activity
20142026
most citedBigFCM: Fast, Precise and Scalable FCM on Hadoop

21 citations · 34 across the 12 of their papers we have counts for

collaborators

17 papers

cs.AI2026

From Scores to Safe Sets: Exact Safety--Constrained Decoding for Medication Recommendation

Animesh Agarwal, Meysam Ghaffari, Nina Fatehi +2

Recent generative medication recommendation systems ultimately produce sets of drugs, but drug--drug interaction (DDI) constraints depend on the set as a whole. A natural post-hoc…

cs.AI2026

Verification Turns Capability Gaps into Routing Decisions: Small Language Models for Clinical Documentation

Nina Fatehi, Meysam Ghaffari, Animesh Agarwal +2

Clinical note generation from doctor--patient dialogue is high-volume and hallucination-intolerant: a fabricated laboratory value can create patient-safety risk, not a quality regr…

cs.AI2026

LearnActCoder: Role-Aware Error Memory for Adaptive Clinical Coding Agents

Meysam Ghaffari, Bhaskar Sen, Nasim Sabetpour +3

Clinical coding agents repeatedly encounter the same failure modes, including unsupported codes, missed documented conditions, specificity errors, and procedure-coding convention m…

cs.CL2026

A Multi-Agent Pipeline for Source-Grounded Synthetic Note Generation from Longitudinal Structured EHR

Nina Fatehi, Reihaneh Hassanzadeh, Meysam Ghaffari +2

Structured EHR is abundant but sparse, coded, and difficult to use directly for note-centric clinical modeling. We present MedNotes, a multi-agent synthetic data generation pipelin…

cs.AI2026

Structured Evidence Routing for Incident Risk Prediction from Multimodal Longitudinal EHRs

Animesh Agarwal, Meysam Ghaffari, Nina Fatehi +1

Incident risk prediction from longitudinal electronic health records (EHRs) is challenging because relevant signals are multimodal, weak in isolation, and distributed across irregu…

cs.CL2026

Foundation Agents Meet Agentic Deep Research: Evidence-Grounded Clinical Code Forecasting

Junda Wang, Meysam Ghaffari, Akshat Choube +3

Next-encounter ICD forecasting predicts which standardized diagnosis codes will be documented at a future visit from the longitudinal record available beforehand. The task is prosp…

cs.CL2026

Context Poisoning as Extreme-Value Attention Interference in Long-Context Language Models

Meysam Ghaffari, Nina Fatehi, Bhaskar Sen +2

Large language models can process increasingly long prompts, yet their ability to locate and use decisive evidence may degrade as irrelevant or confusable context is added. We form…

cs.CV2026

Text Over Image: Auditing Multimodal Robustness in Synthetic Medical Image Detection

Ching-Hao Chiu, Hao-Wei Chung, Gelei Xu +7

With the rapid adoption of generative AI, synthetic medical images pose growing risks, including diagnostic deception and insurance fraud. Although prior work has explored vision-l…

cs.LG2026

Reasoning Quality Emerges Early: Data Curation for Reasoning Models

Hongyi Henry Jin, Wenhan Yang, Meysam Ghaffari +2

Supervised fine-tuning (SFT) on a small, high-quality set of long reasoning traces is an effective approach for eliciting strong reasoning capabilities in Large Language Models (LL…

cs.SI2019

Next-Generation High-Resolution Vector-Borne Disease Risk Assessment

Meysam Ghaffari, Ashok Srinivasan, Anuj Mubayi +2

Vector-borne diseases cause more than 1 million deaths annually. Estimates of epidemic risk at high spatial resolutions can enable effective public health interventions. Our goal i…

cs.SI2019

High-resolution home location prediction from tweets using deep learning with dynamic structure

Meysam Ghaffari, Ashok Srinivasan, Xiuwen Liu

Timely and high-resolution estimates of the home locations of a sufficiently large subset of the population are critical for effective disaster response and public health intervent…

cs.MM2017

Duplicate matching and estimating features for detection of copy-move images forgery

Ghassem Alikhajeh, Abdolreza Mirzaei, Mehran Safayani +1

Copy-move forgery is the most popular and simplest image manipulation method. In this type of forgery, an area from the image copied, then after post processing such as rotation an…

cs.CR2016

P4QS: A Peer to Peer Privacy Preserving Query Service for Location-Based Mobile Applications

Meysam Ghaffari, Nasser Ghadiri, Mohammad Hossein Manshaei +1

The location-based services provide an interesting combination of cyber and physical worlds. However, they can also threaten the users' privacy. Existing privacy preserving protoco…

cs.DC2016★ 21 cited

BigFCM: Fast, Precise and Scalable FCM on Hadoop

Nasser Ghadiri, Meysam Ghaffari, Mohammad Amin Nikbakht

Clustering plays an important role in mining big data both as a modeling technique and a preprocessing step in many data mining process implementations. Fuzzy clustering provides m…

cs.MM2015★ 2 cited

Improving image watermarking based on Tabu search by Chaos

Mohammad Tafaghodi, Meysam Ghaffari, Alimohammad Latif +1

With the fast development of communication and multimedia technology, the rights of the owners of multimedia products is vulnerable to the unauthorized copies and watermarking is o…

cs.AI2014

Generating Graphical Chain by Mutual Matching of Bayesian Network and Extracted Rules of Bayesian Network Using Genetic Algorithm

Mostafa Sepahvand, Ghasem Alikhajeh, Meysam Ghaffari +1

With the technology development, the need of analyze and extraction of useful information is increasing. Bayesian networks contain knowledge from data and experts that could be use…

cs.AI2014★ 11 cited

Ambiguity-Driven Fuzzy C-Means Clustering: How to Detect Uncertain Clustered Records

Meysam Ghaffari, Nasser Ghadiri

As a well-known clustering algorithm, Fuzzy C-Means (FCM) allows each input sample to belong to more than one cluster, providing more flexibility than non-fuzzy clustering methods.…