About

Ali Abbas is associated with the field of Ethical Decision Quality (EDQ). He is involved in offering a wide range of business and management consulting services, including strategic planning, conducting audits on Ethical Decision Quality, and coaching organizations on building an ethical decision culture. His work emphasizes assessing the ethical quality of decisions and developing organizational practices to foster an ethical decision-making environment. Abbas has hosted webinars on EDQ in collaboration with professional societies such as the Society of Decision Professionals and the Decision Analysis Society of INFORMS, indicating his active engagement in promoting and educating about ethical decision processes.

Research topics

• Computer Science
• Artificial Intelligence
• Political Science
• Engineering
• Mathematics
• Human–computer interaction
• Operations research
• Data science
• Telecommunications
• Statistics
• Mechanical engineering
• Management science
• Simulation

Selected publications

• A Trend Analysis of Rank Reversal in Widely Used Decision‐Making Methods

  Journal of Multi-Criteria Decision Analysis · 2026-01-20 · 1 citations

  articleSenior authorCorresponding

  ABSTRACT Rank reversal is a phenomenon that can occur with various proposed decision‐making methods when the rank order of alternatives changes by the inclusion or removal of an uninformative alternative. This survey provides a trend analysis of five widely used decision‐making methods that are subject to rank reversal: (i) the Analytic Hierarchy Process (AHP), (ii) the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), (iii) the Preference Ranking Organisation METHod for Enrichment Evaluations (PROMETHEE), (iv) the ÉLimination Et Choix Traduisant la REalité (ELECTRE), which means Elimination and Choice Translating Reality and (v) the VIse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), which means: Multicriteria Optimization and Compromise Solution in Serbian. The trend analysis also segments the literature based on three categories: (i) literature that proposes a modified procedure of a decision‐making method to correct for rank reversal; (ii) literature that identifies the root cause of rank reversal within a method and (iii) literature that evaluates a proposed method based on its potential for rank reversal. The first observation of this paper is that despite the importance of choosing a method for decision‐making that avoids rank reversal, and despite several publications on the effects of this issue, applications using methods prone to rank reversal continue to be widely used. Further, by tracing historical publication trends across the three categories, this paper shows how rank reversal research has developed over time, with research on correcting rank reversal (Category 1) remaining steady and dominant, while root‐cause analysis of rank reversal within a method (Category 2) and evaluative work (Category 3) are growing. The survey ends by highlighting other methods that are prone to rank reversal but have not had sufficient literature drawing attention to their susceptibility to this issue. Examples include the Min–Max Regret method and the Characteristic Objects Method (COMET) of decision‐making. We hope that this work draws further attention and sensitivity to the implications of rank reversal in newly proposed and existing decision‐making applications and that it would enable a discussion that would be beneficial to various researchers and practitioners in the broader field of decision‐making.

  PublisherDOI

• Molecular Analysis of Mixed-Type and Branch-Duct Intraductal Papillary Mucinous Neoplasms

  JAMA Surgery · 2025-12-23

  articleOpen access

  Importance: Studying the molecular profiles of mixed-type and branch-duct (BD) intraductal papillary mucinous neoplasms (IPMNs) is important to understand the underlying biological basis for higher malignant potential of mixed-type IPMNs. Objective: To compare mutation patterns in mixed-type vs BD-IPMNs through cyst fluid next-generation sequencing (NGS) analysis using PancreaSeq NGS. Design, Setting, and Participants: For this cohort study, pancreatic cyst fluid specimens from 31 medical centers were sent to a centralized NGS lab for analysis between January 2018 and February 2020. Patients with IPMNs (based on KRAS and GNAS mutant status) and with available main pancreatic duct (MPD) size data were included. Patients with main-duct IPMNs and with MPD 10 mm or greater were excluded. Mixed-type IPMNs were defined as IPMNs with an MPD of 5 to 9 mm, and BD-IPMNs were defined as IPMNs with an MPD less than 5 mm. High-risk mutations (HRMs) were categorized as alterations in TP53, SMAD4, CTNNB1, and mTOR genes. Advanced neoplasia was defined as IPMNs with invasive carcinoma or high-grade dysplasia. Data were analyzed from June 1 to 5, 2025. Main Outcomes and Measures: Primary outcomes included rates of HRMs and the co-occurrence of 2 or more HRMs in mixed-type IPMNs and BD-IPMNs. Results: Among 674 patients with IPMNs, 202 had mixed-type IPMN, and 472 had BD-IPMN. There were 379 female patients (56.2%) and 295 male patients (43.8%); the mean (SD) age was 70.3 (9.6) years. HRMs were observed in 106 patients (16%), with TP53, SMAD4, and MTOR mutations more common in mixed-type IPMNs. Of the 674 patients, 167 patients underwent surgical resection, and these 167 patients had final surgical pathology available. Overall, mixed-type IPMNs had significantly higher rates of HRMs (62 [31%] vs 44 [9.3%]; P < .001) and co-occurrence of 2 or more HRMs (25 [12.4%] vs 14 [3%]; P < .001) compared with BD-IPMNs. On multivariate logistic regression, mixed-type IPMNs were independently associated with HRMs (odds ratio, 3.42; 95% CI, 1.72-6.82). Preoperative NGS detection of HRMs showed 90% sensitivity, 100% specificity, a positive predictive value (PPV) of 100%, and a negative predictive value (NPV) of 86% for predicting advanced neoplasia in mixed-type IPMNs. The presence of any worrisome feature or high-risk stigmata showed a sensitivity of 100%, very low specificity of 13.3%, PPV of 67%, and NPV of 100%. Conclusions and Relevance: This study found that mixed-type IPMNs are more likely to harbor HRMs associated with advanced neoplasia. Cyst fluid NGS is highly sensitive and specific for predicting advanced neoplasia in patients with mixed-type IPMNs and should therefore be considered to help upgrade or downgrade risk based on the presence or absence of other worrisome features.

  PublisherOA PDFDOI

• COMPARISON OF MAJOR SPINE NAVIGATION PLATFORMS BASED ON KEY PERFORMANCE METRICS: A META-ANALYSIS OF 16,040 SCREWS

  Orthopaedic Proceedings · 2025-10-22

  article

  Navigation technologies continue to develop and aid the instrumentation of spinal hardware. This meta-analysis attempted to evaluate all available published literature on computer-assisted spine navigation to compare the placement accuracy and surgical outcomes of prominent platforms such as Medtronic, Brainlab, and Stryker, using conventional techniques (free-hand or fluoroscopy) as a common control. Literature searches were performed using OVID MEDLINE and EMBASE databases. Included studies must have performed postoperative computed tomography to evaluate screw placement. Screw placement accuracy, neurologic complications, operative time, and blood loss were then analysed directly via network meta-analysis. Among the 28 included studies, 2959 patients underwent spinal instrumentation surgery, of which 1471 patients were in the navigation group and 1488 patients in the conventional group. Average age of patients in the navigation and conventional groups were 59.1 and 57.8 years old, respectively. 16,040 screws were included of which 7957 screws were placed using navigation technologies and 8083 screws were placed using conventional methods. Navigation manufactures included in the pooled analysis were Medtronic (15 studies, screws=9421), BrainLab (8 studies, screws=4778), Stryker (4 studies, screws=1684), and SeaSpine (7D Surgical) (1 study, screws=157). At all spinal levels, there was a significantly lower risk of major breach and improved screw accuracy in the navigation group compared to the conventional group (OR 0.42, 95% CI 0.27 to 0.63, p&lt;0.0001, I2 = 56%, random effect model). Across platforms, Stryker demonstrated the highest screw accuracy with an 84% reduction in risk of breach (OR 0.16 95% CI 0.06 to 0.41, P &lt; 0.00001, I2 = 0%, REM), followed by Medtronic and then Brainlab. Additionally, there were no significant differences in secondary surgical outcomes including rates of neurologic complications and blood loss between navigation platforms. However, BrainLab demonstrated significantly faster operative time compared to Medtronic by approximately 30 minutes (95% CI −63.27 to −2.47, p=0.03, I2=74%). Our results indicate that use of computer-assisted navigation platforms in spine surgery leads to an approximately 60% reduction in risk of major breach compared to conventional methods, with Stryker demonstrating the highest accuracy among platforms. Furthermore, we demonstrated that this increased accuracy is without negative change to surgical outcomes such as neurologic complications and blood loss. Although the studies analysed are highly heterogeneous, this study is the first to directly and quantitatively compare available navigation platforms. As such, our findings provide a foundation for further investigations and offer insight in guiding the acquisition of navigation platforms by surgeons and institutions.

  PublisherDOI

• Risk Sharing with a Time Preference

  Decision Analysis · 2025-08-07

  articleSenior author

  Classic risk sharing results determine the optimal share of each member in a group that faces a present deal by maximizing the sum of expected utilities of the group members. For decision-makers with exponential utility functions, this formulation is equivalent to maximizing the sum of certain equivalents of the group members. This paper investigates the effects of time preference and different (but constant) risk tolerances among the group members on the individual shares when the payoff is received at a future time period. The analysis first defines several concepts: (i) a group future risk tolerance to be used for valuing the certain equivalent of future payoffs, (ii) a group time preference compounding factor that takes into account the time preference of individuals in the group, and (iii) a group present risk tolerance with time preference by which the partnership should operate for the discounted value of future deals. The results show that if the individuals in a group have the same time preference, then the classic risk sharing results still apply. However, when individuals have different time preferences, then the optimal shares of the individuals are modified by two components; the first depends on the ratio of the individual time preference compounding factor to the group time preference compounding factor, and the second depends on the surety of the deal multiplied by the group future risk tolerance. Several examples illustrate the results.

  PublisherDOI

• AnyTask: an Automated Task and Data Generation Framework for Advancing Sim-to-Real Policy Learning

  ArXiv.org · 2025-12-19

  articleOpen access

  Generalist robot learning remains constrained by data: large-scale, diverse, and high-quality interaction data are expensive to collect in the real world. While simulation has become a promising way for scaling up data collection, the related tasks, including simulation task design, task-aware scene generation, expert demonstration synthesis, and sim-to-real transfer, still demand substantial human effort. We present AnyTask, an automated framework that pairs massively parallel GPU simulation with foundation models to design diverse manipulation tasks and synthesize robot data. We introduce three AnyTask agents for generating expert demonstrations aiming to solve as many tasks as possible: 1) ViPR, a novel task and motion planning agent with VLM-in-the-loop Parallel Refinement; 2) ViPR-Eureka, a reinforcement learning agent with generated dense rewards and LLM-guided contact sampling; 3) ViPR-RL, a hybrid planning and learning approach that jointly produces high-quality demonstrations with only sparse rewards. We train behavior cloning policies on generated data, validate them in simulation, and deploy them directly on real robot hardware. The policies generalize to novel object poses, achieving 44% average success across a suite of real-world pick-and-place, drawer opening, contact-rich pushing, and long-horizon manipulation tasks. Our project website is at https://anytask.rai-inst.com .

  PublisherOA PDF

• Mo1448: ACCURATE DIAGNOSIS OF MUCINOUS PANCREATIC CYSTS USING A NEXT-GENERATION SEQUENCING-INFORMED APPROACH IMPROVES COST-EFFECTIVENESS OF SURVEILLANCE RELATIVE TO CYST FLUID CARCINOEMBRYONIC ANTIGEN LEVELS

  Gastroenterology · 2025-05-01

  article
  PublisherDOI

• Changes to management influenced by next-generation sequencing of pancreatic duct aspirates among patients with main pancreatic duct dilation of unclear etiology: a multicenter cohort study

  Gastrointestinal Endoscopy · 2025-11-01

  article
  PublisherDOI

• AnyTask: an Automated Task and Data Generation Framework for Advancing Sim-to-Real Policy Learning

  arXiv (Cornell University) · 2025-12-19

  preprintOpen access

  Generalist robot learning remains constrained by data: large-scale, diverse, and high-quality interaction data are expensive to collect in the real world. While simulation has become a promising way for scaling up data collection, the related tasks, including simulation task design, task-aware scene generation, expert demonstration synthesis, and sim-to-real transfer, still demand substantial human effort. We present AnyTask, an automated framework that pairs massively parallel GPU simulation with foundation models to design diverse manipulation tasks and synthesize robot data. We introduce three AnyTask agents for generating expert demonstrations aiming to solve as many tasks as possible: 1) ViPR, a novel task and motion planning agent with VLM-in-the-loop Parallel Refinement; 2) ViPR-Eureka, a reinforcement learning agent with generated dense rewards and LLM-guided contact sampling; 3) ViPR-RL, a hybrid planning and learning approach that jointly produces high-quality demonstrations with only sparse rewards. We train behavior cloning policies on generated data, validate them in simulation, and deploy them directly on real robot hardware. The policies generalize to novel object poses, achieving 44% average success across a suite of real-world pick-and-place, drawer opening, contact-rich pushing, and long-horizon manipulation tasks. Our project website is at https://anytask.rai-inst.com .

  PublisherDOI

• India’s Acquisition of MIRVs: Destabilizing the Strategic Stability of South Asia

  Journal of Regional Studies Review · 2025-06-30

  articleOpen accessSenior author

  India’s acquisition of Multiple Independently Targetable Re-entry Vehicle (MIRV) capability and its integration into the Agni-V Inter-Continental Ballistic Missile (ICBM) series reveals a significant shift in the South Asia’s strategic landscape. This particular development not only undermines strategic stability but also intensifies the prevailing security dilemma, potentially accelerating an arms race between India and Pakistan in the region. Analysed through the theoretical frameworks of the Spiral Model and Security Dilemma of Arms Race, this study investigates how India’s MIRV capability exacerbates the threat perception and contributes to the sophisticated security dynamics of South Asia. Moreover, this paper presents the rationalization of MIRVs debate in the hostile South Asian context and its implications on the arms race stability. This paper proposes prospective Confidence-Building Measures (CBMs), with a particular focus on Nuclear CBMs, as mechanisms to mitigate escalatory risks. By placing MIRVs technology within the broader South Asian strategic context, this research paper contributes to the existing literature by highlighting its destabilizing implications and the critical need for cooperative security measures.

  PublisherOA PDFDOI

• 1317: DIABETIC PATIENTS WITH SUB-CENTIMETER PANCREATIC CYSTS ARE MORE LIKELY TO PROGRESS DURING THE CYST SURVEILLANCE PERIOD

  Gastroenterology · 2025-05-01

  article
  PublisherDOI

Recent grants

• Assessing Joint Distributions with Isoprobability Contours

  NSF · $280k · 2006–2010

• EAGER/Collaborative Research: Lectures for Foundations in Systems Engineering

  NSF · $150k · 2016–2021

• SGER/Collaborative Research: Applying Decision Theory to Machining Optimization

  NSF · $114k · 2006–2009

• EAGER: A Decision Analytic Framework for Large-Scale Design and Manufacturing

  NSF · $299k · 2012–2015

• EAGER: A Decision Analytic Framework for Large-Scale Design and Manufacturing

  NSF · $135k · 2015–2016

Frequent coauthors

• Tony L. Schmitz

  13 shared

• Jaydeep Karandikar

  Oak Ridge National Laboratory

  10 shared

• David V. Budescu

  9 shared

• Dušan M. Stipanović

  University of Illinois Urbana-Champaign

  9 shared

• Zhengwei Sun

  Wenzhou Medical University

  8 shared

• Vicki M. Bier

  University of Wisconsin–Madison

  8 shared

• James Matheson

  7 shared

• Avrim Blum

  6 shared

Labs

• AhoonaPI

Awards & honors

• Recipient of multiple awards from the National Science Found…
• First cohort of NSF I-Corps award