Chandan Kumar

Assistant Professor
Computer Science, Alfred University

๐Ÿ“ง [email protected]
๐Ÿ“ž
๐ŸŒ Website
๐ŸŽ“ Google Scholar
๐Ÿ’ป GitHub
๐Ÿ”— LinkedIn

Education

Iowa State University, USA

  • Degree: Doctor of Philosophy (Ph.D.), Computer Science (Focus: Deep Learning, Computer Vision)
  • Advisor: Dr. Ali Jannesari and Dr. Matthew Darr
  • Graduation Year: May 2025

Iowa State University, USA

  • Degree: Master of Science, Computer Science
  • Advisor: Dr. Ali Jannesari
  • Graduation Year: Dec 2022

BIT Sindri, India

  • Degree: Bachelor of Technology in Computer Science (With Distinction)
  • Graduation Year: June 2015

Professional Experience

Assistant Professor โ€“ Alfred University

Aug 2025 โ€“ Present | Alfred, NY

  • Teaching foundational programming, algorithmic thinking, and computational problem-solving.
  • Teaching advanced AI, deep learning, and computer vision courses.
  • Mentoring undergraduate research and project-based learning.
Research Scientist โ€“ Cygeniq Inc

Jun 2025 โ€“ Aug 2025 | Remote

  • Developed a specialized language model for automated cybersecurity threat detection.
  • Reduced manual incident classification time by 75%.
  • Designed real-time ML pipelines aligned with MITRE ATT&CK framework.
Graduate Researcher โ€“ Oak Ridge National Laboratory

Sep 2024 โ€“ May 2025 | Oak Ridge, TN

  • Designed a 1B+ parameter multimodal foundation model using Vision Transformers.
  • Achieved 95% accuracy in satellite image vectorization.
  • Optimized polygonization algorithms, reducing runtime by 400%.
Visiting Researcher โ€“ Pacific Northwest National Laboratory

May 2024 โ€“ Dec 2024 | Richland, WA

  • Developed unsupervised semantic segmentation models using contrastive learning.
  • Worked in HPC environments for large-scale training.
Graduate Research Assistant- Iowa State University

Jan 2023 - Aug 2024 | Ames, IA

  • Skills Used: Python, Pytorch, CUDA, bash scripts, slurm.
  • Unsupervised Learning approach to Object-Detection. Developed fully unsupervised leaning based object detection algorithm using contrastive learning.
  • Unsupervised Image retrieval. Developed algorithm to retrieve image using unsupervised learning.
  • Scaling Unsupervised Learning algorithm to HPC(High Performance Computing).
Data Scientist Coop-Hagie Manufacturing (John Deere)

Jan 2022 โ€“ Jan 2023 | Clarion, IA

  • President award winner for extraordinary performance.
  • Skills Used: Alteryx, Ignition SCADA, Databricks, PowerBI, Microsoft Excel,AWS, RabbitMQ, Python, OpenCV, Pytorch.
  • Using tools and techniques to perform Text Mining, ML models development for predictive analysis and automation and Computer Vision models.
  • Design and develop project pipeline(Data Exploration, Sampling, Feature Engineering, Model Building, Field Performance Evaluation).
Graduate Research Assistant - Iowa State University

Jan 2017 โ€“ Dec 2022 | Ames, IA

  • Skills Used: CAN-Bus, Python, OpenCV, POE, Pytorch, ROS
  • Developed real-time driver assist system for large farm-vehicles. Involved a system of 16 cameras, edge computing and image stitching to utilize the CAN protocols and integrate the mechanism to existing system.
  • Real-time depth detection and analysis using stereo camera(s). Used stereo camera to develop algorithm that can perform real-time depth detection and calculate volume of objects from the drone.
Business Analyst - EXL(Inductis) Services India Pvt. Ltd.

Feb 2016 โ€“ Dec 2016 | Gurugram, IN

  • Awarded Rising Star Award (1 of 6 awardees out of 37,000+ employees) Skills used: SAS, SQL, IBM-Netezza, DB2,Tableau, R, Python, Microsoft Excel.
  • Utilized applications like SAS to identify trends and relationships between different pieces of data, draw appropriate conclusions and translated analytical findings.
  • Created and worked on various reporting frameworks (Microsoft Excel, Tableau) that involved customer segmentation and clustering exercises for customers

Teaching Experience

Assistant Professor โ€“ Alfred University

2025 โ€“ Present | Alfred, NY

  • CSCI 156: Introduction to Computer Science
  • CSCI 400: AI for Computer Vision
Teaching Assistant & Mentor โ€“ Iowa State University

2017 โ€“ 2024 | Ames, IA

  • COMS 1130: Spreadsheets & Databases (1,200+ students)
  • AI 2010: Introduction to Applied AI
  • COMS 1060: Introduction to Web Programming
  • COMS 402C: Computer Science Senior Project

Publications (Selected)

  • Discerning Self-supervised Learning and Weakly Supervised Learning โ€” ICLR 2024
  • Unsupervised learning based object detection using Contrastive Learning โ€” 2024
  • Efficient Volume Estimation for Dynamic Environments using Deep Learning on the Edge โ€” PAISE @ IPDPS 2022
  • Pattern Based Multivariate Regression using Deep Learning โ€” CVPR LXAI 2022

(Full list available upon request)

Technical Skills

  • Languages: Python, Java, C/C++, JavaScript, HTML/CSS
  • Frameworks: PyTorch, TensorFlow, OpenCV, HuggingFace
  • Tools: Docker, AWS, Git, CUDA, Linux
  • Libraries: NumPy, Pandas, Scikit-learn, Matplotlib

Awards & Grants

  • NSF ACCESS Grant (Co-PI): $174,090
  • NSF ACCESS Extension Grant: $8,000
  • Intel Edge AI Scholarship
  • PyTorch Scholarship Challenge

Service & Leadership

  • Program Committee: AAAI 2025
  • Reviewer: ICML, ICLR, NeurIPS, ECCV, WACV
  • President, Graduate Student Organization (raised $100K+)

Reviewer

  • Conference: ECCV 2024.
  • Conference: ICML 2024.
  • Conference: ICLR 2024.
  • Conference: NeurIPS 2023.
  • Journal: Journal of AI Research (JAIR).
  • Journal: River Publishers.

Professional Memberships

  • IEEE
  • IEEE Computer Society
  • Cohere for AI

Invited Talks

  • AI and Computer Vision for Sustainable Power Grids
    AU Energy Conference 2025, Alfred, NY
  • Volume Analysis for Dynamic Environments (2021)
    International 7-in-1 Symposium, CGC, Herning, Denmark.

Resume

  • Description: Click here to view my resume.