# Nishank Singhal

> AI Software Engineer

Location: New York, New York, United States
Profile: https://flows.cv/nishank

Hello, I am Nishank Singhal, a data scientist and software engineer currently working full-time at Virtual Dental Care (VDC). My role involves developing innovative healthcare solutions such as SmartScan for early dental problem detection, AI-powered teeth shade generation, and a chatbot for dental-related queries. These projects showcase my ability to create AI-driven solutions that bridge technology and healthcare.

I hold a Master's in Data Science from Pace University (GPA 3.87, May 2023) and a Master of Science in Advanced Computing from the University of Bristol. Additionally, I graduated with honors in Computer Science from BITS Dubai, equipping me with a strong computing and data science foundation.

Previously, I contributed as a Data Analyst and Research Assistant at the Robotics Lab, developing systems for audio classification and motion planning. At ByteLearn, I achieved 95% accuracy using transfer learning in a multi-class classification model. My work at the Indian Institute of Science focused on optimizing computer vision algorithms, reducing training times by 50%.

Technical Expertise
Languages: Python, Java, C++, SQL
Frameworks: TensorFlow, PyTorch, Scikit-learn
Platforms: AWS, MATLAB, Git
Achievements
Best Poster Award: Motion Planning for Robotic Arms (MID-2022)
Hackathon Winner: 1st Prize, Dataiku Hackathon (Pace University)
Contact Information:
📧 Email: nishank20singhal@gmail.com

I am passionate about leveraging technology to deliver impactful solutions and make a difference in the tech and healthcare industries.

## Work Experience
### AI Software Engineer @ Virtual Dental Care, Inc.
Jan 2023 – Present | California, United States

### Data Scientist @ Pace University - Seidenberg School of Computer Science and Information Systems
Jan 2022 – Jan 2023 | New York, NY 10038
Audio Classification System
•	Created a speech clutter disorder classification system for 3,000 records using acoustic feature vectors obtained from audio-
associated visibility graphs.
•	Conducted digital signal processing and trained a deep neural network (DNN) model with K-fold validation using Python, Librosa, TensorFlow, Torch, and Keras, achieving 85% accuracy on test records.
Q-learning for dynamic environment
•	Developed and implemented a Q-Learning algorithm to solve reinforcement learning problems in the Open AI Gym environment.
•	Trained an agent over 100,000 episodes using an epsilon-greedy policy and updated the Q-table using the Bellman equation.
•	Created a Python script using data analytics to rank Tennis ATP players depending on player stats. The client rated the script "extremely useful."
•	Created a machine learning algorithm to forecast supply needs in a busy restaurant based on past receipts reducing inventory. 
costs by 25%.
Jackal Robot: Converting Reality to Virtuality through Surrounding Rendering and Object Detection (Capstone Project)
•	Designed and developed a system using Jackal Robot for object detection and surrounding rendering to accurately reflect the 
real-world environment into a virtual world with 85% match in Unity with Python.[link]
•	Setting up the 3-way cross-platform interaction between Jackal (ROS) to Python and Python along with the PIFUHD model.
Technology used: Python, Librosa, TensorFlow, Torch, Keras, Open AI Gym, Machine learning algorithm, Jackal Robot, Velodyne VLP-16 Lidar Sensor Puck, Zed Camera, Unity, ROS, PIFUHD model

### Data Analyst @ ByteLearn.com
Jan 2021 – Jan 2021 | Delhi, India
•	Performed multi-class classification using transfer learning technique on efficient net PyTorch model. 
•	Designed an architecture pattern of python framework which can be used as plug and play for different data analyst engineer.
•	Designed, implemented, and deployed the complete workflow of geometric shape generation along with the mentorship of two interns

### Machine Learning Engineer @ Analytics India Magazine
Jan 2018 – Jan 2019 | Bengaluru, Karnataka, India
•	Worked with a team to develop an algorithm to count and IDENTIFY number of people in the hall using a camera.
•	Worked on optimization of YOLOv3, Zero-Short-Learning, and GANs algorithms and reduced their training time by 50%.
•	Created Python scripts to perform ETL processes using Glue, Lambda, and Sage Maker.
•	Built Excel and Tableau dashboards, tools, and ad-hoc reports to improve reporting, analytics, and visualization needs while 
working collaboratively and delivering projects on time in an Agile team environment.
Technology used: Python, Image Processing, YOLOv3, Zero-Short-Learning, GANs, Excel and Tableau Dashboards, Agile Methodology


## Education
### Master of Science - MS in Data Science
Pace University
Jan 2022 – Jan 2023

### Master of Science - MS in Advance Computing: Machine Learning
University of Bristol
Jan 2019 – Jan 2021

### Bachelor of Engineering - BE in (Hons.) in Computer Science
Birla Institute of Technology and Science, Pilani
Jan 2014 – Jan 2018


## Contact & Social
- LinkedIn: https://linkedin.com/in/nishank-singhal

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Source: https://flows.cv/nishank
JSON Resume: https://flows.cv/nishank/resume.json
Last updated: 2026-04-01