About Me

  • Full Name:Pratham Saraf
  • Phone:+1 347-793-7420
  • Email:prathamssaraf@gmail.com
  • Location:Brooklyn, New York

Hello There!

Hi there! I'm Pratham, a Master's student in Computer Science at New York University with a CGPA of 3.92/4, currently serving as a Teaching Assistant for Deep Learning, Tutor for Numerical Computing at Courant, and Research Assistant in AI & Neuroscience. I hold a B.Tech in Data Science Engineering from Manipal University Jaipur where I graduated with distinction (8.91/10 CGPA) and received the Dean's List Excellence in Academics Award.

Currently, I'm engaged in cutting-edge research projects including facial morphing detection pipelines using FISWG 19-feature frameworks with Prof. Banerjee, and vision models for behavioral neuroscience with Prof. Froemke. My research focuses on developing lightweight AI architectures, including distillation of 72B models into efficient 7B architectures for real-world deployment.

With professional experience at Hewlett Packard Enterprise, ONGC, and OnFees, I've designed server management systems reducing crashes by 30%, built predictive maintenance models lowering downtime by 25%, and developed real-time analytics platforms. I'm proficient in Python, C++, Java, JavaScript, and Dart, with expertise in TensorFlow, PyTorch, HuggingFace, and cloud technologies including AWS, Docker, and Kubernetes.

My Resume

  • Work Experience

  • Software Engineering Intern

    Hewlett Packard Enterprise (HPE), Mumbai - July 2023 - July 2024
    • Designed server management system using Isolation Forest, reducing potential crashes and vulnerabilities by 30%.
    • Built alert manager with Prometheus, Loki, and Grafana for real-time anomaly detection across distributed servers.
    • Optimized MicroStrategy analytics dashboard, reducing query latency 10x and improving performance for thousands of daily users.
    • Developed YOLO-based document classification pipeline (95% accuracy), automating sensitive info detection & masking.
    • Collaborated with cross-functional teams to deploy anomaly detection pipeline across 100+ enterprise servers.

  • Project Intern

    Oil and Natural Gas Company (ONGC), Mumbai - June 2023 - July 2023
    • Built predictive maintenance model (Random Forest, XGBoost), lowering equipment downtime by 25%.
    • Partnered with electronics team to refine feature selection, improving analysis precision by 15%.
    • Developed real-time analytics platform for sensor data visualization, increasing decision-making speed by 8%.
    • Streamlined sensor data pipelines using optimized batch processing, reducing storage overhead and improving query efficiency by 12%.

  • Software Engineering Intern

    OnFees, Mumbai - January 2023 - February 2023
    • Integrated news feed and chat widget into mobile app, boosting user engagement by 20%.
    • Contributed to 10 feature updates in EdFly app with a 15-member team, improving release velocity by 25%.

  • Education

  • New York University

    Masters in Computer Science - Expected: May 2026

    CGPA: 3.92/4.0
    TA: Deep Learning — Assisted 120+ graduate students with coursework, assignments, and lab sessions.
    Tutor: Numerical Computing — Courant Institute of Mathematical Sciences.
    RA: AI & Neuroscience Research — Working with Profs. Banerjee & Froemke on facial morphing detection pipelines and vision models for behavioral neuroscience.
    Coursework: Big Data, Artificial Intelligence, Deep Learning, Opensource Development, Information Visualization, Design & Analysis of Algorithms

    View Official Transcript

  • Manipal University Jaipur

    B.Tech in Data Science Engineering - July 2024

    CGPA: 8.91/10.0 - Received the Dean's List Excellence in Academics Award
    Coursework: Data Structures, OOPS, Computer Networks, OS, Machine Learning, NLP, Artificial Intelligence, Big Data Analytics

    View Official Transcript

Research Experience

  • Facial Morphing Detection (NYU – Forensics AI)

    Prof. S. Banerjee, NYU - July 2025 - Present
    • Built ML pipeline using FISWG 19-feature framework and CLIP-based NLP integration for forensic biometric analysis.
    • Active Research: Exploring distillation of Qwen2.5-72B models into lightweight 7B architectures for faster, resource-efficient detection.
    • Developing advanced facial morphing detection systems using PyTorch, Qwen 2.5, Molmo 2, and HuggingFace transformers.

  • Computational Neuroscience (NYU Langone)

    Prof. Robert Froemke, NYU Langone Health - July 2025 - Present
    • Automated social behaviour quantification from video using ML, improving accuracy vs. manual annotations.
    • Active Research: Developing a computer vision model to trace mice movement patterns from video data, enabling precise behavioural mapping in neural circuit studies.
    • Implementing TensorFlow and OpenCV-based systems for behavioral analysis in neuroscience research applications.

  • VR/AR Rendering Optimization (NYU Immersive Labs)

    Prof. Sun Qi, NYU Immersive Labs - July 2025 - Present
    • Designed and conducted 2AFC psychophysics studies in Unity with 50 participants, validating dichoptic foveation technique achieving 30-40% rendering compute reduction while maintaining perceptual equivalence.
    • Built production Unity application using C# implementing dichoptic rendering pipeline with multi-threaded architecture achieving real-time 60+ FPS performance across diverse VR hardware.
    • Created optimized algorithms based on 3D mathematics implementing Gaussian blur kernels, unsharp masking, and binocular fusion models to optimize visual effects while maintaining perceptual quality.

My Projects

Intelligent DNS Security Platform

GuardNet

Built an enterprise-grade DNS filtering platform blocking malware, phishing, and ads with real-time threat intelligence feeds.
Designed Go-based DNS resolver with caching, achieving <15ms response times. Developed Node.js API gateway and React dashboard.

AI Nutrition & Health Assistant

WholeSight

Developed a cross-platform mobile app with AI-powered food recognition (>90% accuracy) and multimodal logging (camera, barcode, voice, text).
Integrated Firebase and applied Clean Architecture + BLoC pattern for scalability.

Expense Tracking Application

Expensify

Built an expense tracking app using Flutter with local storage (SQLite) for data persistence and Provider state management.
Features include expense categorization, monthly analytics, and data visualization for personal finance management.

Technical Skills

Programming Languages

Python, C++, Java, JavaScript, Dart, SQL

Databases

PostgreSQL, MySQL, SQLite, MongoDB

Frameworks

TensorFlow, PyTorch, HuggingFace, Flask, React, Flutter, Hadoop

Cloud & DevOps

AWS (EC2, S3, Lambda), Docker, Kubernetes, Git, CI/CD

AI/ML & Generative AI

Computer Vision (YOLO, OpenCV), NLP (Transformers, CLIP), LLM (Gemini API), Model Training & Deployment

Tools & Platforms

Firebase, MicroStrategy, Linux, VS Code, Prometheus, Grafana

Extracurricular Activities

IEEE India Council Hackathon Mentor

IC Hack 2023

Mentored 10+ participants at the IEEE India Council Hackathon, providing guidance in app development and offering technical expertise in mobile application development and software engineering best practices.

Hire Me!

With a strong background in data science and a passion for using technology to solve complex problems, I am excited to join your team and make a significant impact on your next machine learning or deep learning project. Let's build innovative solutions together.

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