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My professional curriculum vitae including education, experience, and research interests in AI Safety, AI for Science, Multimodal Learning, and NeuroAI.

Basics

Name Mallikarjuna Tupakula
Label ML Researcher | AI Safety & Science
Email tmallikarjuna1111@gmail.com
Url https://malli7622.github.io/
Summary Independent student researcher pursuing MS in Computer Science at Rochester Institute of Technology with full graduate scholarship. Focused on AI Safety, AI for Science, Multimodal Learning, and NeuroAI. Published sole-author work at NeurIPS'25 FM4LS workshop.

Work

  • 2024.09 - Present

    Rochester, NY, USA

    Graduate Research Assistant | ML Research
    Rochester Institute of Technology
    Independent student researcher working on AI Safety, AI for Science, Multimodal Learning, and NeuroAI. Advisor: Prof. Ashique KhudaBukhsh
    • Sole-authored publication at NeurIPS 2025 (FM4LS) on 'Thin Bridges for Drug Text Alignment: Lightweight Contrastive Learning for Target Specific Drug Retrieval' - achieving Recall@1 = 0.762 on ChEMBL and 3× scaffold-split gain over baselines
    • Co-authored publication in INFORMS Journal on Computing: developed multimodal machine-comprehension framework evaluating 48,956 YouTube Kids videos; achieved 77.5% accuracy on ScienceQA and F1 = 0.82 on CVQA dataset
    • Developing diffusion-based brain decoding pipelines using fMRI data and image reconstruction for multimodal perception tasks with Stable Diffusion and CLIP embeddings
    • Developing large-scale empathetic dialogue systems using CANDOR dataset (1 TB video/audio/text) and studying LLM neuron interpretability to align multimodal agents with human values for safer reasoning in medical and financial domains
  • 2020.12 - 2024.08

    Hyderabad, India

    Research Assistant | Pre-doctoral Program
    Indian School of Business
    Research Assistant in Pre-doctoral Program working on AI for Social Good and AI Safety problems on social media platforms. Advisor: Prof. Sumeet Kumar
    • Worked on AI for Social Good and AI Safety problems on social media platforms by processing large multimodal datasets (YouTube, Amazon, Twitter) at TeraBytes scale, leading to publications at AAAI, ASONAM, INFORMS, and ACL
    • Applied PyTorch, OpenCV, and CUDA to accelerate large-scale computer vision pipelines, optimizing training and inference speed for terabyte-scale datasets
    • Publications at top-tier venues: NeurIPS, ACL, ASONAM, INFORMS Journal on Computing, INFORMS on Data Science, and AAAI
    • Awarded prestigious Kathuria Pre-Doctoral Scholarship from Shri Nihal Chand Kathuria Education Trust
  • 2020.08 - 2020.11

    Stockholm (Remote)

    Research Intern | Core ML Team
    Spacept
    Research Intern on Core ML Team developing deep learning solutions for satellite imagery analysis. Advisor: Sergiu Iliev (Founder)
    • Developed a custom Deep Learning model for oil spill classification using Google Earth Engine and Sentinel satellite data of the Mauritius oil spill (July 2020), engineering scalable pipelines and augmentations
    • Improved accuracy from 65% to 78%, demonstrating transferability to real-world autonomous sensing applications
  • 2019.12 - 2020.03

    Chennai, India

    Research Intern | Neuromotor Team
    Indian Institute of Technology Madras
    Research Intern on Neuromotor Team working on medical imaging and CT reconstruction. Advisor: Prof. Srinivasa Chakravarthy
    • Implemented Elman-Jordan-based CT reconstruction halving projections (360 → 180) for efficient imaging AI techniques extendable to on-device simulation
  • 2019.05 - 2019.07

    Bangalore, India

    Research Intern | Research and Development Team
    Indian Institute of Management Bangalore
    Research Intern on R&D Team analyzing real-time sales data and marketing analytics. Advisor: Prof. Trilochan Sastry
    • Analyzed real-time data sales from Farmveda and predicted future sales, even further improving the sales by being actively involved in the Digital Marketing team

Education

  • June 2016 - May 2020
    B.Tech
    Acharya Nagarjuna University
    Computer Science & Engineering
  • 2024.09 - Present

    Rochester, New York, USA

    M.S
    Rochester Institute of Technology, Rochester, NY
    Computer Software & Machine Learning

Skills

Machine Learning
Computer Vision
Deep Learning
Probabilistic Modeling
Neural Networks
AI Research
AI Safety
AI for Science
Multimodal Learning
NeuroAI
Programming
Python
PyTorch
C/C++
Java
MATLAB
Data Science
Data Analysis
Visualization
Statistical Modeling

Languages

English
Fluent
Telugu
Native
Hindi
Fluent

Interests

AI Safety
Safe AI Systems
Interpretability
AI for Science
Drug Discovery
Foundation Models
NeuroAI
Multimodal Learning
Cross-modal Learning
Vision-Language Models

References

Professor Ashique KhudaBukhsh
Rochester Institute of Technology, Advisor
Professor Sumeet Kumar
Indian School of Business, Advisor

Awards

Publications