Gunjan Verma

Results-oriented research leader specializing in machine learning and statistical modeling. Recognized for impactful communication and collaboration across government, academia, and industry, ensuring alignment with national defense priorities and driving scientific excellence in advanced wireless communications. Accomplished R&D Portfolio Director with a proven track record in leading multi-million-dollar research initiatives. Expertise in machine learning and signal processing drives innovative solutions in wireless communications.

• Machine Learning DevOps Engineer, Udacity, 07/01/25, Present
• Generative AI, Udacity, 07/01/25, Present
• Generative AI for Software Development Specialization, DeepLearning.AI, 02/01/25, Present
• Deep Learning Specialization, DeepLearning.AI, 06/01/18, Present
• Sequence Models, DeepLearning.AI, 06/01/18, Present
• Convolutional Neural Networks, DeepLearning.AI, 05/01/18, Present

NestQuest– LLM-Powered Real Estate Recommendation System, 06/01/25, 07/01/25, A prototype machine learning–driven real estate recommendation engine that uses Large Language Models (LLMs) and vector similarity search to match homebuyers with listings that fit their lifestyle and preferences. ImageSwap – Segment Anything + Diffusion Inpainting, 05/01/25, 06/01/25, ImageSwap is an interactive image editing tool that combines Meta AI's Segment Anything Model (SAM) with Stable Diffusion XL inpainting to enable intuitive, click-to-edit image modifications based on text prompts. FinanceChatbot – LLM + RAG for Stock News Analysis, 04/01/25, 05/01/25, This project showcases a chatbot powered by Large Language Models (LLMs) enhanced with Retrieval-Augmented Generation (RAG) to analyze stock-related queries using recent news data. Parameter Efficient Fine Tuning of LLMs with Hugging Face, 03/01/25, 04/01/25, This project demonstrates how to fine-tune a large language model (DistilBERT) efficiently using the PEFT (Parameter-Efficient Fine-Tuning) approach with LoRA (Low-Rank Adaptation) via the Hugging Face peft library. Integrated SDR & Robotics Platform for Joint Wireless–Autonomy Research, 09/01/15, 09/01/19, Pioneered the first integration of software-defined radios (SDRs) with ARL’s fleet of ground robots.

• Civilian Service Commendation Medal, 09/01/25, One of the most prestigious awards granted by the Government, awarded for exceptional leadership, research, and development efforts that were instrumental in contributing to the success of several high-impact research and development initiatives.
• ARL Award for Outstanding Research and Development, 08/01/24, Recognized by an independent panel of academic and industry experts for excellence in R&D for my work on using machine learning to forecast the performance of communications networks under various loads.
• First Place, ARL Computational Sciences Division R&D Competition, 2024, Received top honors for effectively presenting my R&D of compression in neural networks to a non-technical panel of Army stakeholders.
• Invited Panel Participant on the Future of Homeland Defense, 10/01/23, I was an invited participant in Future of Homeland Defense Workshop with Army Cyber Command, Artificial Intelligence Center, and Department of Energy, served as a machine learning subject matter expert.
• ARL Recognition for Youth STEM Engagement, 06/01/23, Highlighted in an official press release for outreach efforts involving AI/ML education and mentorship of grade 6–8 students.
• Finalist, Nominated for Army Research Office's “Year in Review - Successful Outcomes” Report, 12/01/22, Recognized for my collaborative R&D with Rice University on graph neural networks and their applications to networking and resource optimization.
• ARL award for excellence in research leadership, 10/01/20, Granted for demonstrating excellence in leading a 10 year, multi-university, multi-million dollar research program focused on ML and distributed sensors.
• ARL award for DARPA support, 10/01/19, ARL Award for excellence in providing rigorous evaluation of DARPA funded science and technology.
• Finalist for ARL award for seminal research, 09/01/19, I was selected as a finalist from over 50 projects for my work on machine learning in adversarial contexts.
• ARL award for excellence in research leadership, 07/01/19, Granted for demonstrating excellence in leading a 10 year, multi-university, multi-million dollar research program focused on ML and distributed sensors.
• Honorable mention for R&D, 08/01/16, Led the development of a novel statistical methodology for inferring the communications channel in non-line-of-sight optical communication systems.
• Army Certificate of Achievement, 2016, I was involved in several student outreach efforts, including giving talks to student interns at ARL, evaluating poster presentations, and participating as a judge in local science fairs.
• Medallion of Excellence from the US Army Network Technology Command, 03/01/12, Awarded for conducting outstanding research and development supporting sensor networking in challenging Army environments.
• Official Commendation, 10/01/10, In recognition of outstanding contributions to the development and field testing of a software solution enabling seamless connectivity across a large-scale sensor network.
• Official Commendation, 03/01/09, Official commendation for a demonstration of my work on sensor/robot communications at the United States Military Academy.

• Gardening