Resume

Education

• Master’s in Artificial Intelligence, University at Buffalo, SUNY (class of 2022)
• Fellowship (Machine Learning), Indian Institute of Technology, Delhi, India. (2018)
• Bachelor’s in Computer Science, JIIT, Noida, India. (Class of 2015).  

Work experience

• Summer 2021: Intel Corporation
  • Software Engineer (Machine Learning) Intern
    • QIRI Chatbot
    • Targetted testcases execution
• Fall 2021: University at Buffalo
  • Research Assistant
    • Implemented federated learning using convolution neural network in a cross-silo setting in a peer to peer architecture with Java PeerSim distributed network of nodes.
• May 2016 - July 2021: Cadence Design System
  • Reduced the time to reach the target code coverage by 40% by learning the optimal input conditions of the randomization engine which are required to achieve the target code coverage using the non-linear regression technique.
    • Code coverage is the first and crucial step in the validation cycle. The engineers previously wrote the input conditions manually, which was a tedious and time-consuming task and took days to achieve the coverage goal.
    • Deployed the model at the customer end which made randomized coverage regression faster by reducing the customer’s coverage run from 17000 runs to 5000 runs to hit the target coverage.
  • Virtual Bridge Project:
    • Created view panels in system debugger using Java Swing framework which displays the protocol transaction packets information across the bridge, State transition information, and transaction statistics for performance analysis
    • Created an automated framework to fetch user application information and displayed it in debugger GUI Using GDB and Python
    • This helped 20+ existing customers to debug both hardware and software issues in-house and enabled the 100+ hardware and software engineers to debug the issue together.
  • IXCOM Compiler
    • Worked on supporting new language constructs of System Verilog HDL language both syntactically and semantically using LEX and YACC tools
    • Increased the performance of macro handling code by 20% and developed applications to support new macro syntax.

Skills

Programming Languages : Python, C++, C, Java, Verilog.
Libraries/Framework   : Pandas, Numpy, SciPy, Sk-learn, Keras, Spacy, Pytorch, Tensorflow, Jupyter notebooks, Pycharm.
Cloud Computing       : GCP: Docker, Kubernetes, DataFlow, BigQuery, VertexAI.
Version Control       : Git, Perforce, Clearcase.
Data Visualization    : Seaborn, Matplotlib, Plotly.
Database              : SQL, MongoDB, Cassandra.
EDA Tools             : IXCOM, Xcelium, Virtual Bridge, Palladium
Virtualization Tools  : QEMU

Publications

Intelligent Jobs Scheduling in palladium Cloud using Machine learning

A Comparative assessment of Data Mining Algorithms to predict fraudulent firms

H. Monish and A. C. Pandey, "A Comparative Assessment of Data Mining Algorithms to Predict Fraudulent Firms," 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2020, pp. 117-122, doi: 10.1109/Confluence47617.2020.9057968.

Projects

Action Spotting in Soccer broadcast Untrimmed videos

Deep Learning models Compression Techniques - Pruning, Knowledge Distillation

Dependency Parsing in Natural Language Processing

Variational Autoencoder and Generative Adversarial Network

Achievements

• Google Developer Student Club Lead at University at Buffalo
• Completed the NVIDIA Deep Learning Institute Course-Fundamentals of Deep Learning.
• Pitched the startup idea of smart AI trainer in UB Blackstone Launchpad startup-event and got in top 10 ideas out of 40.
• Won Cadence Global Hackathon 2019 held in Cadence San Jose, California Campus.
• Sports Society Head and Basketball Team Captain of Jaypee Institute of Information Technology