CV

Academic curriculum vitae of ROHIT M, highlighting research experience, publications, fellowships, and software systems.

Contact Information

Name Rohit Manivasagam
Professional Title AI/ML Systems & Quantitative Trading Systems
Email popingpixle@gmail.com
Location Chengalpattu / Chennai, Tamil Nadu

Professional Summary

Third-year Computer Science and Engineering student at SRM Institute of Science and Technology (SRMIST) specializing in AI/ML engineering, systems design, and quantitative trading systems. Highly passionate about Multi-Agent Reinforcement Learning (MARL), Vision Transformers, and hardware-software co-designed sustainable systems.

Experience

  • 2021 - 2023

    India

    Official Ambassador
    Atal Innovation Mission (AIM), Government of India
    Led drone technology operations, additive manufacturing, and student mentorship programs.
    • Spearheaded an intensive drone technology and UAV operations program for 30+ students, handpicking the top 6 for advanced technical mentorship in aerial flight systems and high-end photography.
    • Provided strategic design oversight and technical mentorship for 13+ student-led innovation projects submitted to the AIM national competition, guiding 2 core teams into the Top 100 and Top 300 tiers.
    • Pioneered local advancements in 3D printing applications by designing and slicing intricate structural models, including a functional prototype of an aerospace rocket.

Education

  • 2023 - 2027

    Kattankulathur, Chennai, India

    B.Tech
    SRM Institute of Science and Technology (SRMIST)
    Computer Science and Engineering
    • Third-year undergraduate researcher.
  • 2006 - 2023

    New Delhi, India

    High School Diploma
    M. L. Khanna D.A.V. Public School
    Physics, Chemistry, Mathematics, and Computer Science
    • Focus on Science and Computer Science tracks.

Projects

  • QuantAlpha

    Designing and co-developing an AI-driven, end-to-end automated alpha discovery, quantitative backtesting, and systematic execution platform. Built in partnership with technical teammate Pradeep U K.

    • Quantitative Finance & Algorithmic Execution.
  • Multi-Agent Reinforcement Learning Graph Framework

    Developed a foundational system mapping Directed Acyclic Graphs (DAGs) to track data provenance and explicitly assign deterministic rewards/credit to individual reinforcement learning agents in chaotic market environments.

    • Research paper titled ‘Deterministic Credit Assignment for Multi-Agent Portfolio Management via a Provenance DAG’.
    • Fully engineered and submitted to an IEEE conference on April 26, 2026, as part of academic track 21CSP302L.
  • Frontier Medical Imaging: Vision Transformers

    Published deep learning research utilizing a custom-implemented Vision Transformer (ViT) architecture to automate brain tumor classification, trained and benchmarked across a high-volume medical dataset containing over 50,000+ individual MRI slices.

    • Achieved a verified model classification accuracy of 96%.
    • Core Skills: Computer Vision, Medical Imaging, Deep Learning.
  • Brain Tumour Spotter

    Designed a cost-effective, web-integrated medical imaging application to accelerate initial neuro-oncology diagnostics. The computer vision model analyzes uploaded brain scans and streams classification payloads to a centralized cloud database.

    • Affiliation: M. L. Khanna D.A.V. Public School.
    • Core Skills: Medical Imaging, Supervised Learning, Computer Vision.
  • Energy Management Using Machine Learning

    Engineered an integrated chain of technologies incorporating machine learning algorithms and embedded hardware to optimize real-time power consumption, mitigating systemic 60% grid-level energy wastage.

    • Affiliation: M. L. Khanna D.A.V. Public School.
    • Core Skills: Machine Learning, Embedded Systems, Resource Optimization.
  • Open Gym Electricity Generator

    Formulated a zero-emission, dual-purpose sustainability project that converts physical workout energy into electrical current. Regulates the electrical input via basic neural network modeling and stores it in high-capacity batteries.

    • Affiliation: M. L. Khanna D.A.V. Public School.
    • Core Skills: Electronics, Hardware Interfacing, Neural Networks.

Skills

Core Paradigms (Advanced): Supervised Learning, Self-Supervised Learning (SimCLR), Predictive World Models (JEPA), Multi-Agent Reinforcement Learning
Architectures (Advanced): Vision Transformers (ViT), Directed Acyclic Graphs (DAGs), Neural Networks, Fused Hardware Kernels
Engineering Fields (Advanced): Medical Imaging Informatics, Quantitative Trading Systems, Embedded Systems Design, Systems Software Engineering
Hardware & Robotics (Advanced): Drone Piloting & UAV Flight Operations, 3D Printing / Additive Model Design, Digital Electronics
Core Ecosystem (Advanced): Python, TensorFlow, Hardware-level optimization, Data Structures & Algorithms

Certificates

  • MTA: Introduction to Programming Using Python - Microsoft Technology Associate (2021)

Academic Outreaches

  • India AI Impact Summit (2026): Attended the national AI summit at Bharat Mandapam, New Delhi (February 16 – February 20, 2026) to interface with top-tier researchers and national infrastructure designers.
  • IIT Madras Summer Internship: Applied to the Wadhwani School of Data Science and AI summer internship track.
  • National University of Singapore Cohort: Applied to the international NUS SAP cohort.
  • Harvard Medical School SAP: Applied to the competitive Semester Abroad Program (SAP) to deploy advanced Vision Transformers directly onto real-world clinical data pipelines.