CV

Education

• B.S. in GitHub, GitHub University, 2012
• M.S. in Jekyll, GitHub University, 2014
• Ph.D in Version Control Theory, GitHub University, 2018 (expected)

Work experience

• Summer 2015: Research Assistant
  • Github University
  • Duties included: Tagging issues
  • Supervisor: Professor Git
• Fall 2015: Research Assistant
  • Github University
  • Duties included: Merging pull requests
  • Supervisor: Professor Hub

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

Chain FL: Decentralized Federated Machine Learning via Blockchain

Integrating Image Data Extraction and Table Parsing Methods for Chart Question Answering

Chart-to-Text: A Large-Scale Benchmark for Chart Summarization

ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Chart Question Answering: State of the Art and Future Directions

UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning

Do LLMs Work on Charts? Designing Few-Shot Prompts for Chart Question Answering and Summarization

LongFin: A Multimodal Document Understanding Model for Long Financial Domain Documents

ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning

Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs

BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks

Apriel-1.5-15b-Thinker

LLM-based data science agents: A survey of capabilities, challenges, and future directions

Improving GUI Grounding with Explicit Position-to-Coordinate Mapping

Scope: Selective Cross-modal Orchestration of Visual Perception Experts

Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reasoning?

Learning or Cheating? Assessing Data Contamination in Large Vision-Language Models

Colflor: Towards Bert-Size Vision-Language Document Retrieval Models

BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks

ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild

Masry, A., Thakkar, M., Bajaj, A., Kartha, A., Hoque, E., & Joty, S. (2025). ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild. COLING 2025.

COLMATE: Contrastive Late Interaction and Masked Text for Multimodal Document Retrieval

ChartQAPro: A more diverse and challenging benchmark for chart question answering

BigCharts-R1: Enhanced Chart Reasoning with Visual Reinforcement Finetuning

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding

DashboardQA: Benchmarking Multimodal Agents for Question Answering on Interactive Dashboards

Talks

Multimodal Chart Understanding with VLMs Permalink

March 01, 2025

Invited Talk at Alexandria University, Alexandria, Egypt

NLP+Vis: Data Visualization Understanding with VLMs Permalink

September 01, 2025

Invited Talk at Koc University, Istanbul, Turkey

Data Visualization Understanding with VLMs Permalink

December 05, 2025

Invited Talk at McGill University (McGill NLP Group), Montreal, Quebec

Teaching

Undergraduate Teaching Assistant

Teaching Assistant

Service and leadership

• Currently signed in to 43 different slack teams