Mohammad
Soltaniehha
Clinical Assistant Professor of Information Systems
Embodied AI & Interactive Avatars · LLMs for Social Impact · ML in Economics & Cancer Research
About
I'm a Clinical Assistant Professor in the Information Systems Department at Boston University's Questrom School of Business. My research sits at the intersection of artificial intelligence and real-world impact — from embodied AI and interactive avatars to socially impactful applications of LLMs and machine learning in economic and cancer research.
Before joining BU in 2018, I worked as a Data Scientist at Infor's Dynamic Science Labs, where I designed data-driven applications including customer churn forecasting, time-series anomaly detection, inventory optimization, and lead scoring. My academic foundation is in computational physics — I earned my Ph.D. from Northeastern University studying low-dimensional strongly correlated quantum systems.
I teach courses spanning big data analytics, Python and R programming, cloud computing, database management, and business analytics. I'm passionate about democratizing data science education and founded the APS Data Science Unit (GDS) in 2018 to provide educational opportunities for scientists.
APS Board Member
2025–2027
Google Cloud Faculty Expert
Inaugural Cohort, 2020
DSECOP Editor-in-Chief
2022–Present
Patent Holder
CNN for Cancer Classification
Education
Ph.D., Computational Condensed Matter Physics
Northeastern University
2015
M.Sc., Computational Condensed Matter Physics
University of Wyoming
2012
M.Sc., Computational Statistical Physics
Sharif University of Technology
2010
B.Sc., Physics
University of Tabriz
2007
Research Interests
Research
Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images
J. Noorbakhsh, S. Farahmand, A. Foroughi Pour, S. Namburi, D. Caruana, D. Rimm, M. Soltaniehha, K. Zarringhalam, J. Chuang
Nature Communications 11, 6367 (2020)
This work demonstrates that deep learning models trained on cancer histology images learn spatial behaviors that are conserved across different cancer types, suggesting shared organizational principles in tumor microenvironments.
Read PaperPublications
Era of experiential and heuristic learning
J. McNally, Y. Yin, M. Soltaniehha, M. Bahrami
AI & Society (2025)
Data science education in undergraduate physics: lessons learned from a community of practice
K. Shah, J. Butler, A. Knaub, W. Ratcliff, A. Zenginoğlu, M. Soltaniehha
American Journal of Physics 92, 655–662 (2024)
Spectral function of the U→∞ one-dimensional Hubbard model at finite temperature and the crossover to the spin-incoherent regime
M. Soltaniehha, A. E. Feiguin
Physical Review B 90, 165145 (2014)
Interplay of charge, spin and lattice degrees of freedom on the spectral properties of the one-dimensional Hubbard-Holstein model
A. Nocera, M. Soltaniehha, C.A. Perroni, V. Cataudella, A. E. Feiguin
Physical Review B 90, 195134 (2014)
Class of Variational Ansatze for the Spin-Incoherent Ground State of a Luttinger Liquid Coupled to a Spin Bath
M. Soltaniehha, A. E. Feiguin
Physical Review B 86, 205120 (2012)
Working Papers
AI's Job Shakeup: Analyzing the Uneven Impact of AI Adoption on Labor Demand
B. Gu, M. Soltaniehha, X. Wang
My Fate Is to Die Young, But to Live Forever in Song: Echeloned Design Science Research to a Digital-Me Expert System Design
M. Osmo, T. Tuunanen, Y. Yin, M. Soltaniehha, P. Parvinen
SHAPoly: A Novel Shapley-Polynomial Framework for Estimating Nonlinear Dynamics in Macroeconomic Data Using Deep Neural Networks
L. Longo, M. Soltaniehha
Machine Learning Meets Macroeconomics: A Fresh Perspective through a Novel Forecasting Framework
M. M. Badia, M. Soltaniehha, L. Xu
Patent
Convolutional Neural Networks For Classification Of Cancer Histological Images
J. Chuang, J. Noorbakhsh, A. Foroughi Pour, K. Zarringhalam, S. Farahmand, M. Soltaniehha
WO 2021/016131 A1 · PCT/US2020/042675 · US 2025/0378559 A1
Scholarly Review Activities
Teaching
I teach a range of courses at Boston University's Questrom School of Business, spanning data analytics, machine learning, programming, and cloud computing. Here are the core courses I've developed and regularly teach.
Big Data Analytics for Business
Big DataBA/IS843
Data analytics and machine learning at scale. Covers big data platforms including Hadoop, Spark, and BigQuery.
Introduction to Data Analytics
AnalyticsBA780
Descriptive analytics and data munging using Python and data science packages.
Business Analytics Toolbox
AnalyticsBA775
Hands-on experience with scalable cloud computing, databases, and machine learning APIs.
Business Analytics in Practice
AnalyticsIS833
Data analysis and machine learning with business applications using Python, NumPy, pandas, and scikit-learn.
Deep Learning with Python Bootcamp
Machine LearningQM878
Intensive bootcamp covering deep learning foundations and practical implementation in Python.
Intro to Python for Data Science
ProgrammingQM877
Programming basics, data cleaning, manipulation, visualization, and exploratory analysis in Python.
Advanced Programming: Data Structures & Algorithms
ProgrammingMF810
Data structures, algorithms, and advanced programming concepts.
Python for Data Science Bootcamp
ProgrammingQM875
Programming, data cleaning, data manipulation, visualization, and exploratory data analysis in Python.
R Programming Bootcamp
ProgrammingQM870
Programming, data cleaning, manipulation, visualization, and EDA in R.
Analytics Practicum
AnalyticsBA890
Applied analytics project work with real-world data and business problems.
Additionally, I have coordinated capstone projects (BA886/BA887/BA888), taught ML & Computer Vision bootcamps internationally (Pano Masterclass, Taiwan), and previously taught Statistical Mechanics & Thermodynamics and Physics labs at the University of Wyoming.
Service & Leadership
Professional Service
Board Member
CurrentAmerican Physical Society
Editor-in-Chief
CurrentDSECOP
Curated content and managed 12 Ph.D. fellows in the APS-funded Data Science Education Community of Practice.
Faculty Expert
CurrentGoogle Cloud — Faculty Expert Program
Member of the inaugural cohort helping educators explore Google Cloud for teaching and research.
Faculty Affiliate
CurrentBU Hariri Institute for Computing
Founding Chair / Founder
American Physical Society — Data Science Unit (GDS)
Founded the data science unit within APS to provide educational opportunities and a research discussion platform.
Research Affiliate
BU Center for Antiracist Research
Research Innovator
Google Cloud — Research Innovators Program
Data Science Advisor
Vistan Health, LLC.
Served on the advisory board offering data science consultation.
Community Organizer / Co-founder
APS — Boston Local Links
Helped APS launch professional community gatherings bridging academia and industry.
Committee Member
APS — Committee on Membership
Planned services for 55,000+ APS members. Proposed initiatives leading to FECS and GDS formation.
Member-at-Large
APS — Forum for Early Career Scientists
University Service
Faculty Coordinator, Questrom Learning Communities
2021 – PresentFaculty Lead, Questrom Learning Communities
2021 – PresentPDC Faculty Member, MSBA
2019 – PresentFaculty Advisor, Digital Technology & Operations Learning Community
2019 – PresentGraduate Analytics Committee, Questrom
2022 – 2023Questrom IT Steering Committee
2019 – 2021Faculty Search Committee, IS Department
2022 – 2023Faculty Search Committee, IS Department
2019 – 2020Curriculum Design Committee, MSBA
2018 – 2019Grants
Google Cloud Research Credit
2021
Google Cloud Platform Research Credit
2020
Google Cloud Platform Research Credit
2019
Google Cloud Platform Research Credit
2018
In the Media
"You're just staring at yourself: Job seekers lament AI interview process"
"Built to Last in an AI Future"
by M. Soltaniehha
"Hybrid Text Classification: Labeling with LLMs and Dense Neural Networks"
by M. Soltaniehha
"Go Ahead, Write Your Cover Letter With ChatGPT"
by S. G. Carmichael
"Companies Want Fewer Grad Hires This Year"
by J. Pisani and L. Ellis
"The Physics Curriculum Needs More Data Science — and One Team is Making it Easier Than Ever to Integrate It"
by L. Boatman
"Message from the Chair"
by M. Soltaniehha
"The Topical Group on Data Science"
by A. Dove
"Laramie Celebrates Persian New Year"
by S. Hossaini
Contact
I welcome collaboration opportunities, speaking invitations, and inquiries from prospective students. Feel free to reach out.