Anil Aswani

4119 Etcheverry Hall; Berkeley, CA 94720-1777
Phone: 510-664-9114
email: aaswani@berkeley.edu
url: http://aswani.ieor.berkeley.edu/

Current Appointments
2013-Now Assistant Professor, Industrial Engineering and Operations Research, UC Berkeley

Education
2010 PhD in Electrical Engineering and Computer Sciences, UC Berkeley, advised by Claire Tomlin
2010 Designated Emphasis in Computational and Genomic Biology, UC Berkeley, advised by Peter Bickel, Statistics
2007 MS in Electrical Engineering and Computer Sciences, UC Berkeley
2005 BS in Electrical Engineering, University of Michigan, Ann Arbor

Previous Appointments
2013 Research Scientist, Fitbit
2010-2012 Postdoctoral Researcher, UC Berkeley
2005-2010 Graduate Student Researcher, UC Berkeley
2004 High-Frequency Electronics Group, Intern, National Instruments
2003 Electronic Reliability Engineer, Intern, GE Healthcare

Honors and Awards (Including to Advisees)
2019 CAREER Award, National Science Foundation, Operations Engineering
2019 Undergraduate OR Prize Finalist (to Undergraduate Advisees C.-C. Lo, C. Yang, and L. Na), INFORMS
2019 Marshall-Oliver-Rosenberger Fellowship (to PhD Advisee P. Hespanhol), UC Berkeley
2018 Best Student Paper Award (to PhD Advisee M. Olfat), INFORMS Data Mining & Decision Analytics Workshop
2018 Grassi Fellowship (to PhD Advisee M. Olfat), UC Berkeley
2017 William Pierskalla Finalist, INFORMS Health Applications Society
2017 Grassi Fellowship (to PhD Advisee Y. Mintz), UC Berkeley
2016 William Pierskalla Runner-Up Award, INFORMS Health Applications Society
2016 Katta G. Murty Best Paper Prize in Optimization (to PhD Advisee A. Siddiq), UC Berkeley
2015 Hellman Fellow, Hellman Fellows Program
2012 Leon O. Chua Award, UC Berkeley
2004 EECS Senior Scholar Award, University of Michigan, Ann Arbor

Peer-Reviewed Journal Articles

Accepted and to be Published
2019 Y. Mintz, A. Aswani, P. Kaminsky, E. Flowers, and Y. Fukuoka (2019), Non-stationary bandits with habituation and recovery dynamics, Operations Research. Accepted.

Published
2019 A. Aswani, Z.-J. Shen, and A. Siddiq (2019), Data-driven incentive design in the Medicare Shared Savings Program, Operations Research, vol. 67, no.4: 1002-1026.
2019 A. Aswani (2019), Statistics with set-valued functions: Applications to inverse approximate optimization, Mathematical Programming, vol. 174, no.1-2: 225-251
2019 A. Aswani, P. Kaminsky, Y. Mintz, E. Flowers, and Y. Fukuoka (2019), Behavioral modeling in weight loss interventions, European Journal of Operational Research, vol. 272, no. 3: 1058-1072.
2019 M. Zhou, Y. Fukuoka, K. Goldberg, E. Vittinghoff, and A. Aswani (2019), Applying machine learning to predict future adherence to physical activity programs, BMC Medical Informatics and Decision Making, vol. 19: 169.
2019 A. Miller, A. Aswani, M. Zhou, J. Slagle, M. Weinger, and D. France (2019), Using telephone call rates as an indicator of resilient performance during high nursing workload periods, Cognition, Technology & Work, vol. 21, no. 2: 225-236.
2019 M. Chapman, T. Risom, A. Aswani, E. Langer, R. Sears, and C. Tomlin (2019), Modeling phenotypic-state transitions that are linked to therapeutic escape in triple-negative breast cancer, PLOS Computational Biology, vol. 15, no.3: e1006840.
2018 A. Aswani, Z.-J. Shen, and A. Siddiq (2018), Inverse optimization with noisy measurements, Operations Research, vol. 66, no. 3: 870-892.
2018 L. Na, C. Yang, C.-C. Lo, F. Zhao, Y. Fukuoka, and A. Aswani (2018), Feasibility of reidentifying individuals in large national physical activity data sets from which protected health information has been removed with use of machine learning, JAMA Network Open, vol. 1, no. 8: e186040.
2018 M. Zhou, Y. Fukuoka, Y. Mintz, K. Goldberg, P. Kaminsky, E. Flowers, and A. Aswani (2018), Evaluating machine learning-based automated personalized daily step goals delivered through a mobile phone app: Randomized controlled trial, JMIR Mhealth & Uhealth, vol. 6, no. 1: e28.
2018 Y. Fukuoka, T. Lindgren, Y. Mintz, J. Hooper, and A. Aswani (2018), Applying natural language processing to understand motivational profiles for maintaining physical activity after an application and accelerometer-based intervention: The mPED randomized controlled trial, JMIR Mhealth & Uhealth, vol. 6, no. 6: e10042.
2018 Y. Fukuoka, M. Zhou, E. Vittinghoff, W. Haskell, K. Goldberg, and A. Aswani (2018), Objectively measured baseline physical activity patterns in women in the mPED trial: Cluster analysis, JMIR Public Health & Surveillance, vol. 4, no. 1: e10.
2018 T. Risom, E. Langer, C. Margaret, J. Rantala, A. Fields, C. Boniface, A. Mariano, C. Pelz, N. Kendsersky, K. Johnson-Comacho, L. Dobrolecki, K. Chin, A. Aswani, N. Wang, A. Califano, M. Lewis, P. Spellman, C. Tomlin, A. Adey, J. Gray, R. Sears (2018), Differentiation-state plasticity is a targetable resistance mechanism in basal-like breast cancer, Nature Communications, vol. 9, no. 1: 3815.
2016 A. Aswani (2016), Low-rank approximation and completion of positive tensors, SIAM Journal on Matrix Analysis and Applications, vol. 37, no. 3: 1337-1364.
2013 M. Lee, A. Aswani, A. Han, C. Tomlin, and J. Dueber (2013), Expression-level optimization of a multi-enzyme pathway in the absence of a high-throughput assay, Nucleic Acids Research, vol. 41, no. 22: 10668-10678.
2013 A. Aswani, H. Gonzalez, S. Sastry, and C. Tomlin (2013), Provably safe and robust learning-based model predictive control, Automatica, vol. 49, no. 5: 1216-1226.
2012 A. Aswani, N. Master, J. Taneja, D. Culler, and C. Tomlin (2012), Reducing transient and steady state electricity consumption in HVAC learning-based model predictive control, Proceedings of the IEEE, vol. 100, no. 1: 240-253.
2011 A. Aswani, P. Bickel, and C. Tomlin (2011), Regression on manifolds: Estimation of the exterior derivative, Annals of Statistics, vol. 39, no. 1: 48-81
2010 A. Aswani, S. Keränen, J. Brown, C. Fowlkes, D. Knowles, M. Biggin, P. Bickel, and C. Tomlin (2010), Nonparametric identification of regulatory interactions from spatial and temporal gene expression data, BMC Bioinformatics, vol. 11, no. 413.
2009 A. Aswani, and C. Tomlin (2009), Monotone piecewise affine systems, IEEE Transactions on Automatic Control, vol. 54, no. 8: 1913-1918.

Under Review
2019 Y. Mintz, A. Aswani, P. Kaminsky, E. Flowers, and Y. Fukuoka (2019), Behavioral analytics for myopic agents, Under Review at Management Science.
2019 P. Hespanhol, M. Porter, R. Vasudevan, and A. Aswani (2019), Sensor switching control under attacks detectable by finite sample dynamic watermarking tests, Under Review at IEEE Transactions on Automatic Control.
2019 M. Mahendra, M. Steurer-Muller, S. Hohmann, R. Kellar, A. Aswani, and A. Dudley (2019), Predicting NICU admissions in near-term and term infants with low illness acuity, Under Review at Pediatrics.
2019 J. Lee, M. Laskey, A. Tanwani, A. Aswani, and K. Goldberg (2019), Dynamic regret and convergence guarantees of on-policy imitation learning algorithms, Under Review at International Journal of Robotics Research (IJRR).

Unsubmitted Working Papers with Complete Drafts
2019 M. Olfat, B. Laraia, and A. Aswani (2019), Redesigning SNAP benefits considering time constraints.
2019 M. Olfat and A. Aswani (2019), Consistency of an optimization hierarchy for fair statistical decision problems.
2019 A. Aswani and P. Hespanhol (2019), Statistically-consistent identification of switched linear systems.
2019 M. Mahendra, M. Steurer-Muller, A. Aswani, P. Oishi, and A. Dudley (2019), Resource utilization in unplanned admissions to the pediatric ICU from the ward.

Peer-Reviewed Book Chapters

Published
2012 A. Aswani, M. Biggin, P. Bickel, and C. Tomlin (2012), Nonparametric variable selection and modeling for spatial and temporal regulatory networks, In Methods in Cell Biology, vol. 110: 243-261.
2007 A. Aswani, and C. Tomlin (2007), Reachability algorithm for biological piecewise-affine hybrid systems, In Hybrid Systems: Computation and Control 2007: 633-636.

Peer-Reviewed Conference Articles

Accepted and to be Published
2019 P. Hespanhol and A. Aswani (2019), Surrogate optimal control for strategic multi-agent systems, In Proceedings of the IEEE Conference of Decision and Control. Accepted.

Published
2019 M. Olfat and A. Aswani (2019), Convex formulations for fair principal component analysis, In Proceedings of the AAAI Conference on Artificial Intelligence: 663-670.
2019 M. Porter, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan (2019), Simulation and real-world evaluation of attack detection schemes, In Proceedings of the American Control Conference.
2018 M. Olfat and A. Aswani (2018), Spectral algorithms for computing fair support vector machines, In International Conference on Artificial Intelligence and Statistics (AISTATS): 1933-1942.
2018 J. Lee, M. Laskey, A.K. Tanwani, A. Aswani, and K. Goldberg (2018), A dynamic regret analysis and adaptive regularization algorithm for on-policy robot imitation learning, In Proceedings of the International Workshop on the Algorithmic Foundations of Robotics.
2018 P. Hespanhol, M. Porter, R. Vasudevan, and A. Aswani (2018), Statistical watermarking for networked control systems, In Proceedings of the American Control Conference: 5467-5472.
2018 A. Ouattara and A. Aswani (2018), Duality approach to bilevel programs with a convex lower level, In Proceedings of the American Control Conference: 1388-1395.
2018 P. Hespanhol and A. Aswani (2018), Family-personalized dietary planning with temporal dynamics, In Proceedings of the American Control Conference: 2163-2169
2018 Y. Mintz, J. Cabrera, J. Pedrasa, and A. Aswani (2018), Control synthesis for bilevel linear model predictive control, In Proceedings of the American Control Conference: 2338-2343.
2018 J. Cabrera, Y. Mintz, J. Pedrasa, and A. Aswani (2018), Designing real-time prices to reduce load variability with HVAC, In Proceedings of the American Control Conference: 6170-6175.
2018 C. Garaza, P. Hespanhol, Y. Mintz, J. Pedrasa, and A. Aswani (2018), Impact of occupancy modeling and horizon length on HVAC controller efficiency, In Proceedings of the European Control Conference: 1328-1334.
2018 M. Zhou, Y. Mintz, Y. Fukuoka, K. Goldberg, E. Flowers, P. Kaminsky, A. Castillejo, and A. Aswani (2018), Personalizing mobile fitness apps using reinforcement learning, In ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE).
2017 Y. Mintz, Z.-J. Shen, and A. Aswani (2017), Local water storage control for the developing world, In Proceedings of IEEE Conference on Decision and Control: 5074-5079.
2017 P. Hespanhol, M. Porter, R. Vasudevan, and A. Aswani (2017), Dynamic watermarking for general LTI systems, In Proceedings of IEEE Conference on Decision and Control: 1834-1839.
2017 Y. Mintz and A. Aswani (2017), Polynomial-time approximation for nonconvex optimization problems with an L1-constraint, In Proceedings of IEEE Conference on Decision and Control: 682-687.
2016 M. Chapman, T. Risom, A. Aswani, R. Dobbe, R. Sears, and C. Tomlin (2016), A model of phenotypic state dynamics initiates a promising approach to control heterogeneous malignant cell populations, In Proceedings of IEEE Conference on Decision and Control: 2481-2487.
2012 A. Aswani, N. Master, J. Taneja, A. Krioukov, D. Culler, and C. Tomlin (2012), Quantitative methods for comparing different HVAC control schemes, In International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS): 326-332.
2012 A. Aswani and C. Tomlin (2012), Incentive design for efficient building quality of service, In Allerton Conference on Communication, Control, and Computing: 90-97.
2012 A. Aswani, N. Master, J. Taneja, A. Krioukov, D. Culler, and C. Tomlin (2012), Energy-efficient building HVAC control using hybrid system LBMPC, In IFAC Conference on Nonlinear Model Predictive Control: 496-501.
2012 A. Aswani, N. Master, J. Taneja, V. Smith, A. Krioukov, D. Culler, and C. Tomlin (2012), Identifying models of HVAC systems using semi-parametric regression, In Proceedings of the American Control Conference: 3675-3680.
2012 A. Aswani, P. Bouffard, and C. Tomlin (2012), Extensions of learning-based model predictive control for real-time application to a quadrotor helicopter, In Proceedings of the American Control Conference: 4661-4666.
2012 P. Bouffard, A. Aswani, and C. Tomlin (2012), Learning-based model predictive control on a quadrotor: Onboard implementation and experimental results, In Proceedings of the IEEE International Conference on Robotics and Automation: 279-284.
2011 A. Aswani and C. Tomlin (2011), Game-theoretic routing of GPS-assisted vehicles for energy efficiency, In Proceedings of the American Control Conference: 3375-3380.
2009 A. Aswani, H. Guturu, and C. Tomlin (2009), System identification of hunchback protein patterning in early Drosophila embryogenesis, In Proceedings of IEEE Conference on Decision and Control: 7723-7728.
2009 A. Aswani, N. Boyd, and C. Tomlin (2009), Graph-theoretic topological control of biological genetic networks, In Proceedings of the American Control Conference: 1700-1705.
2009 A. Aswani, P. Bickel, and C. Tomlin (2009), Statistics for sparse, high-dimensional, and nonparametric system identification, In Proceedings of the IEEE International Conference on Robotics and Automation: 2133-2138.
2008 A. Aswani and C. Tomlin (2008), Topology based control of biological genetic networks, In Proceedings of IEEE Conference on Decision and Control: 781-786.

Unsubmitted Working Papers with Complete Drafts
2019 M. Olfat and A. Aswani (2019), Average margin regularization for classifiers.

Professional Talks, in Addition to Conference Talks Listed Above
2018 A. Aswani (2018), "Making robust decisions from data", Presented at: Operations Research Seminar, Stanford University.
2018 A. Aswani (2018), "Personalizing physical activity interventions using reinforcement learning", Presented at: POMS Annual Conference.
2018 A. Aswani (2018), "Statistics with set-valued functions: Applications to inverse approximate optimization", Presented at: Berkeley-Columbia Meeting in Engineering and Statistics.
2018 A. Aswani (2018), "Combining inverse optimization with reinforcement learning", Presented at: INFORMS Optimization Society Conference.
2018 A. Aswani (2018), "Making robust decisions from data", Presented at: Industrial Engineering and Operations Research, Columbia University.
2017 A. Aswani (2017), "Making robust decisions from data", Presented at: Industrial Engineering and Management Sciences, Northwestern University.
2017 A. Aswani (2017), "Making robust decisions from data", Presented at: Control Seminar, University of Michigan.
2017 A. Aswani (2017), "Analytics for personalized healthcare using mobile devices", Presented at: INFORMS Annual Meeting.
2017 A. Aswani (2017), "Personalizing health treatments using Bayesian inverse optimization", Presented at: INFORMS Annual Meeting.
2017 A. Aswani (2017), "Making robust decisions from data", Presented at: Center for Systems and Control (CSC@USC) and Electrical Engineering, University of Southern California.
2017 A. Aswani (2017), "Personalizing health treatments using Bayesian inverse optimization", Presented at: INFORMS Healthcare.
2017 A. Aswani (2017), "Family-customized nutritious and low-cost dietary planning support", Presented at: INFORMS Healthcare.
2017 A. Aswani (2017), "Tutorial on unsupervised learning", Presented at: ENSAE ParisTech.
2017 A. Aswani (2017), "Designing personalized healthcare treatments using bilevel programming", Presented at: Applied Mathematics, École Polytechnique.
2016 A. Aswani (2016), "Designing personalized weight loss treatments using bilevel programming", Presented at: Electrical and Systems Engineering, Washington University in St. Louis.
2016 A. Aswani (2016), "Data-driven incentive design in the Medicare Shared Savings Program", Presented at: INFORMS Annual Meeting.
2016 A. Aswani (2016), "Numerical solution of bilevel programs using a duality-based approach", Presented at: International Conference on Continuous Optimization.
2016 A. Aswani (2016), "Inverse Optimization with Noisy Data and Applications to Predictive Modeling for Health Care", Presented at: INFORMS International Meeting.
2016 A. Aswani (2016), "Low-Rank Approximation and Completion of Positive Tensors", Presented at: INFORMS Optimization Society Conference.
2015 A. Aswani (2015), "Quantitative Modeling of Behavior Change for Personalized Weight Loss Interventions ", Presented at: INFORMS Healthcare.
2015 A. Aswani (2015), "Quantitative Modeling of Behavior Change for Personalized Weight Loss Interventions ", Presented at: European Conference on Operational Research.
2015 A. Aswani (2015), "Positive Low-Rank Tensor Completion", Presented at: Neyman Seminar, Department of Statistics, UC Berkeley.
2014 A. Aswani (2014), "Positive Low-Rank Tensor Completion", Presented at: ISL Colloquium, Stanford University.
2014 A. Aswani (2014), "Data-Driven Decision Making for Healthcare and Energy Systems", Presented at: Operations Research Department, Naval Postgraduate School.
2014 A. Aswani (2014), "Learning-Based Model-Predictive Control", Presented at: Robotics: Systems and Science.
2012 A. Aswani (2012), "Robust, adaptive control for semi-autonomous systems", Presented at: Waterloo Institute for Sustainable Energy, University of Waterloo.
2012 A. Aswani (2012), "Robust statistical control theory for high performance systems", Presented at: Automatic Control Laboratory, ETH Zürich.
2012 A. Aswani (2012), "Nonparametric modeling of spatial and temporal transcription in Drosophila embryos from in vivo gene expression data", Presented at: ESF-EMBO Conference on Systems Biology of Drosophila.
2010 A. Aswani (2010), "Statistics for sparse, high-dimensional, and nonparametric system identification", Presented at: GRASP Laboratory, University of Pennsylvania.
2009 A. Aswani (2009), "A network-level approach to predictive toxicology", Presented at: Advances in Drug Discovery Informatics: eCheminfo InterAction Meeting.
2009 A. Aswani (2009), "Statistics for sparse, high-dimensional, and nonparametric system identification", Presented at: Sibley School of Mechanical and Aerospace Engineering, Cornell University.

Technical Reports
2014 A. Aswani, P. Bouffard, X. Zhang, and C. Tomlin (2014), Practical comparison of optimization algorithms for learning-based MPC with linear models, arXiv:1404.2843.
2012 A. Aswani, H. Gonzalez, S. Sastry, and C. Tomlin (2012), Statistical results on filtering and epi-convergence for learning-based model predictive control, arXiv:1208.0864.

Teaching

Doctoral Students Advised
2019-Now Ilgin Dogan, UC Berkeley
2019-Now Yoon Lee, UC Berkeley
2017-Now Caleb Bugg, UC Berkeley
2016-Now Matt Olfat, UC Berkeley
2015-Now Pedro Hespanhol, UC Berkeley
2014-2018 Auyon Siddiq, UC Berkeley, Assistant Professor at University of California, Los Angeles
2014-2018 Mo Zhou, UC Berkeley, Data Scientist at Uber Technologies Inc.
2014-2018 Yonatan Mintz, UC Berkeley, Postdoctoral Scholar at Georgia Institute of Technology

Masters Students Advised
2018 Ahmed Ayadi, Technical University of Munich (TUM)
2018 Abigail Chaver, UC Berkeley
2016 Qi (Charlene) Xu, UC Berkeley
2016 Hing (Katie) Mak, UC Berkeley
2015-2016 Aurelien Ouattara, UC Berkeley
2013-2014 Angel Yang, UC Berkeley
2013 Sarah Cox, UC Berkeley
2011 Xiaojing Zhang, ETH Zürich

Undergraduate Students Advised
2018-Now Wayne Li, UC Berkeley
2018 Steve Sloan, UC Berkeley
2017-2018 Liangyuan Na, UC Berkeley
2017-2018 Cong Yang, UC Berkeley
2017-2018 Chi-Cheng Lo, UC Berkeley
2016-2017 Jessica Lin, UC Berkeley
2016-2017 Emily Ma, UC Berkeley
2016-2017 Smita Jain, UC Berkeley
2016 Emily Rah, UC Berkeley
2014-2015 Ryan Corley, UC Berkeley
2014 Pedro Hespanhol, Pontifical Catholic University of Rio de Janeiro (PU-RIO)
2013 Benjamin Lewis, UC Berkeley
2013 Jolie Tan, UC Berkeley
2011 Virginia Smith, University of Virginia
2010-2012 Neal Master, UC Berkeley
2009 Tremaine Rawls, Norfolk State University
2008 Nicholas Boyd, UC Berkeley
2007-2008 Eugene Li, UC Berkeley
2007-2008 Harendra Guturu, UC Berkeley

Courses Developed or Revised
2014-Now IEOR 165 - Engineering Statistics, Quality Control, and Forecasting, Instructor, UC Berkeley
Added material on method of moments, L1 and L2 regularization for estimation and regression, cross-validation, nonparametric and semiparametric estimators, and support vector machines from machine learning.
2014-Now IEOR 265 - Learning and Optimization, Instructor, UC Berkeley
Developed new course covering topics in high-dimensional analysis for statistics and convex geometry, variational analysis, robust and adaptive optimization modeling, and case-studies of applications to engineered systems.
2013-Now IEOR 151 - Service Operations Design and Analysis, Instructor, UC Berkeley
Added material on machine learning with the newsvendor model, kidney matching exchanges, hospital residency matching, principal-agent models, risk in decision-making, and queuing theory for service systems.

Courses Taught
2015-Now IEOR 165 - Engineering Statistics, Quality Control, and Forecasting, Instructor, UC Berkeley
2015-Now IEOR 265 - Learning and Optimization, Instructor, UC Berkeley
2014-Now ENGIN 296MA/B - Capstone Project, Advisor, UC Berkeley
2014 IEOR 290A - Dynamic Production, Instructor, UC Berkeley
2013-Now IEOR 151 - Service Operations Design and Analysis, UC Berkeley
2013-Now EE 40 - Introduction to Microelectronic Circuits, Graduate Student Instructor, UC Berkeley
2013-Now EE 128 - Feedback Control, Graduate Student Instructor, UC Berkeley

Grants and Gift Funding
2019-Now PI: CAREER: Data-Driven Personalized Chronic Disease Management, National Science Foundation, Total: $500,000.
2019-Now Co-PI: Reinforcement Learning-Based Scheduling for Manufacturing Processes, Western Digital Corporation, Total: $18,073.
2019-Now Co-PI: Deep Fairness in Public Policy, Center for Long-Term Cybersecurity, Total: $15,000.
2018-Now Co-PI: Attack Detection and Mitigation for Distributed Water Grid Management, Siebel Energy Institute, Total: $50,000.
2018-Now Co-PI: Center for Industrial Big Data Analytics (CIBDA), Hitachi, Inc., Total: $137,000.
2018 Co-PI: Deep Fairness in Classification, Center for Long-Term Cybersecurity, Total: $15,000.
2017 PI: Securing Protected Health Information in Mobile Health Devices, Center for Long-Term Cybersecurity, Total: $15,000.
2016-2017 Co-PI: Data Analytics and Stochastic Control for Optimal Management of Microgrid Generation and Storage Resources, Siebel Energy Institute, Total: $19,000.
2015-2017 Co-PI: Resilient Cyber Physical Societal Scale Systems, Commission on Higher Education, Total: $1,575,825.
2015-2017 PI: Addressing Food Insecurity in Underserved Communities Using Operations Research, Hellman Fellows Fund, UC Berkeley, Total: $12,672.
2014-2017 PI: EAGER: Quantitative Modeling of Behavioral- Change for Personalized Weight Loss Interventions, National Science Foundation, Total: $300,000.
2012-2017 Research Scientist: Quantitative Modeling of Transcriptional Information in the Drosophilia Genome, LBNL Lawrence Berkeley National Laboratory via NIH, Total: $1,290,513.

Press and Publicity
2019 Press release: Restructuring Medicare Shared Savings Program Can Yield 40% Savings in Health Costs, INFORMS
2019 Op-ed article: Artificial Intelligence Could Identify You and Your Health History From Your Step Tracker, USA Today
2019 Magazine article: Protecting Health Data Privacy, Berkeley Engineer
2018 News article: Designing Algorithms to Increase Fairness in Artificial Intelligence, SIAM News
2018 News interview: Anonymous Patient Data May Not Be As Private As Previously Thought, Reuters
2018 News article: Coverage by Forbes, Business Insider, and nearly 30 Other Organizations
2018 News interview: Aggregated Data From Wearables Don't Fully Conceal Individuals' Identities, MedPage Today
2018 Press release: Advancement of Artificial Intelligence Opens Health Data Privacy to Attack, Berkeley News
2018 News interview: Could These Apps Help You Lose Weight For Good This Year?, BBC News
2018 News article: UC Berkeley Researchers Develop App to Modify Fitness Goals Automatically, The Daily Californian
2018 Website article: New Exercise App Uses Machine Learning to Keep Goals Within Reach, Berkeley Engineering
2018 Magazine article: Exercising with Cal Fitness, Berkeley Engineer
2016 Magazine article: Big Data, mHealth and the Pursuit of Precision Behavior Change, Science of Caring, UCSF School of Nursing
2011 Television interview: Daily Planet, Discovery Channel Canada
2011 Major website coverage: Feber.se, Forbes.com, Gizmodo, IEEE Spectrum Automaton
2011 YouTube demonstration: http://www.youtube.com/watch?v=dL_ZFSvLXlU

Software
2018 Numerical Implementation Software for Fair Principal Component Analysis
Python code that performs fair (kernel) principal component analysis.
https://github.com/molfat66/FairML
2018 Numerical Implementation Software for Statistics with Set-Valued Functions
MATLAB code that for particular examples performs kernel regression of set-valued functions and solves the inverse approximation optimization problem.
http://ieor.berkeley.edu/~aaswani/code/ssvf.zip
2017 Numerical Implementation Software for Fair Support Vector Machines
MATLAB code that computes fair (kernel) support vector machines.
https://github.com/molfat66/FairML
2014 Numerical Implementation Software for Positive Low-Rank Tensor Completion
MATLAB code that solves a partition log-linear formulation for positive low-rank tensor completion.
http://ieor.berkeley.edu/~aaswani/plrt/
2013 Numerical Solver Software for Learning-Based Model Predictive Control
C++ code that solves different quadratic programming formulations that arise when learning-based model predictive control is applied to linear models.
https://bitbucket.org/lbmpc/lbmpc.bitbucket.org/wiki/Home
2012 Energy Quantification and Comparison Software
MATLAB code that statistically compares and quantifies differences in energy consumption and occupant comfort due to changes in building automation algorithms.
http://hybrid.eecs.berkeley.edu/~NEDE/compEng.zip
2010 Exterior Derivative Estimation Software
MATLAB code that computes model coefficients using the exterior derivative estimator.
http://hybrid.eecs.berkeley.edu/~NEDE/EDE_Code.zip
2010 NODE Modeling Software for Drosophila Embryogenesis
MATLAB code for modeling even-skipped stripes during stage 5 of embryo formation.
http://bdtnp.lbl.gov/Fly-Net/archives/BID_downloads/Software/NODE_Model.zip

External Service
2019 Panelist, Interdisciplinary Research and Writing Collaborative Grants, INFORMS New Faculty Colloquium
2019 Grant Proposal Review Panel, National Science Foundation
2019 Technical Program Committee, AAAI Conference on Artificial Intelligence 2020
2019 Workshop Co-Organizer, Bay Area Optimization Meeting
2018-Now Senior Editor, Production and Operations Management
2018-Now Associate Editor, Journal of Optimization Theory and Applications
2018-Now Associate Editor, Journal of Management Science and Engineering
2018 Workshop Co-Organizer, Bay Area Optimization Meeting
2018 Invited Session Organizer, INFORMS Optimization Society Conference
2017 Invited Session Organizer, Health Applications Society, INFORMS Annual Meeting
2017 Invited Area Chair, INFORMS Healthcare
2017 Technical Program Committee, ACM e-Energy 2017
2016 Invited Session Organizer, Health Applications Society, INFORMS Annual Meeting
2016 Grant Proposal Review Panel, National Science Foundation
2016 Invited Session Organizer, Health Applications Society, INFORMS International
2015 Invited Session Organizer, Health Applications Society, INFORMS Annual Meeting
2015 Workshop Co-Organizer, Bay Area Optimization Meeting
2014 Workshop Co-Organizer, Robotics Science and Systems
2014 Technical Program Committee, ACM e-Energy 2014
2013 Technical Program Committee, ACM e-Energy 2013
2012 Workshop Organizer, IEEE Conference on Decision and Control

Peer-Review Service
2008-Now Journal Referee
Control:
Acta Automatica Sinica; AIAA Journal of Guidance, Control, and Dynamics; Automatica; ACM Transactions on Intelligent Systems and Technology; Control Engineering Practice; IEEE Transactions on Automatic Control; IEEE Transactions on Control of Network Systems; IEEE Transactions on Control Systems Technology; IEEE Transactions on Robotics; IEEE Transactions on Cybernetics; Systems & Control Letters
Operations Research:
International Journal of Production Research; Management Science; Manufacturing & Service Operations Management; Operations Research; Stochastic Systems
Other:
Bioinformatics; Energy and Buildings; IEEE Transactions on Smart Grid; Journal of Medical Internet Research; Proceedings of the IEEE; Sensors
Statistics:
Annals of Statistics; Biometrika; Journal of the American Statistical Association
2008-Now Conference Referee
Control:
American Control Conference; European Control Conference; IEEE Conference on Decision and Control; IEEE Multi-Conference on Systems and Control; IFAC Conference on Nonlinear Model Predictive Control; IFAC World Congress
Robotics:
IEEE Conference on Robotics and Automation; IEEE/RSJ International Conference on Intelligent Robots and Systems

University Service
2018-2019 IEOR Department Seminar Co-Organizer, UC Berkeley
2017-Now IEOR Department Graduate Fellowships Committee, UC Berkeley
2017-2018 (IEOR) Stochastics Faculty Search Committee, UC Berkeley
2016-Now UCB-UCSF Joint Medical Program Core Faculty, UC Berkeley
2015-2016 (IEOR) Decision-Analytics Faculty Search Committee, UC Berkeley
2014-2015 (Engineering) Decision-Analytics Faculty Search Committee, UC Berkeley
2015-Now IEOR Department Graduate Admissions Committee, UC Berkeley
2014-Now M.Eng. Capstone Project - Student Group Advisor, UC Berkeley
2014-2015 IEOR Department Seminar Co-Organizer, UC Berkeley
2014-Now Faculty advisor of Berkeley chapter of Alpha Pi Mu, the Industrial Engineering Honor Society, UC Berkeley
2014-Now Undergraduate student advising for IEOR majors, UC Berkeley
2014 IEOR 180 - Senior Project, Student Group Advisor, UC Berkeley