Anoop Mishra

OFFICE: PKI 383, 1110 S 67th St, Omaha, NE -68182

📧 amishra@unomaha.edu amishraai@outlook.com

This website needs serious update. Currently, I am working on important stuffs. Maybe check back soon or email me!

I'm an Applied AI and a Responsible AI scientist passionate about building ethical, human-centered AI solutions that create real-world impact. Driven by AI's potential to create positive societal change, I'm spearheading research on the fairness of AI/ML systems. I recently completed my PhD under the supervision of Dr. Deepak Khazanchi.

I’m passionate about fairness, accountability, and transparency in AI systems. My recent research focuses on fairness evaluation in the machine learning development process, including the sociotechnical context and how it's understood and experienced by both practitioners and users. My expertise spans building and deploying AI models, conducting socio-technical assessments, and advancing fairness theory and measurement development. I actively contribute to open-source communities to create reproducible tools and community-driven standards, integrating interdisciplinary insights from cognitive psychology, ethics, and social sciences to strengthen societal trust in AI.

Connect with me if you're interested in:

1) Collaborating on responsible AI projects

2) Discussing the future of ethical and impactful AI

...or simply want to learn more about my research!

Some of my research interests are-

Responsible AI, including Fairness, perception in ML*
Generative AI (LLMs- development and evaluation)*
Edge-AI, Hardware-Accelerated Machine Learning*
Deep learning methods in Computer vision (like attention networks, weakly supervised learning, transfer learning, and reinforcement learning);*
Game theory
Socially Assistive Robotics (using modular self-reconfigurable robots & soft robotics), Human-robot interaction

(*: shows actively working)

You can contact me by filling out the 'Contact information' form below or emailing me.

Google Scholar

Recent News

Aug, 2025, Defended my PhD dissertation🎉 under the supervision of Dr. Deepak Khazanchi, Dr. Michael Cortese, Dr. Harvey Siy, and Dr. Chun Hua Tsai. My Dissertation title was "Measuring Perceived Fairness of the ML development Process: An empirical investigation". I will share my dissertation doc as soon as it is published in the Proquest thesis repo!
Jan, 2025, I am teaching HNR 3040-099 AI and Business at University Of Nebraska at Omaha along with Dr. Deepak Khazanchi. This class covers fundamental AI concepts, its limitations, and implementation challenges in business. It evaluates case studies for innovation potential, offers advice on feasibility, examines ethical issues, and communicates AI's social and economic impacts.
Jan, 2025, I am visiting ATDC Indian Institute of Technology, Kharagpur, in January 2025 as visiting researcher for cybersecurity research and exploring the exciting intersection of Machine Learning and Edge AI to address critical security challenges.
Sep, 2024, My dissertation research topic has been selected for the AIS ICIS 2024 Doctoral Consortium. Title-Measuring Perceived Fairness in Machine Learning (ML) Process. I am the first doctoral student/candidate from my school to be selected for this prestigious AIS conference.
July, 2024, I completed my internship at Buildertrend. During my internship, I served as a Machine Learning intern. My responsibilities encompassed working on generative AI development, specifically the first genAI product of the company, i.e., an LLM for internal business use. I took the lead in crafting a comprehensive LLM development guide for designing, developing, and evaluating an LLM product. Additionally, I formulated a custom chat evaluation framework and engineered ML models to forecast customer churn while conducting customer behavior analysis.
May, 2024, My dissertation research topic has been selected for the ACM FAccT 2024 Doctoral Consortium. Title-Perceived Fairness in Machine Learning (ML) Process: A Conceptual Framework
April, 2024, SURVEY ALERT: Calling All Machine Learning (ML) professionals for ML fairness survey! CLICK HERE to Know more.
February, 2024, My work integrating edge-AI in the structural health monitoring domain with the title- "An Investigation into the Advancements of Edge-AI Capabilities for Structural Health Monitoring" is accepted in IEEE Access Journal (Five-year Impact factor: 4.1)
January, 2024, I will be working as TA for HONR3030-099: Honors Colloquium Digital Human Rights in the Age of AI at IS&T, UN Omaha, for the Spring 2024 session.
January, 2024, My work utilizing weakly supervised learning in the structural health monitoring domain with the title- "Weakly Supervised Crack Segmentation Using Crack Attention Network (CrANET) On Concrete Structures" is accepted in the journal Sage Structural Health Monitoring (Five-year Impact factor: 7.0)

Some interesting videos:

**All these videos are posted just for educational purposes. This website holds NO ownership of the contents posted in this section "some interesting videos". These are youtube videos, the references are given in the youtube video description.**