Mansur Ahmad

About

Eric Schiffman, DDS, MS, is a Professor and the Director of Clinical Research in the School of Dentistry at the University of Minnesota. He has received over $19 million in research funding from the National Institutes of Health (NIH) and has authored over 60 peer-reviewed publications, 12 book chapters, and holds 3 patents with another pending. His past research as an NIH study principal investigator includes developing and publishing validated Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for the most common TMD, applicable in both clinical and research settings. He has also conducted research on TMD management, assessing the long-term effectiveness of medical management versus comprehensive rehabilitation with and without TMJ surgery in patients with symptomatic TMJ closed lock and limited mouth opening. Additionally, his work includes studying the longitudinal impact of intra-articular TMJ disorders on jaw pain, function, and disability. Schiffman has contributed to the NIH-funded National Dental Practice-Based Research Network by evaluating how dentists manage TMD patients in their practices. His recent projects include developing and clinically testing the Restful Jaw device, a device attached to dental chairs designed to support the jaw during various dental procedures, including third molar surgeries.

Research topics

• Computer Science
• Artificial Intelligence
• Political Science
• Machine Learning
• Computer Security
• Commerce
• Knowledge management
• Cognitive science
• Data science
• Mathematics

Selected publications

• Trust Amongst Rogues? A Hypergraph Approach for Comparing Clandestine Trust Networks in MMOGs

  Proceedings of the International AAAI Conference on Web and Social Media · 2021 · 22 citations

  1st authorCorresponding

  Gold farming and real money trade refer to a set of illicit practices in massively multiplayer online games (MMOGs) whereby players accumulate virtual resources to sell for “real world” money. Prior work has examined trade relationships formed by gold farmers but not the trust relationships which exist between members of these organizations. We adopt a hypergraph approach to model the multi-modal relationships of gold farmers granting other players permission to use and modify objects they own.…

  PublisherOA PDFDOI

• Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI

  arXiv (Cornell University) · 2023-09-26 · 17 citations

  preprintOpen access1st authorCorresponding

  Large language models have proliferated across multiple domains in as short period of time. There is however hesitation in the medical and healthcare domain towards their adoption because of issues like factuality, coherence, and hallucinations. Give the high stakes nature of healthcare, many researchers have even cautioned against its usage until these issues are resolved. The key to the implementation and deployment of LLMs in healthcare is to make these models trustworthy, transparent (as muc…

  PublisherOA PDFDOI

• Islamic Chatbots in the Age of Large Language Models

  ArXiv.org · 2025-12-31

  articleOpen access1st authorCorresponding

  Large Language Models (LLMs) are rapidly transforming how communities access, interpret, and circulate knowledge, and religious communities are no exception. Chatbots powered by LLMs are beginning to reshape authority, pedagogy, and everyday religious practice in Muslim communities. We analyze the landscape of LLM powered Islamic chatbots and how they are transforming Islamic religious practices e.g., democratizing access to religious knowledge but also running the risk of erosion of authority.…

  PublisherOA PDF

• A Surgeon's Guide to Machine Learning.

  UNC Libraries · 2025-06-21

  articleOpen accessSenior author

  Machine learning (ML) represents a collection of advanced data modeling techniques beyond the traditional statistical models and tests with which most clinicians are familiar. While a subset of artificial intelligence, ML is far from the science fiction impression frequently associated with AI. At its most basic, ML is about pattern finding, sometimes with complex algorithms. The advanced mathematical modeling of ML is seeing expanding use throughout healthcare and increasingly in the day-to-day…

  PublisherDOI

• Provable Distributional Value Iteration under Partial Observability

  ArXiv.org · 2025-05-10

  preprintOpen accessSenior author

  In many real-world planning tasks, agents must tackle uncertainty about the environment's state and variability in the outcomes induced by stochastic dynamics and rewards. Motivated by recent progress in world model approaches, where latent models approximate beliefs and support planning, we extend Distributional Reinforcement Learning (DistRL), which models the entire return distribution for fully observable domains, to Partially Observable Markov Decision Processes (POMDPs). Concretely, we int…

  PublisherOA PDFDOI

Frequent coauthors

• Jaideep Srivastava

  26 shared

• Carly Eckert

  24 shared

• Ankur Teredesai

  22 shared

• Noshir Contractor

  11 shared

• Brian Keegan

  University of Colorado Boulder

  10 shared

• Dmitri Williams

  University of Exeter

  9 shared

• Marshall Scott Poole

  7 shared

• Zoheb Borbora

  University of Minnesota System

  6 shared

Education

• PhD, Computer Science

  University of Minnesota

• Bachelors of Science, Computer Science

  Rochester Institute of Technology

  2006

Awards & honors

• The National Dental PBRN (2014 - 2019)
• Proximal caries and bone loss detection accuracy using i (20…
• NIH NIDCR NATL INST OF DENTAL (2011 - 2015)

Similar researchers at University of Minnesota

• David Bereiterh-56
• Kristin Artingerh-35
• Massimo Costalongah-19