Amin Karimi Monsefi
Ph.D. Candidate · Computer Science · The Ohio State University
I am a Ph.D. candidate in Computer Science at The Ohio State University, advised by Professor Rajiv Ramnath. My research advances efficient and controllable generative models and the representations that power them — few-step diffusion and flow matching across both continuous (vision) and discrete (language) spaces, self-supervised and vision–language pretraining, and the translation of both into high-impact scientific domains. I am also a machine-learning research intern with the Apple MIND team, working on few-step discrete diffusion and flow matching for large-scale text generation.
News
- 2026 New Serving as a reviewer for NeurIPS 2026, WACV 2026, and BMVC 2026.
- 2026 Recognized as a Silver Reviewer for ICML 2026.
- Jan 2026 FS-DFM — fast and accurate long-text generation with few-step diffusion language models — accepted at ICLR 2026.
- 2025–26 Received the Graduate Research Award from the OSU Department of Computer Science and Engineering.
- Jul 2025 ISOSNet accepted in Biomedical Optics Express.
- Jun 2025 TaxaDiffusion accepted at ICCV 2025.
Research Interests
Diffusion & Flow Matching in Continuous Space
Controllable and physics-aware generative models for images and video, with few-step samplers that approach or surpass thousand-step teachers.
Discrete Diffusion & Flow Matching for Language
Diffusion language models that close the gap with autoregressive systems while staying parallel and bidirectional — step-aware discrete flow matching, trajectory distillation, and RL with per-step credit assignment.
Self-Supervised & Vision–Language Representation Learning
Pretraining objectives that capture fine-grained structure, underpinning downstream generation, recognition, and segmentation.
Applied Generative Learning for Scientific Domains
Translating these methods to biodiversity, 3D medical imaging, and multimodal spatiotemporal prediction for smart mobility.
Selected Publications
- ICLR 2026
FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models - Journal 2025 ISOSNet: A Unified Framework for Cone Photoreceptor Detection and Inner/Outer Segment Length Measurement from AO-OCT B-Scans
- ICCV 2025
TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation - ICLR 2025
Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning - KDD 2024
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain - KDD 2023 Novel Physics-Based Machine-Learning Models for Indoor Air Quality Approximations
Show more publications
- CVPR-W 2025
KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models - ICLR-W 2025
DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks - Journal 2024 Reducing Manual Labeling Requirements and Improved Retinal Ganglion Cell Identification in 3D AO-OCT Volumes Using Semi-Supervised Learning
- SIGSPATIAL-W 2023 CrashFormer: A Multimodal Architecture to Predict the Risk of Crash
- Journal 2023 Smart and Collaborative Industrial IoT: A Federated Learning and Data Space Approach
- SIGSPATIAL 2022 Will There Be a Construction? Predicting Road Constructions Based on Heterogeneous Spatiotemporal Data
Full list on the publications page and on Google Scholar.
Experience
ML Research Intern — Apple, MIND Team- Developed FS-DFM, a step-aware discrete flow-matching framework that matches the quality of 1024-step diffusion baselines in 8 steps (128× speedup), outperforming LLaDA-8B and Dream-7B while being 40× smaller. [ICLR 2026]
- Designed reinforcement-learning methods for diffusion language models based on per-step credit assignment and stratified likelihood estimation, improving reasoning on MATH-500, GSM8K, and Sudoku at zero extra inference cost.
- Developed trajectory-shaping techniques for discrete flow distillation — energy-guided navigation and a contrastive curriculum — enabling a distilled 8-step student to surpass its 1024-step teacher.
- Machine Learning Intern — Higharc
- Conducted research on semantic and panoptic segmentation for architectural floor plans.
- Pre-trained a DETR-based model on unlabeled data, addressing the scarcity of labeled examples with self-supervised learning.
- Implemented domain-adaptation approaches to generalize models across datasets with distinct distributions, and strategies to transfer a trained model between domains.
- Senior Machine Learning Engineer — JIBB
- Built computer-vision pipelines for object detection and dynamic content filtering across images and video for a handwriting-capture platform.
- Developed custom CNN architectures to detect content color and remove shadows and reflections.
- Created automated tooling that improved visual clarity in real-time handwriting sessions.
- CTO — BlueBitSoft
- Designed the high-level architecture for pharmacy software solutions, targeting scalability, reliability, and efficiency.
- Aligned technical strategy with business goals across software and domain-expert teams.
- Introduced agile practices and CI/CD pipelines, and led work on performance, security, and regulatory compliance.
- Senior Data Scientist & Back-End Developer — TAPSI
- Developed AI-powered pricing microservices in Python, communicating over RabbitMQ for real-time fare adjustment.
- Designed a GPS anomaly-detection system to prevent fraud and protect rider safety.
- Built data-driven recommendation features (origin, destination, favorite places) using unsupervised learning.
- Created an ETA microservice from live driver GPS traces and published the underlying method.
- Engineered a spatiotemporal forecasting tool to predict high-demand ride areas across urban regions.
Academic Service
| Venue | Reviewing | Recognition |
|---|---|---|
| NeurIPS | 2026 | — |
| ICML | 2026 | Silver Reviewer (2026) |
| ICLR | 2025, 2026 | — |
| CVPR | 2025, 2026 | — |
| ECCV | 2026 | — |
| WACV | 2025, 2026 | — |
| BMVC | 2026 | — |
| ACM SIGKDD | 2024, 2025, 2026 | Outstanding Reviewer (top 10%, 2025 second round) Excellent Reviewer (top 20%, 2025 first round; 2026) |
Awards & Honors
- 2025–26 Graduate Research Award, Department of Computer Science and Engineering, The Ohio State University. Selected by the OSU CSE Department for distinguished research contributions in generative modeling.
- 2026 Silver Reviewer, ICML 2026.
- 2025 Outstanding Reviewer (top 10%) and Excellent Reviewer (top 20%), ACM SIGKDD.
- 2022 Student Travel Award, 30th ACM SIGSPATIAL Conference.
- 2009 Bronze Medal, University of Waterloo Mathematics Olympiad.
Education & Early Research
- Ph.D. in Computer Science — The Ohio State University, Columbus, Ohio
- M.Sc. in Computer Engineering (Software) — Shahid Beheshti University, Tehran
- B.Sc. in Computer Engineering (Hardware) — Shahid Beheshti University, Tehran