Engineering

Mahnoosh Alizadeh

UC Santa Barbara · Electrical & Computer Engineering

I am currently an Associate Professor in the department of Electrical & Computer Engineering at the University of California Santa Barbara. I am also affiliated with the Institute for Energy Efficiency and the Center for Control, Dynamical Systems and Computation. My research group develops mathematically principled tools for real-time, robust decision-making in cyber-physical systems. Our work spans fundamental questions in networks, optimization, control, and artificial intelligence, as well as applications in smart grids and electric transportation systems.

We are especially interested in settings where safety, uncertainty, and limited information make online decision-making both mathematically challenging and practically consequential.

Prior to joining UC Santa Barbara, I spent two years at Stanford University as a postdoctoral scholar. I received my PhD degree in Electrical and Computer Engineering from the University of California Davis in 2014. I was a recipient of the National Science Foundation CAREER award in 2019, and currently serve as Associate Editor of the IEEE Transactions on Control of Network Systems and IEEE Control Systems Magazine.

Control Learning Optimization Game Theory Energy Systems Cyber-Physical Systems

Research threads

Safe learning & online control

My lab's interest in safe learning originally grew out of demand response problems in power systems, where even a single exploratory action can be physically unacceptable. Motivated by these stage-wise safety constraints, which cannot be violated at any point during the learning process, we have studied stage-wise safety in bandits, online convex optimization, and learning-based control, with an emphasis on guarantees that are meaningful for safety-critical systems rather than only average-case performance.

Distributed optimization

A recurring thread in my lab's work is the design of distributed optimization and resource-allocation algorithms for large-scale multi-agent systems where privacy, scalability, and limited information make centralized control unrealistic. This includes resilient and communication-efficient optimization methods for networked decision-making, as well as more recent work on decentralized learning for modern machine learning systems. Across these problems, we are interested in how distributed computation, statistical efficiency, and system structure interact when learning and optimization must be carried out across many agents.

Game theory

Game theory is another core thread of my research, with a strong emphasis on theoretical questions in multi-agent systems and resource allocation. We are particularly interested in how incentives, timing, information structures, and asymmetries shape equilibrium behavior in competitive and cooperative settings. This has led to a body of work on General Lotto and related games, as well as broader questions involving coordination, strategic behavior, and equilibrium analysis in networked systems and electric vehicle applications.

Energy systems & transportation electrification

Energy systems are a central application area for our group, and much of our work is motivated by concrete operational challenges in electricity markets, demand response, smart grids, electric vehicle charging, and coupled power-transportation networks. We develop models, algorithms, and pricing mechanisms that are mathematically principled but designed with deployment and practical implementation in mind, including work on charging coordination, congestion-aware pricing, and demand-side flexibility.

Publications

A full list is also on Google Scholar

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✦ Hover over a paper title to see a brief summary of the problem and contribution.

Preprints
  • 2026
    Low-rank Adaptation is All You Need for Few-shot Adversarial Robustness in Vision–Language Models
    Problem: Vision-language models are vulnerable to adversarial perturbations, while standard robust fine-tuning can be too expensive for few-shot adaptation.
    Contribution: Uses low-rank adapters in an adversarial training objective to improve robustness while keeping the trainable footprint small.
    S. Ghiasvand, H. E. Oskouie, M. Alizadeh, R. Pedarsani
  • 2026
    Problem: Deep multi-modal prompting improves VLM adaptation, but can require millions of trainable parameters and overfit in few-shot regimes.
    Contribution: Introduces low-rank vision and text prompts with consistency and alignment terms, achieving a strong accuracy-efficiency tradeoff with 11.5K trainable parameters.
    S. Ghiasvand, H. E. Oskouie, M. Alizadeh, R. Pedarsani
  • 2026
    Problem: Online non-stochastic control algorithms are usually compared against steady states attainable by constant inputs, which limits the benchmark class.
    Contribution: Achieves √T regret against the richer class of affine-controller steady states using an FPL-style optimization method with batching for stability.
    V. Hebbar, S. Hutchinson, M. Alizadeh, C. Langbort
  • 2026
    Problem: EV charging combines continuous charging schedules with binary station-access decisions, making traditional marginal pricing difficult.
    Contribution: Uses copositive duality to construct marginal prices for charging and station access, capturing EVSE congestion with revenue adequacy and user incentive guarantees.
    N. Jiang, Y. Zhou, J. A. Taylor, M. Alizadeh
  • 2026
    Problem: Adaptive LQR with unknown dynamics, unbounded disturbances, and state-input safety constraints lacks near-optimal regret guarantees.
    Contribution: Proves Õ(√T) regret with chance-constraint satisfaction using an optimistic SDP policy search followed by a safety-scaling step.
    S. Hutchinson, N. Jiang, M. Alizadeh
Journal Publications
Select CS-style Conference Proceedings
  • 2026
    S. Ghiasvand, M. Alizadeh, R. Pedarsani
    14th Int'l Conference on Learning Representations (ICLR)
  • 2025
    S. Ghiasvand, Y. Yang, Z. Xue, M. Alizadeh, Z. Zhang, R. Pedarsani
    Findings of the Association for Computational Linguistics (ACL)
  • 2025
    S. Hutchinson, M. Alizadeh
    42nd Int'l Conference on Machine Learning (ICML)
  • 2025
    Optimistic Safety for Linearly-constrained Online Convex Optimization
    S. Hutchinson, T. Chen, M. Alizadeh
    Int'l Conference on Artificial Intelligence and Statistics (AISTATS)
  • 2024
    Directional Optimism for Safe Linear Bandits
    S. Hutchinson, B. Turan, M. Alizadeh
    Int'l Conference on Artificial Intelligence and Statistics (AISTATS)
  • 2022
    Parameter and Feature Selection in Stochastic Linear Bandits
    A. Moradipari, B. Turan, Y. Abbasi-Yadkori, M. Alizadeh, M. Ghavamzadeh
    39th Int'l Conference on Machine Learning (ICML) — Spotlight
  • 2020
    Stage-wise Conservative Linear Bandits
    A. Moradipari, C. Thrampoulidis, M. Alizadeh
    Advances in Neural Information Processing Systems (NeurIPS)
  • 2019
    Linear Stochastic Bandits under Safety Constraints
    S. Amani, M. Alizadeh, C. Thrampoulidis
    Advances in Neural Information Processing Systems (NeurIPS), pp. 9256–9266
Conference Proceedings
  • 2025
    Decentralized Low-rank Fine-tuning of Large Language Models
    S. Ghiasvand, M. Alizadeh, R. Pedarsani
    1st Workshop for Research on Agent Language Models (REALM), pp. 334–345
  • 2025
    Online Nonstochastic Control with Convex Safety Constraints
    N. Jiang, S. Hutchinson, M. Alizadeh
    American Control Conference (ACC)
  • 2025
    N. Jiang, H.-T. Wai, M. Alizadeh
    IEEE Conference on Decision and Control (CDC)
  • 2025
    Y. John, V. Shah, J. A. Preiss, M. Alizadeh, J. R. Marden
    IEEE Conference on Decision and Control (CDC)
  • 2025
    The Safety-Privacy Tradeoff in Linear Bandits
    A. Zibaie, S. Hutchinson, R. Pedarsani, M. Alizadeh
    IEEE Int'l Symposium on Information Theory (ISIT)
  • 2024
    Robust Decentralized Learning with Local Updates and Gradient Tracking
    S. Ghiasvand, A. Reisizadeh, M. Alizadeh, R. Pedarsani
    60th Annual Allerton Conference on Communication, Control, and Computing
  • 2024
    Safe Online Convex Optimization with First-order Feedback
    S. Hutchinson, M. Alizadeh
    American Control Conference (ACC)
  • 2024
    Safe Online Convex Optimization with Multi-point Feedback
    S. Hutchinson, M. Alizadeh
    6th Annual Learning for Dynamics & Control Conference (L4DC), PMLR, pp. 168–180
  • 2024
    Safe Dynamic Pricing for Nonstationary Network Resource Allocation
    B. Turan, S. Hutchinson, M. Alizadeh
    6th Annual Learning for Dynamics & Control Conference (L4DC), PMLR, pp. 155–167
  • 2023
    The Impact of the Geometric Properties of the Constraint Set in Safe Optimization with Bandit Feedback
    S. Hutchinson, B. Turan, M. Alizadeh
    5th Annual Learning for Dynamics and Control Conference (L4DC), PMLR
  • 2023
    Analyzing Pre-commitment Strategies in General Lotto Games
    K. Paarporn, R. Chandan, D. Kovenock, M. Alizadeh, J. Marden
    American Control Conference (ACC)
  • 2022
    The Art of Concession in General Lotto Games
    R. Chandan, K. Paarporn, D. Kovenock, M. Alizadeh, J. R. Marden
    Game Theory for Networks (GameNets)
  • 2022
    Multi-environment Meta-learning in Stochastic Linear Bandits
    A. Moradipari, M. Ghavamzadeh, C. Thrampoulidis, M. Alizadeh
    IEEE Int'l Symposium on Information Theory (ISIT)
  • 2022
    Real-time Electric Vehicle Smart Charging at Workplaces: A Real-world Case Study
    N. Tucker, G. Cezar, M. Alizadeh
    IEEE Power and Energy Society General Meeting
  • 2022
    Strategic Investments in Multi-stage General Lotto Games
    R. Chandan, K. Paarporn, M. Alizadeh, J. R. Marden
    IEEE Conference on Decision and Control (CDC)
  • 2022
    A Safe Pricing Mechanism for Distributed Resource Allocation with Bandit Feedback
    S. Hutchinson, B. Turan, M. Alizadeh
    IEEE Conference on Decision and Control (CDC)
  • 2022
    Safe Dual Gradient Method for Network Utility Maximization Problems
    B. Turan, M. Alizadeh
    IEEE Conference on Decision and Control (CDC)
  • 2022
    A Deployable Online Optimization Framework for EV Smart Charging with Real-world Test Cases
    N. Tucker, M. Alizadeh
    13th IEEE Int'l SmartGridComm
  • 2022
    Predicting Parameters for Modeling Traffic Participants
    A. Moradipari, S. Bae, M. Alizadeh, E. Moradi-Pari, D. Isele
    23rd Int'l Conference on Intelligent Transportation Systems (ITSC)
  • 2022
    Collaborative Multi-agent Stochastic Linear Bandits
    A. Moradipari, M. Ghavamzadeh, M. Alizadeh
    American Control Conference (ACC)
  • 2022
    The Importance of Randomization in Resource Assignment Problems
    K. Paarporn, R. Chandan, M. Alizadeh, J. R. Marden
    American Control Conference (ACC)
  • 2021
    Regret Bounds for Safe Gaussian Process Bandit Optimization
    S. Amani, M. Alizadeh, C. Thrampoulidis
    IEEE Int'l Symposium on Information Theory (ISIT)
  • 2021
    On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients
    B. Turan, C. A. Uribe, H.-T. Wai, M. Alizadeh
    American Control Conference (ACC)
  • 2021
    The Division of Assets in Multiagent Systems: A Case Study in Team Blotto Games
    K. Paarporn, R. Chandan, M. Alizadeh, J. R. Marden
    51st IEEE Conference on Decision and Control (CDC)
  • 2021
    On Robustness of Normalized Block Coordinate Descent Method for Non-convex Optimization
    B. Turan, C. A. Uribe, H.-T. Wai, M. Alizadeh
    51st IEEE Conference on Decision and Control (CDC)
  • 2020
    Generalized Linear Bandits with Safety Constraints
    S. Amani, M. Alizadeh, C. Thrampoulidis
    IEEE Int'l Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3562–3566
  • 2020
    Regret Bounds for Safe Gaussian Process Bandit Optimization
    S. Amani, M. Alizadeh, C. Thrampoulidis
    Learning for Dynamics and Control (L4DC), PMLR, pp. 158–159
  • 2020
    An Aggregate Model of the Flexible Energy Demand of Thermostatically Controlled Loads with Explicit Outdoor Temperature Dependency
    K. Hreinsson, A. Scaglione, M. Alizadeh
    HICSS-53
  • 2020
    Linear Thompson Sampling under Unknown Linear Constraints
    A. Moradipari, M. Alizadeh, C. Thrampoulidis
    IEEE Int'l Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3392–3396
  • 2020
    Mobility-aware Smart Charging of Electric Bus Fleets
    A. Moradipari, N. Tucker, T. Zhang, G. Cezar, M. Alizadeh
  • 2019
    An Online Pricing Mechanism for Electric Vehicle Parking Assignment and Charge Scheduling
    N. Tucker, B. Ferguson, M. Alizadeh
    American Control Conference (ACC), pp. 5755–5760
  • 2019
    Online Charge Scheduling for Electric Vehicles in Autonomous Mobility on Demand Fleets
    N. Tucker, B. Turan, M. Alizadeh
    IEEE Intelligent Transportation Systems Conference (ITSC), pp. 226–231
  • 2019
    Smart Charging Benefits in Autonomous Mobility-on-Demand Systems
    B. Turan, N. Tucker, M. Alizadeh
    IEEE Intelligent Transportation Systems Conference (ITSC), pp. 461–466
  • 2019
    Risk and Security Tradeoffs in Graphical Coordination Games
    K. Paarporn, M. Alizadeh, J. R. Marden
    IEEE 58th Conference on Decision and Control (CDC), pp. 4409–4414
  • 2019
    Characterizing the Interplay between Information and Strength in Blotto Games
    K. Paarporn, R. Chandan, M. Alizadeh, J. R. Marden
    IEEE 58th Conference on Decision and Control (CDC), pp. 5977–5982
  • 2019
    Resilient Distributed Optimization Algorithms for Resource Allocation
    C. A. Uribe, H.-T. Wai, M. Alizadeh
    IEEE 58th Conference on Decision and Control (CDC), pp. 8341–8346
  • 2018
    Optimal Planning of Workplace Electric Vehicle Charging Infrastructure with Smart Charging Opportunities
    B. Ferguson, V. Nagaraj, E. C. Kara, M. Alizadeh
    21st Int'l Conference on Intelligent Transportation Systems (ITSC), pp. 1149–1154
  • 2018
    Learning to Dynamically Price Electricity Demand Based on Multi-armed Bandits
    A. Moradipari, C. Silva, M. Alizadeh
    IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 917–921
  • 2018
    On the Interaction between Autonomous Mobility-on-Demand Systems and the Power Network: Models and Coordination Algorithms
    F. Rossi, R. Iglesias, M. Alizadeh, M. Pavone
    Robotics: Science and Systems (RSS)
  • 2018
    Online Pricing Mechanisms for Electric Vehicle Management at Workplace Charging Facilities
    N. Tucker, M. Alizadeh
    56th Annual Allerton Conference on Communication, Control, and Computing, pp. 351–358
  • 2018
    The Impact of Informed Adversarial Behavior in Graphical Coordination Games
    B. Canty, P. N. Brown, M. Alizadeh, J. R. Marden
    IEEE Conference on Decision and Control (CDC), pp. 1923–1928
  • 2018
    Pricing Differentiated Services in an Electric Vehicle Public Charging Station Network
    A. Moradipari, M. Alizadeh
    IEEE Conference on Decision and Control (CDC), pp. 6488–6494
  • 2017
    Wholesale Electricity Pricing in the Presence of Geographical Load Balancing
    M. A. Abdelghany, H. Mohsenian-Rad, M. Alizadeh
    51st Asilomar Conference on Signals, Systems, and Computers, pp. 653–658
  • 2017
    Marginal Charging Station Pricing in an Intelligent Electric Transportation System
    M. Alizadeh, H.-T. Wai, A. Goldsmith, A. Scaglione
    American Control Conference (ACC), pp. 3438–3444
  • 2017
    Optimal Electricity Pricing for Societal Infrastructure Systems
    M. Alizadeh, H.-T. Wai, A. Goldsmith, A. Scaglione
    50th Hawaii Int'l Conference on System Sciences (HICSS)
  • 2017
    Congestion Control and Pricing in a Network of Electric Vehicle Public Charging Stations
    P. Wong, M. Alizadeh
    55th Annual Allerton Conference on Communication, Control, and Computing, pp. 762–769
  • 2015
    The Perils of Dynamic Electricity Pricing Tariffs in the Presence of Retail Market Imperfections
    M. Alizadeh, A. Goldsmith, A. Scaglione
    49th Asilomar Conference on Signals, Systems and Computers, pp. 683–688
  • 2014
    Capturing Aggregate Flexibility in Demand Response
    M. Alizadeh, A. Scaglione, A. Goldsmith, G. Kesidis
    53rd IEEE Conference on Decision and Control (CDC), pp. 6439–6445
  • 2014
    Optimized Path Planning for Electric Vehicle Routing and Charging
    M. Alizadeh, H.-T. Wai, A. Scaglione, A. Goldsmith, Y. Y. Fan, T. Javidi
    52nd Annual Allerton Conference on Communication, Control, and Computing, pp. 25–32
  • 2013
    On Modeling and Marketing the Demand Flexibility of Deferrable Loads at the Wholesale Level
    M. Alizadeh, T.-H. Chang, A. Scaglione
    46th Hawaii Int'l Conference on System Sciences (HICSS), pp. 2177–2186
  • 2013
    Clustering Consumption in Queues: A Scalable Model for Electric Vehicle Scheduling
    M. Alizadeh, G. Kesidis, A. Scaglione
    Asilomar Conference on Signals, Systems and Computers, pp. 374–378
  • 2013
    Least Laxity First Scheduling of Thermostatically Controlled Loads for Regulation Services
    M. Alizadeh, A. Scaglione
    IEEE Global Conference on Signal and Information Processing, pp. 503–506
  • 2013
    Scalable Model Predictive Control of Demand for Ancillary Services
    M. Alizadeh, A. Scaglione, G. Kesidis
    IEEE Int'l Conference on Smart Grid Communications (SmartGridComm), pp. 684–689
  • 2013
    Incentive Design for Direct Load Control Programs
    M. Alizadeh, Y. Xiao, A. Scaglione, M. Van Der Schaar
    51st Annual Allerton Conference on Communication, Control, and Computing, pp. 1029–1036
  • 2012
    Grid Integration of Distributed Renewables through Coordinated Demand Response
    M. Alizadeh, T.-H. Chang, A. Scaglione
    51st IEEE Conference on Decision and Control (CDC), pp. 3666–3671
  • 2012
    The Emergence of Deferrable Energy Requests and a Greener Future: What Stands in the Way?
    M. Alizadeh, T.-H. Chang, A. Scaglione, C. Chen, S. Kishore
    5th Int'l Symposium on Communications, Control and Signal Processing
  • 2012
    On the Market Effects of Queueing Energy Requests as an Alternative to Storing Electricity
    M. Alizadeh, Z. Wang, A. Scaglione, C. Chen, S. Kishore
    IEEE Power and Energy Society General Meeting
  • 2012
    Coordinated Home Energy Management for Real-time Power Balancing
    T.-H. Chang, M. Alizadeh, A. Scaglione
    IEEE Power and Energy Society General Meeting
  • 2012
    A Cournot Game Analysis on Market Effects of Queuing Energy Request as Demand Response
    C. Chen, S. Kishore, Z. Wang, M. Alizadeh, A. Scaglione
    IEEE Power and Energy Society General Meeting
  • 2012
    How Will Demand Response Aggregators Affect Electricity Markets? — A Cournot Game Analysis
    C. Chen, S. Kishore, Z. Wang, M. Alizadeh, A. Scaglione
    5th Int'l Symposium on Communications, Control and Signal Processing
  • 2012
    Queuing Models for Providing Quality of Service to Transactive Loads
    A. Scaglione, M. Alizadeh, R. J. Thomas
    IEEE PES Innovative Smart Grid Technologies (ISGT)
  • 2011
    Direct Load Management of Electric Vehicles
    M. Alizadeh, A. Scaglione, R. J. Thomas
    IEEE Int'l Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5964–5967
  • 2011
    Information Infrastructure for Cellular Load Management in Green Power Delivery Systems
    M. Alizadeh, A. Scaglione, R. J. Thomas, D. Callaway
    IEEE Int'l Conference on Smart Grid Communications (SmartGridComm), pp. 13–18
  • 2011
    Demand Side Management Trends in the Power Grid
    M. Alizadeh, Z. Wang, A. Scaglione
    4th IEEE Int'l Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 141–144
  • 2011
    On the Impact of Smart Grid Metering Infrastructure on Load Forecasting
    M. Alizadeh, A. Scaglione, Z. Wang
    48th Annual Allerton Conference on Communication, Control, and Computing, pp. 1628–1636
Book Chapter
  • 2012
    New Models for Networked Control in Smart Grid
    A. Scaglione, Z. Wang, M. Alizadeh
    in Smart Grid Communications and Networking, Cambridge University Press

Group

Current members & alumni
Note to Prospective Students

I am currently looking for new PhD students. I tend to work best with students who have a strong mathematical background and are interested in interdisciplinary problems. If you are interested in joining the group, please apply to the ECE graduate program at UCSB and list me as a potential faculty advisor.

Current Ph.D. Students
Spencer Hutchinson
Spencer Hutchinson
Since Oct 2021
B.Sc. Colorado School of Mines
Arghavan Zibaei
Arghavan Zibaei
Since Jan 2023 · B.Sc. Sharif University
co-advised with R. Pedarsani
Nanfei Jiang
Nanfei Jiang
Since Oct 2023
B.Sc. SUSTech
Sajjad Ghiasvand
Sajjad Ghiasvand
Since Oct 2023 · B.Sc. Sharif University
co-advised with R. Pedarsani
Irmak Fitoz
Irmak Fitoz
Since Oct 2025
B.Sc. Bilkent University
Current Undergraduate Researchers
Lily Chen
Since Sep 2024
Yi Zhou
Since Jan 2025
Samuel Zhou
Since Feb 2026
Alumni

Ph.D.

  • Berkay Turan · Dec 2023 First position: Uber
  • Ahmadreza Moradipari · Dec 2022 First position: Toyota InfoTech Labs
  • Nathaniel Tucker · Sep 2022 First position: Apple

Postdoctoral

  • Keith Paarporn · 2018–2021 Next position: Assistant Professor, University of Colorado Colorado Springs

M.S.

  • Rey Yue · 2021–2024 First position: Resonant Inc.
  • Brian Canty · 2017–2019 First position: CACI International
  • Varun Nagaraj · 2017–2018 First position: Qualcomm

Undergraduate

  • Cody Silva · 2017 Currently: Scientist, General Motors
  • Bryce Ferguson · 2017–2018 Currently: Assistant Professor, Dartmouth College
  • Tuo Zhang · 2019–2020 Currently: Applied Scientist, Amazon
  • Kelly Lin · 2020 Currently: Software Engineer, Netflix
  • Gil Marc Sia · 2021 Freshman research intern
  • Arthur Wang · 2021–2022 Capstone project & honors thesis
  • Jovanny Ramirez · May–Aug 2025 UC LEADS summer research intern (UC Berkeley)

Teaching

Courses at UCSB