Rohan Wadhawan

Life is like a puzzle in progress. In the end, we all wish that the pieces come together into a masterpiece...

I am interested in Human-inspired Artificial Intelligence research at the intersection of Computer Vision, Multimodal Learning, Generative AI, and Affective Computing. I want to develop Eco-friendly technology, Equally Accessible to All.

I am looking for Applied Research and Machine Learning Engineer Internships where I can apply my technical and soft skills to push the boundaries of innovation and customer satisfaction!

Get my Resume

Get in Touch


  • Working as a Teaching Assistant for Introduction to Computer Science II by the Computer Science Department at UCLA, Winter 2023.
  • Working as a AI studio Tutor for Break Through Tech AI program, Computer Science Department at UCLA, Fall 2022.
  • Working as a Teaching Assistant for Introduction to Programming in C++ course, offered as part of the Program in Computing, Mathematics Department at UCLA, Fall 2022.
  • Started my Graduate Studies in the Computer Science Department at University of California, Los Angeles (UCLA)


University of California, Los Angeles (UCLA)

Masters of Science in Computer Science
Los Angeles, CA
Expected June 2024

GPA: 4.0/4.0

Relevant Coursework: Large Scale Machine Learning, Reinforcement Learning

Teaching Positions:

  • Teaching Assistant - Introduction to Computer Science II, Winter 2023.
  • AI Tutor - Break Through Tech AI, Fall 2022.
  • Teaching Assistant - Introduction to Programming in C++, Fall 2022.
  • Netaji Subhas Institute of Technology, University of Delhi

    Bachelors of Engineering in Computer Engineering
    New Delhi, India
    July 2020

    Admission: Secured 2520 rank in all India Joint Engineering Entrace (JEE) Main exam, 2016
    Placed in Top 0.2% out of 1.2M candidates

    CGPA: 8.94/10.00 (1st division with Distinction, 89.4%)

    Relevant Coursework: Mathematics (Linear Algebra, Multivariate Calculus), Discrete Structres (Logic, Counting Principles, Probability, Graph Theory), Algorithms, Artificial Intelligence, Neural Networks, Big Data and Analytics

    Bachelor's Thesis title: Face Synthesis using Descriptions Extracted from Unstructured Text

    Work Experience

    Samsung R&D Institute

    Senior Software Engineer, Visual Intelligence Team
    • Enhanced tone and saturation of images rendered by the Expert Raw Application via integration of a new deep learning module to its pipeline in flagship models (S22).
    Bengaluru, India
    February 2022 - June 2022

    Samsung R&D Institute

    Software Engineer, Visual Intelligence Team
    • Deployed various camera solutions like Video Stabilization, Hyperlapse, & Single Take on existing & upcoming S (S22), A (A73), & M (M53) series smartphones & Tablets (Tab S8).
    • Developed a toolkit for fine-grained latency analysis of Samsung's propriety interface layer in the camera software stack.
    Bengaluru, India
    January 2021 - January 2022

    Nable IT Consultancy Services, a computer vision startup

    Software Engineer - Artificial Intelligence Intern
    • Improved the edge-based facial recognition system's accuracy and efficiency and made it agnostic to facial sizes.
    • Modularized facial recognition pipeline and Developed various standalone facial recognition applications on top of it.
    New Delhi, India
    January 2020 - March 2020

    Samsung R&D Institute

    Software Engineer Intern, Visual Intelligence Team
    • Programmed an android application that automated and reduced the testing time of the camera module by 90% .
    • Software used: Android Studio, Java
    Bengaluru, India
    May 2019 - July 2019

    HCL Infosystems Limited, Noida

    Summer Trainee
    • Developed a personalized TODO list web application using JSP and servlets, Interfaced MySQL database with it and Deployed it on the WildFly application server. Go to Project Page
    • Software used: Java, MySQL, ERDPlus, WildFly.
    National Capital Region, India
    June 2018 - July 2018

    Research Experience

    Indian Institute of Technology, Delhi (IIT D)

    Research Affiliate, Neurocomputing Lab
    • Advised 10 undergraduate students in scoping and planning 5 Computer Vision and Machine Learning Semester projects.
    New Delhi, India
    January 2021 - Present

    Indian Institute of Technology, Delhi (IIT D)

    Research Assistant, Neurocomputing Lab
    • Architected a human-inspired, landmark-aware ensemble Facial Expression Recognition Network that improved the current benchmark on the CK+ and JAFFE datasets by 0.51% and 5.34% and required only 3.28 MFLOPs for inference. Go to Publication
    • Invented a spatio-temporal deep learning pipeline for water stress phenotyping of Chickpea plant that achieved a ceiling level classification performance of 98.52% on JG-62 and 97.78% on Pusa-372 chickpea plant shoot image dataset and outperformed the best reported time-invariant technique by at least 14%, being robust to noisy input, with a less than 2.5% dip in average model accuracy and a small standard deviation. Go to Publication
    • Designed and carried out neural network simulations for multiple lab projects on physiological signal processing.
    • Software used: Keras, TensorFlow, PyTorch, MATLAB, OpenCV, Google Colab, Overleaf
    New Delhi, India
    July 2020 - January 2021

    Netaji Subhas Insititute of Technology, University of Delhi

    Undergraduate Researcher, Department of Computer Science & Engineering
    New Delhi, India
    August 2018 - July 2020

    Teaching Experience

    University of California, Los Angeles (UCLA)

    Teaching Assistant - PIC 10A Introduction to Programming, Mathematics Department
    • Conducting weekly hands-on training & discussion sessions on programming foundations using C++ for 30 undergraduate students.
    Los Angeles, CA
    September 2022 - Present

    University of California, Los Angeles (UCLA)

    AI Studio Tutor - Break Through Tech AI, Computer Science Department
    • Delivering workshops on data analysis, modeling, and evaluation for 26 students belonging to underrepresented groups in tech.
    • Leading brainstorming sessions, monitoring team progress, and helping teams complete their respective ML challenges.
    Los Angeles, CA
    September 2022 - Present


    Empirical analysis of pruning strategies in Federated Learning

    Large Scale Machine Learning Course Project
    • Investigated the effect of pruning on model generalization and accuracy vs. efficiency tradeoff in federated setup.
    • Proposed protocol applied to the Iterative Magnitude Pruning method achieved an improvement of 6% on FMNIST and 8% on MNIST for a 99% prune ratio when compared with one iteration of standard federated training.
    • Software used: Python, PyTorch, Google Colab, Latex, Overleaf
    Los Angeles, CA, United States
    October 2022 - December 2022

    Spotify music recommendation using Reinforcement Learning

    Reinforcement Learning Course Project
    • Simulated Spotify music recommendations, precisely predicting skips in Spotify streaming data as a Reinforcement Learning Problem.
    • Employed Deep Deterministic Policy Gradient framework and Offline Reinforcement learning techniques to recommend a diverse list of songs that reduced the average skip rate by 12% from the baseline. Go to Project Page
    • Software used: Python, TensorFlow, Google Colab, Git
    Los Angeles, CA, United States
    October 2022 - December 2022

    Face Synthesis using Descriptions Extracted from Unstructured Text

    Undergraduate Head Researcher - Bachelor’s Thesis
    • Invented a novel pipeline to generate faces from their corresponding textual description. The motivation was to augment the reading experience for young children, especially those with reading difficulty, by animating characters through facial cues. Go to Publication
    • Developed a crowdsourcing platform and consolidated our Multi-Attributed and Structured Text-to-face (MAST) dataset consisting of structured textual descriptions for face images. Go to Project Page
    • Performed text classification to filter out descriptive sentences from a textual data consolidation of Gutenberg and Face2Text datasets using Bi-LSTM with attention mechanism and achieved 98.5% accuracy and 0.97 F1 score on the test set
    • Devised an algorithm for fast transformation of an unstructured facial description to a structured one; it has linear complexity with respect to the number of words in the sentence
    • Trained an Attentional Generative Adversarial Network to synthesize faces from structured descriptions and reported benchmark scores of 54.09 Freechet' s Inception Distance, 1.080 Facial Semantic Distance, and 60.42% Facial Semantic Similarity on our MAST dataset
    • Software used: Keras, TensorFlow, PyTorch, OpenCV, Google Colab, Microsoft Cognitive Service, Angular Framework, MongoDB, NodeJS, Heroku, Overleaf
    August 2019 - July 2020

    Project ViSTARa - India Winner UN Reboot the Earth Hackathon

    United Nations Technology Innovation Labs, India
    • Designed a web-based Learning Management platform to Educate rural women through India's Self-Help Group network and Empower them to lead green climate initiatives. Coverage
    • Devised a recommender system to suggest crops that require minimum supplementary irrigation based on rainfall patterns and Employed predictive analytics to detect deforestation at the district level in India
    August 2019

    GRiD Flipkart Machine learning challenge for Large Scale Object Localization

    Flipkart, Bangalore
    • Architected a ResNet-34 inspired model to perform object localization on Flipkart’s large and diverse items dataset.
    • Trained the model on images of size 128x96 (downscaled from VGA to a 1MP camera resolution)
    • Achieved an IoU score of 90.05% on the private test set.
    • Software used: Keras, TensorFlow, OpenCV, Google Colab.
    January 2019 - March 2019

    Skillset recommendation system to aid engineering aspirants in securing an Internship

    Undergraduate researcher - Soft Computing Semester Project
    • Proposed a skill set recommender system to aid engineering aspirants in securing an Internship. Go to Project Page
    • Consolidated a small dataset of various skills an aspiring intern may have and categorized them as generic, company-specific, and domain-specific.
    • Modeled the skill selection problem as a combinatorial optimization problem with multiple objectives and employed a Genetic algorithm (GA) to solve it.
    • Established a Fitness Function to evaluate the fitness of each individual in the chromosome population.
    • Formulated an Objective Function to combine opposing goals of finding the best skillset while minimizing the time to achieve it.
    • Implemented a modular GA pipeline in C++ to evaluate and select the optimum set from the possible combinations of GA operations: population initialization, parent selection, crossover, mutation, survivor selection, and termination.
    • Software used: C++.
    August 2018 - December 2018

    Game Playing Agents - Tic Tac Toe AI

    Undergraduate researcher - Course Project
    • Simulated adversarial games between AI agents on a 3x3 and a 4x4 Tic Tac Toe board. Go to Project Page
    • Observed 1-move lookahead provided the best tradeoff between win-draw-loss ratio and time to decide the optimum move, irrespective of boardsize.
    • Software used: Python.
    October 2018 - November 2018

    Book My Flight - Database Management Semester Project

    Department of Computer Engineering, Netaji Subhas Insititute of Technology, an affiliate of Delhi University
    • Implemented a Flight Booking Management system for domestic flights in India.
    • Modeled a MySQL database system with a complex database trigger and recovery mechanism.
    • Designed Java-based user interface. Go to Project Page
    • Software used: Java, MySQL, ERDPlus.
    August 2017 - December 2017


    * Co-First Authors

    † Corresponding Author

    Awards & Honors


    Byte-size Information to Chew on

    Paper Synopsis Blog Series

    • Synopsis: Multi-Attributed and Structured Text-to-Face Synthesis

      Go to Medium Article

    • Synopsis: Intelligent Monitoring of Stress Induced by Water Deficiency in Plants Using Deep Learning

      Go to Medium Article

    • VQ-GAN & Transformer — Taming Transformers for High-Resolution Image Synthesis: Synopsis

      Go to Medium Article

    Project Blogs


    Programming Languages
    Research Tools and Frameworks
    Development Tools and Frameworks
    Cloud Platforms


    • Dissectologist Assembling jigsaw puzzles is a stress buster!
    • Travelling, Music and Food enthusiast
    • Capturing the world through my
    • Learning how to play the Piano

    Contact Me