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
Publications
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)
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)
Interplay between charge, spin, and phonons in low dimensional strongly interacting systems
M. Soltaniehha
Ph.D. Thesis, Northeastern University ISBN: 9781321699784 (2015)
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
Mixed-Frequency Deep Learning for GDP Forecasting: A Real-Time Framework
M. Soltaniehha, L. Xu, M. M. Badia
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
Selected Talks
ODSC AI East, Boston
Apr 2026Embodied AI: A Cognitive Shift, Not a Cosmetic Change
Keynote
Lunch & Learn, Questrom
Apr 2026The Latest Advances in Gen AI
Workshop
APS Annual Leadership Meeting, Washington D.C.
Feb 2026Science for a Shared Future: Voices from the Field
Plenary Session
HICSS, Maui
Jan 2026My Fate Is to Die Young, But to Live Forever in Song: Echeloned Design Science Research to a Digital-Me Expert System Design
Conference Paper
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
BA/IS843
Data analytics and machine learning at scale. Covers big data platforms including Hadoop, Spark, and BigQuery.
Introduction to Data Analytics
BA780
Descriptive analytics and data munging using Python and data science packages.
Business Analytics Toolbox
BA775
Hands-on experience with scalable cloud computing, databases, and machine learning APIs.
MSBA Python & Statistics Bootcamp
MSBA
Python programming and applied statistics for incoming MSBA students.
Business Analytics in Practice
IS833
Data analysis and machine learning with business applications using Python, NumPy, pandas, and scikit-learn.
Deep Learning with Python Bootcamp
QM878
Intensive bootcamp covering deep learning foundations and practical implementation in Python.
Intro to Python for Data Science
QM877
Programming basics, data cleaning, manipulation, visualization, and exploratory analysis in Python.
Advanced Programming: Data Structures & Algorithms
MF810
Data structures, algorithms, and advanced programming concepts.
Python for Data Science Bootcamp
QM875
Programming, data cleaning, data manipulation, visualization, and exploratory data analysis in Python.
R Programming Bootcamp
QM870
Programming, data cleaning, manipulation, visualization, and EDA in R.
Analytics Practicum
BA890
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.
Find Me Online
A Bit More About Me
Deadvlei, Namibia
I grew up in Iran, studied the quantum behavior of electrons for a living, and somehow ended up teaching business students how to wrangle data. The through line? I love learning new things, and I love it even more when I get to teach it to people who'll use it to build something meaningful.
When I'm not in the classroom or buried in a research paper, you'll probably find me planning my next trip. In the summer of 2025, my wife and I spent two months traveling across Africa, and it was everything: the landscapes, the wildlife, the conversations with strangers that turned into the best part of the journey. I've gone scuba diving in Silfra's glacial waters, off the coast of Hawaii, and around the Caribbean. If there's a reef or a ruin nearby, I'm going.
I play chess (respectably), make a mean kebab (confidently), and pull espresso shots with a level of seriousness that probably belongs in a lab. I enjoy cooking and like experimenting in the kitchen — from Moroccan tagine to Persian khoreshts to pizza from scratch.
I live in Boston with my wife and Babri, our cat, who has never published a single paper yet somehow peer-reviews everything I do from the couch.