Résumé

Career Objective

I am a MS Computer Science graduate student from the USC with a demonstrated history of working and conducting research in the field of AI, ML, Deep Learning, Data Science, and Software Development for 3 years. I graduated with my B.Tech. (Computer Science & Engineering) from GGSIPU, New Delhi, India.

For more, check out my Github: https://github.com/AnshMittal1811, Scholar: https://scholar.google.com/citations?user=rG4ZgtMAAAAJ&hl=en, and Medium: https://medium.com/@anshm18111996.

January 2023 - May 2023

AI/ML RESEARCH ENGINEER

(INTERN AT KNOW SYSTEMS CORP, INC)

Developed a personalized GenerativeQA using Prompt Engineering with GPT-J and GPT-NeoX; METEOR: 22.34 (2%↑); STS: 0.87 (3.5%↑) and integrated Unit Tests for the GitHub Repo (FastAPI for APIs)
Compared different model-based approaches using metrics (BLEU, ROUGE, METEOR, STS) for loss functions (CE, Triplet)
Prepared a PoC for 3D Human-based Avatar (Using NeurMan and Neural Head Avatars) and Voice-enabled Conversation (using text-to-Speech) for Generated Prompts and integrated with FastAPI

Skills: C++ · Neural Radiance Fields · Machine Learning · Python · Convolutional Neural Networks (CNN) · PyTorch · TensorFlow · Natural Language Processing (NLP) · Computer Vision · Keras · OpenCV · Transformer

August 2021-May 2023

MASTER OF SCIENCE IN COMPUTER SCIENCE

Grade Point: 3.8

COURSES TAKEN:
- CSCI 561 (Foundation of Artificial Intelligence)
- CSCI 570 (Analysis of Algorithms)
- CSCI 566 (Deep Learning and its Applications)
- CSCI 544 (Applied Natural Language Processing)
- CSCI 513 (Autonomous Cyber Physical Systems)
- CSCI 677 (Advanced Computer Vision)
- CSCI 571 (Information Retrieval and Web Search Engines)
  GRADED - CSCI544 (Applied Natural Language Processing)

Skills: Neural Radiance Fields · Python · PyTorch · Natural Language Processing (NLP) · Computer Vision

August 2022 - December 2022

STUDENT RESEARCH WORKER

(AT USC INTEGRATED MEDIA SYSTEMS CENTER LAB)

Classified Street Cleanliness using pre-trained models (MobileNet, EfficientNet, ResNet, etc.); Accuracy: 0.71 (5.72%↑)
Demonstrated I-SPLIT algorithm for Split-Computing on edge-devices using CUmulative Importance (cumulative GradCAM)

Skills: Artificial Intelligence · Python · Artificial Neural Networks · Computer Vision · Computer Science

May 2022 - August 2022

MACHINE LEARNING ENGINEER INTERN

(AT GUIDEWIRE SOFTWARE INC)

Augment Data Quality framework for data artifacts from Sagemaker Feature Store (using Athena), PostgreSQL, and S3
Develop Containers to automatically generate report and JSON objects (with Visualizations) with ML-automated test suite
Developed a PoC for fire hydrant detection for Hazard Hub team to analyze the places with Urgent Firefighter/FireHydrant support using super-resolved Geospatial rasters
Presented a short survey of Neural Radiance Fields and their use-case in different teams across Guidewire

Skills: Continuous Integration and Continuous Delivery (CI/CD) · Docker · Neural Radiance Fields · Python · AWS · Agile · GIS

February 2022 - July 2022

GRADUATE RESEARCH ASSISTANT

(AT USC INFORMATION SCIENCES INSTITUTE)

Engineered a baseline for regressing 3DMM features without explicit Face Landmark detection deploying 62-D Regression.
Implemented Img2pose, 3D Dense Face Alignment, 3D Dense Face Alignment V2, Position-map Regression Network, Volumetric Regression Network, models and evaluated based on Normalized Mean Error on Weights&Biases

Skills: C++ · Generative Adversarial Networks (GANs) · Python · Deep Learning · Computer Vision · Physics · C · MATLAB

April 2022 - June 2022

STUDENT RESEARCH ASSISTANT

(AT USC MARSHALL SCHOOL OF BUSINESS)

Worked on Topic Modelling for research in Quantum Computing using Latent Dirichlet Allocation, Latent Semantic Analysis, Hierarchical Dirichlet process, and BERTopic (Sci-BERT and OAG-BERT embeddings)
Worked on using 3rd Party data along with Researchers data using Expectation Maximization (EM) algorithm to cluster researchers on the basis of political opinion and encourage cross-political thinking research
Planned Fastlink-based EM-algorithm on L2 and Researcher data to cluster researchers based on area and ORCID API

Skills: Python · LaTeX · API · Expectation Maximization (EM) · BERT · Topic Modelling

October 2020 - August 2021

DATA SCIENTIST

(AT SOCIOMETRIK)

Worked on SpaceNet 2 dataset with U-Net for image segmentation.

Multi-label classification for Amazon low-resolution imagery dataset.

Designed metal roof-detection pipeline by leveraging Indore Imagery with the performance of 64.35% & achieved an average IoU score of 0.6981;
Built a feature extraction pipeline based on CI/CD methodology and led a POC utilizing Car Overhead data with F-measure of 0.7341(3.7 % increase) and obtained building-wise IoU of 0.78464 (6.8% increase)
Facilitated a POC for multi-label classification (with 21 pre-trained models and one custom model) for the terrain around rivers (17 different labels such as rivers, forest, cloudy, etc.) (like Amazon). Average Precision: 0.8699 (20 % increase) and Average Recall: 0.7939 (12 % increase)

Skills: Generative Adversarial Networks (GANs) · Data Science · Python · Computer Vision · Neural Networks · Data Visualization · AWS

January, 2020 - October, 2020

RESEARCH ASSOCIATE

(AT INDIAN INSTITUTE OF TECHNOLOGY (IIT), DELHI)

I created a Game-based Interactive simulator for Training in Cyber Security. This game used Heuristic and Meta Heuristics along with Machine Learning to create a recursive learning experience.

Developed a Serious Game to impart Blockchain competencies (Sequence-to-Sequence-based Chatbot) - CEBT paper (Cited 27 times) using WebGL and Android
Developed NAF-based (Actor-Critic Variant) Cont. NPC Adaptiveness Algorithm to augment Game Design & Mechanics with Feedbacks
Presented a report focused on increasing user interactivity by 27% (average user feedback) by utilizing action- feedback elements and behavioral-trees
Integrated a clustering algorithm to group user feedback in a Cyber Threat game (Achieved accuracy of 76.32% (10.6% increase)

Skills: Python · Artificial Neural Networks · Computer Science · Neural Networks · Serious Game Development · PostgreSQL

June 2019 - November 2019

WEB DEVELOPMENT ENGINEER

(AT UVA INSTITUTE)

Built and deployed e-learning website with React, Redux, Spring & MySQL and added video features with FFMPEG;
Comments/reviews Information retrieved using Selenium and BS4; Sales-analysis of courses using EDA led to 15% ↑ in revenue

Skills: Data Science · Data Visualization · Amazon Web Services (AWS)

August 2015 - March 2019

BACHELOR OF TECHNOLOGY

From Bharati Vidyapeeth's College Of Engineering (affiliated to Guru Gobind Singh Indraprastha University), New Delhi

(CGPA: 8.97 / 10.0)

Activities and societies: Research Papers Written, Conferences attended, Smart India Hackathon 2018 and 2019Activities and societies: Research Papers Written, Conferences attended, Smart India Hackathon 2018 and 2019
Worked on several research papers with my professors during my undergraduate courses. These were:
- AIGOS (Artificially Intelligent Geo-Orbital Synchronization) System
- AiCNNs (Artificially-integrated Convolutional Neural Networks) for Brain Tumor Prediction
- Data Augmentation Based Morphological Classification of Galaxies Using Deep Convolutional Neural
- Detecting Pneumonia Using Convolutions and Dynamic Capsule Routing for Chest X-ray Images

Skills: Python Artificial Intelligence

June 15 2018 - July 13 2018

DATA SCIENCE INTERN

(AT DEGS (DELHI E-GOVERNANCE SOCIETY))

I developed a Machine Learning based transaction predictor and a data visualizer using MySQL and ASP.NET. I also analyzed sentiments on comments and complaints received by the department.

Collaborated with National Informatics Centre for visualization; Developed Auto-scaled platform for 478 e-services (Now: 4,038 services) (link: https://etaal.gov.in/etaal2/auth/default.aspx)
Deployed a transactions predictor and visualization tool with daily service prediction facility with 81.74% accuracy using ASP.NET
Extracted relevant data using SQL to develop an analytical and visualization interface

Skills: Data Science · Python · Computer Science · Neural Networks · Data Visualization

June 12, 2017 - July 14, 2017

SUMMER TRAINING

Grade: A (90 % - 100 %)

This was 5 weeks of summer in-house training program conducted by Bharati Vidyapeeth's College of Engineering, New Delhi. This training titled "Embedded Systems with Applications of Machine Learning in the Internet of Things"

April 2014 - March 2015

HIGHSCHOOL (12TH)

Manav Sthali School R Block, New Delhi (Central Board of Secondary Education)

(Percentage: 93.6 % (best5 subjects), 94.75 % (best4 subjects))

I took up 5 subjects in my 12 (10 + 2) class. These subjects consist of Physics (95), Chemistry (95), Mathematics (95), English (94), and Computer Science (89)

April 2012 - March 2013

HIGHSCHOOL (10TH)