activity
20222026
most citedCueless EEG imagined speech for subject identification: dataset and benchmarks

4 citations · 7 across the 37 of their papers we have counts for

collaborators

42 papers

eess.SY2026

Distributed Algorithms for Filtering, Estimation, and Fault Detection over Cyber-Physical-Systems: A Tutorial and Survey

Mohammadreza Doostmohammadian, Mahdi Shamsi, Hadi Zayyani +4

This survey provides overview of distributed estimation, filtering, and fault detection techniques in the context of cyber-physical systems (CPS). To establish a strong foundation,…

cs.SI2026

GTIN: A Unified Scalable Framework for Joint Event and Time Prediction in Temporal Graphs

Mohammad Ostadmohammadi, Sepehr Kazemi, Hamid R. Rabiee

Temporal graphs are increasingly used to model dynamic systems across diverse domains, including social, financial, and traffic networks. Predicting both what the next event will b…

eess.SY2026

Using Non-Lipschitz Signum-based Functions for Distributed Optimization and Machine Learning: Trade-off Between Con-vergence Rate and Optimality Gap

Mohammadreza Doostmohammadian, Amir Ahmad Ghods, Alireza Aghasi +2

In recent years, the prevalence of large-scale data-sets and the demand for sophisti-cated learning models have necessitated the development of efficient distributed ma-chine learn…

cs.CV2026

MonoVoc: Decoupling Geometry and Semantics for Lightweight Monocular Open-Vocabulary 3D Gaussians

Pouya Ardekhani, Zahra Dehghanian, Morteza Abolghasemi +1

Open vocabulary 3D scene understanding is essential for next-generation interactive systems, empowering users to intuitively query and navigate reconstructed environments using nat…

cs.MM2026

Teacher-Student Structure for Domain Adaptation in Ensemble Audio-Visual Video Deepfake Detection

Elham Abolhasani, Maryam Ramezani, Hamid R. Rabiee

The rapid advancement of generative AI models is leading to more realistic deepfake media, encompassing the manipulation of audio, video, or both. This raises severe privacy and so…

eess.SY2026

Distributed Observer-based Fault Detection over Intelligent Networked Multi-Vehicle Systems

Mohammadreza Doostmohammadian, Hamid R. Rabiee

Decentralized strategies are of interest for local decision-making over multi-vehicle networks. This paper studies mixed traffic networks of human-driven and autonomous vehicles wi…

eess.IV2026

3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset

Mehran Advand, Zahra Dehghanian, Navid Faraji +3

Existing medical imaging datasets for abdominal CT often lack three-dimensional annotations, multi-organ coverage, or precise lesion-to-organ associations, hindering robust represe…

eess.SY2026

Impact of Clustering on the Observability and Controllability of Complex Networks

Mohammadreza Doostmohammadian, Hamid R. Rabiee

The increasing complexity and interconnectedness of systems across various fields have led to a growing interest in studying complex networks, particularly Scale-Free (SF) networks…

cs.LG2025

ReDiF: Resource-Efficient Few-Step Diffusion Distillation via Reinforcement Learning

Amirhossein Tighkhorshid, Zahra Dehghanian, Gholamali Aminian +2

Step distillation accelerates diffusion sampling by training a few-step student to imitate a many-step teacher, but distillation itself remains expensive. Typically, this requires…

cs.CV2025

RealDrag: The First Dragging Benchmark with Real Target Image

Ahmad Zafarani, Zahra Dehghanian, Mohammadreza Davoodi +3

The evaluation of drag based image editing models is unreliable due to a lack of standardized benchmarks and metrics. This ambiguity stems from inconsistent evaluation protocols an…

cs.CV2025

CineLOG: A Training Free Approach for Cinematic Long Video Generation

Zahra Dehghanian, Morteza Abolghasemi, Hamid Beigy +1

Controllable video synthesis is a central challenge in computer vision, yet current models struggle with fine grained control beyond textual prompts, particularly for cinematic att…

cs.SD2025

Beyond Unified Models: A Service-Oriented Approach to Low Latency, Context Aware Phonemization for Real Time TTS

Mahta Fetrat, Donya Navabi, Zahra Dehghanian +2

Lightweight, real-time text-to-speech systems are crucial for accessibility. However, the most efficient TTS models often rely on lightweight phonemizers that struggle with context…

cs.LG2025

Machine Learning and CPU (Central Processing Unit) Scheduling Co-Optimization over a Network of Computing Centers

Mohammadreza Doostmohammadian, Zulfiya R. Gabidullina, Hamid R. Rabiee

In the rapidly evolving research on artificial intelligence (AI) the demand for fast, computationally efficient, and scalable solutions has increased in recent years. The problem o…

cs.CV2025

Redefining Generalization in Visual Domains: A Two-Axis Framework for Fake Image Detection with FusionDetect

Amirtaha Amanzadi, Zahra Dehghanian, Hamid Beigy +1

The rapid development of generative models has made it increasingly crucial to develop detectors that can reliably detect synthetic images. Although most of the work has now focuse…

eess.SY2025

Distributed Automatic Generation Control subject to Ramp-Rate-Limits: Anytime Feasibility and Uniform Network-Connectivity

Mohammadreza Doostmohammadian, Hamid R. Rabiee

This paper considers automatic generation control over an information-sharing network of communicating generators as a multi-agent system. The optimization solution is distributed…

eess.IV2025

State of Abdominal CT Datasets: A Critical Review of Bias, Clinical Relevance, and Real-world Applicability

Saeide Danaei, Zahra Dehghanian, Elahe Meftah +4

This systematic review critically evaluates publicly available abdominal CT datasets and their suitability for artificial intelligence (AI) applications in clinical settings. We ex…

cs.IR2025

FIRE: Faithful Interpretable Recommendation Explanations

S. M. F. Sani, Asal Meskin, Mohammad Amanlou +1

Natural language explanations in recommender systems are often framed as a review generation task, leveraging user reviews as ground-truth supervision. While convenient, this appro…

eess.SY2025

Momentum-based Accelerated Algorithm for Distributed Optimization under Sector-Bound Nonlinearity

Mohammadreza Doostmohammadian, Hamid R. Rabiee

Distributed optimization advances centralized machine learning methods by enabling parallel and decentralized learning processes over a network of computing nodes. This work provid…

cs.LG2025

Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning

Armin Behnamnia, Gholamali Aminian, Alireza Aghaei +3

Off-policy learning and evaluation leverage logged bandit feedback datasets, which contain context, action, propensity score, and feedback for each data point. These scenarios face…

cs.GR2025

LensCraft: Your Professional Virtual Cinematographer

Zahra Dehghanian, Morteza Abolghasemi, Hossein Azizinaghsh +3

Digital creators, from indie filmmakers to animation studios, face a persistent bottleneck: translating their creative vision into precise camera movements. Despite significant pro…

cs.CV2025

Camera Trajectory Generation: A Comprehensive Survey of Methods, Metrics, and Future Directions

Zahra Dehghanian, Pouya Ardekhani, Amir Vahedi +2

Camera trajectory generation is a cornerstone in computer graphics, robotics, virtual reality, and cinematography, enabling seamless and adaptive camera movements that enhance visu…

cs.CL2025

Fast, Not Fancy: Rethinking G2P with Rich Data and Rule-Based Models

Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee

Homograph disambiguation remains a significant challenge in grapheme-to-phoneme (G2P) conversion, especially for low-resource languages. This challenge is twofold: (1) creating bal…

cs.CV2025★ 1 cited

Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions

Mohammad Mahdi Abootorabi, Omid Ghahroodi, Pardis Sadat Zahraei +17

Generative AI is reshaping art, gaming, and most notably animation. Recent breakthroughs in foundation and diffusion models have reduced the time and cost of producing animated con…

cs.IR2025

Epistemic Uncertainty-aware Recommendation Systems via Bayesian Deep Ensemble Learning

Radin Cheraghi, Amir Mohammad Mahfoozi, Sepehr Zolfaghari +3

Recommending items to users has long been a fundamental task, and studies have tried to improve it ever since. Most well-known models commonly employ representation learning to map…