Anoop Mishra

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

OPEN TO WORK- I am currently interested in the industrial job market! Please feel free to contact me for any potential opportunities.

I'm a Ph.D. candidate(ABD) and Responsible AI scientist passionate about building ethical and impactful AI solutions. Driven by AI's potential to create positive societal change, I'm spearheading research on the fairness of AI/ML systems under the supervision of Dr. Deepak Khazanchi.

My research focuses on fairness in the machine learning process, particularly how it's understood and experienced by both practitioners and users. I've developed a multidimensional framework that captures core attributes of perceived fairness throughout the ML lifecycle, helping teams conceptualize and measure fairness more effectively. Using a combination of participatory design research and statistical modeling, I collaborate with ML practitioners, domain experts, and end-users to investigate how fairness is perceived, interpreted, and applied in practice. This has led to the creation of validated survey tools, practical resources, and comparative studies that bridge the gap between technical development and human experience. My work is highly relevant to current trends in machine learning, including generative AI, offering timely insights into fairness, transparency, and accountability in rapidly evolving AI systems. A critical aspect of my work involves developing AI/ML systems that generate tangible outcomes reducing biased decision-making, saving costs, promoting ethical practices, and addressing real-world business challenges.

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

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)

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