About Professor Hassan

Saad Hassan obtained his PhD from the Golisano College of Computing and Information Sciences at the Rochester Institute of Technology in 2023. His research centers on Accessible Computing, Human-Computer Interaction (HCI), and Computational Social Science, with a focus on technologies to promote inclusion, facilitate learning, and encourage creative expression among individuals with disabilities. During his graduate studies, Saad worked as a research scientist intern at Google AI and Meta Reality Labs, where he helped develop and deploy innovative technologies. Saad's research has been featured in prestigious computing conferences and journals, including the ACM Conference on Human Factors in Computing Systems (CHI), the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), the ACM Transactions on Accessible Computing (TACCESS), and the Conference on Empirical Methods in Natural Language Processing (EMNLP). Currently, he serves as a program committee member for CHI and ASSETS.
 

Research Interests

Accessible Computing, Human-Computer Interaction (HCI), and Computational Social Science, with a focus on AI-powered technologies to facilitate inclusion, learning, and creative expression for individuals with disabilities.

Office

307 Paul Hall

Courses Taught

CMPS 4661/CMPS 6663: Human-Computer Interaction

Google Scholar Page

DBLP Biography

• 2023: Present: Professor of Practice, Tulane University, New Orleans, LA
• 2022-2023: Postdoctoral Fellow, US Food and Drug Administration
• 2021 - 2022: Lecturer, University of Colorado, Boulder CO
• 2017-2020: Ph.D., Applied Mathematics, Arizona State University, Tempe AZ

As an undergraduate, Daniel P. Howsmon majored in both chemical engineering and biochemistry at Texas A&M University where he became fascinated with using computational techniques to solve problems in medicine. He then went on to earn a Ph.D. in Chemical and Biological Engineering at Rensselaer Polytechnic Institute where he developed fault detection techniques for insulin infusion pumps and identified combinations of plasma metabolites that may be informative for diagnosing autism spectrum disorder. For his postdoctoral work, he joined the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin where he modeled signal transduction pathways relevant to heart valve diseases. He joined the Department of Chemical and Biomolecular Engineering at Tulane University as an assistant professor in 2023.

29.    A. Khang, Q. Nguyen, X. Feng, D. P. Howsmon, and M. S. Sacks, “Three-dimensional analysis of aortic valve interstitial cell shape and its relation to contractile behavior,” Acta Biomateriala, vol. 163, pp. 194–209, Jun. 2023. doi: 10.1016/j.actbio.2022.01.039
28.    T. M. West, D. P. Howsmon, M. W. Messida, H. N. Vo, A. A. Janobas, A. B. Baker, and M. S. Sacks, “The effects of strain rate and level on aortic valve interstitial cell activation in a 3D hydrogel,” APL Bioengineering, vol. 7, no. 2, p. 026 101, 2023. doi: 10.1063/5.0138030 FEATURED ARTICLE
27.    L. Bansal, E.-M. Nichols, D. P. Howsmon, J. Neisen, F. Cunningham, S. Petit-Frere, S. Ludbrook, and V. Damian, “Mathematical modeling of complement pathway dynamics for target validation and selection of drug modalities for complement therapies,” Frontiers in Pharmacology, vol. 13, p. 855 743, Apr. 2022. doi: 10.3389/fphar.2022.855743
26.    A. Khang*, E. M. Lejeune*, A. Abbaspour, D. P. Howsmon, and M. S. Sacks, “On the 3D correlation between myofibroblast shape and contraction,” Journal of Biomechanical Engineering, vol. 143, no. 9, p. 094 503, Sep. 2021. doi: 10.1115/1.4050915
25.    E. Castillero, D. P. Howsmon, B. V. Rego, Y. Xue, C. Camillo, S. Keeney, K. H. Driesbaugh, T. Kawashima, George, R. C. Gorman, J. H. Gorman III, M. S. Sacks, R. J. Levy, and G. Ferrari, “Altered responsiveness to TGF-β and BMP and increased CD45+ cell presence in mitral valves are unique features of ischemic mitral regurgitation,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 41, no. 6, pp. 2049–2062, Jun. 2021. doi: 10.1161/ATVBAHA.121.316111 EDITOR’S PICK
24.    D. P. Howsmon and M. S. Sacks, “On valve interstital cell signaling: The link between multiscale mechanics and mechanobiology,” Cardiovascular Engineering and Technology, vol. 12, pp. 15–27, Feb. 2021. doi: 10.1007/s13239-020-00509-4
23.    K. M. Kodigepalli, K. Thatcher, T. West, D. P. Howsmon, F. J. Schoen, M. S. Sacks, C. K. Breuer, and J. Lincoln, “Biology and biomechanics of heart valve extracellular matrix,” Journal of Cardiovascular Development and Disease, vol. 7, no. 4, p. 57, Dec. 2020. doi: 10.3390/jcdd7040057
22.    S. Ayoub, D. P. Howsmon, C.-H. Lee, and M. S. Sacks, “On the role of predicted mitral valve interstitial cell deformation on its biosynthetic behavior,” Biomechanics and Modeling in Mechanobiology, Aug. 2020. doi: 10.1007/s10237-020-01373-w
21.    D. P. Howsmon*, B. V. Rego*, E. Castillero, S. Ayoub, A. H. Khalighi, R. C. Gorman, J. H. Gorman III, G. Ferrari, and M. S. Sacks, “Mitral valve leaflet response to ischaemic mitral regurgitation: From gene expression to tissue remodeling,” Journal of the Royal Society Interface, vol. 17, no. 165, p. 20 200 098, May 2020. doi: 10.1098/rsif.2020.0098
20.    D. P. Howsmon*, S. M. Quinn*, J. Hahn, and S. P. Gilbert, “Kinesin-2 heterodimerization alters catalytic properties to control entry into the processive run,” Journal of Biological Chemistry, vol. 293, no. 35, pp. 13 389–13 400, Jul. 2018. doi: 10.1074/jbc.RA118.002767
19.    D. P. Howsmon, T. Vargason, R. A. Rubin, S. Melnyk, S. J. James, R. Frye, and J. Hahn, “Multivariate techniques enablea biochemical classification of children with autism spectrum disorder versus typically-developing peers: A comparison and validation study,” Bioengineering and Translational Medicine, vol. 3, no. 2, pp. 156–165, May 2018. doi: 10.1002/btm2.10095 TOP CITED ARTICLE 2018 – 2019
18.    T. Vargason, D. P. Howsmon, and J. Hahn, “From data to diagnosis: The search for biochemical markers of autism spectrum disorder,” Chemical Engineering Progress, vol. 114, no. 5, pp. 40–45, May 2018
17.    G. P. Forlenza, F. M. Cameron, T. T. Ly, D. Lam, D. P. Howsmon, N. Baysal, G. Kulina, L. Messer, P. Clinton, C. Levister, S. D. Patek, C. J. Levy, R. P. Wadwa, D. M. Maahs, B. W. Bequette, and B. A. Buckingham, “Fully closed-loop multiple model probabilistic predictive controller artificial pancreas performance in adolescents and adults in a supervised hotel setting,” Diabetes Technology & Therapeutics, vol. 20, no. 5, pp. 335–343, May 2018. doi: 10.1089/dia.2017.0424
16.    D. P. Howsmon, N. Baysal, B. A. Buckingham, G. P. Forlenza, T. T. Ly, D. M. Maahs, T. Marcal, L. Towers, E. Mauritzen, S. Deshpande, L. M. Huyett, J. E. Pinsker, R. Gondhalekar, F. J. Doyle III, E. Dassau, J. Hahn, and B. W. Bequette, “Real-time detection of infusion site failures in a closed-loop artificial pancreas,” Journal of Diabetes Science and Technology, vol. 12, no. 3, May 2018. doi: 10.1177/1932296818755173
15.    D. P. Howsmon, J. B. Adams, U. Kruger, E. Geis, E. Gehn, and J. Hahn, “Erythrocyte fatty acid profiles in children are not predictive of autism spectrum disorder status: A case control study,” Biomarker Research, vol. 6, p. 12, Mar. 2018. doi: 10.1186/s40364-018-0125-z
14.    D.-W. Kang, Z. E. Ilhan, N. G. Isern, D. W. Hoyt, D. P. Howsmon, M. Shaffer, C. A. Lozupone, J. Hahn, J. B. Adams, and R. Krajmalnik-Brown, “Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders,” Anaerobe, vol. 49, pp. 121–131, Feb. 2018. doi: 10.1016/j.anaerobe.2017.12.007
13.    D. P. Howsmon*, S. Steinmeyer*, R. C. Alaniz, J. Hahn, and A. Jayaraman, “Empirical modeling of t cell activation predicts interplay of host cytokines and bacterial indole,” Biotechnology and Bioengineering, vol. 114, no. 11, pp. 2660–2667, Nov. 2017. doi: 10.1002/bit.26371
12.    F. M. Cameron, T. T. Ly, B. A. Buckingham, D. M. Maahs, G. P. Forlenza, C. J. Levy, D. Lam, P. Clinton, L. H. Messer, E. Westfall, C. Levister, Y. Y. Xie, N. Baysal, D. Howsmon, S. D. Patek, and B. W. Bequette, “Closed-loop control without meal announcement in type 1 diabetes,” Diabetes Technology & Therapeutics, vol. 19, no. 9, pp. 527–532, Aug. 2017. doi: 10.1089/dia.2017.0078
11.    G. P. Forlenza*, S. Deshpande*, T. T. Ly, D. P. Howsmon, F. Cameron, N. Baysal, E. Mauritzen, T. Marcal, L. Towers, B. W. Bequette, L. M. Huyett, J. E. Pinsker, R. Gondhalekar, F. J. Doyle, D. M. Maahs, B. A. Buckingham, and E. Dassau, “Application of zone model predictive control artificial pancreas during extended use of infusion set and sensor: A randomized crossover-controlled home-use trial,” Diabetes Care, p. dc170500, Jun. 2017. doi: 10.2337/dc17-0500
10.    T. Vargason, D. P. Howsmon, D. L. McGuinness, and J. Hahn, “On the use of multivariate methods for analysis of data from biological networks,” Processes, vol. 5, no. 3, p. 36, Jul. 2017. doi: 10.3390/pr5030036
9.    D. P. Howsmon, U. Kruger, S. Melnyk, S. J. James, and J. Hahn, “Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation,” PLoS Computational Biology, vol. 13, no. 3, e1005385, Mar. 2017. doi: 10.1371/journal.pcbi.1005385 JOURNAL COVER
8.    T. Vargason, D. P. Howsmon, S. Melnyk, S. J. James, and J. Hahn, “Mathematical modeling of the methionine cycle and transsulfuration pathway in individuals with autism spectrum disorder,” Journal of Theoretical Biology, vol. 416, pp. 28–37, Mar. 2017. doi: 10.1016/j.jtbi.2016.12.021
7.    D. P. Howsmon, F. Cameron, N. Baysal, T. T. Ly, G. P. Forlenza, D. M. Maahs, B. A. Buckingham, J. Hahn, and B. W. Bequette, “Continuous glucose monitoring enables the detection of losses in infusion set actuation (LISAs),” Sensors, vol. 17, no. 1, p. 161, Jan. 2017. doi: 10.3390/s17010161
6.    J. Adams, D. P. Howsmon, U. Kruger, E. Geis, E. Gehn, V. Fimbres, E. Pollard, J. Mitchell, J. Ingram, R. Hellmers, D. Quig, and J. Hahn, “Significant association of urinary toxic metals and autism-related symptoms – A nonlinear statistical analysis with cross validation,” PLoS ONE, vol. 12, no. 1, e0169526, Jan. 2017. doi: 10.1371/journal.pone.0169526
5.    B. W. Bequette, F. Cameron, N. Baysal, D. Howsmon, B. Buckingham, D. Maahs, and C. Levy, “Algorithms for a single hormone closed-loop artificial pancreas: Challenges pertinent to chemical process operations and control,” Processes, vol. 4, no. 4, p. 39, Oct. 2016. doi: 10.3390/pr4040039
4.    D. P. Howsmon and J. Hahn, “Regularization techniques to overcome over-parameterization of complex biochemical reaction networks,” IEEE Life Sciences Letters, vol. 2, no. 3, pp. 31–34, Sep. 2016. doi: 10.1109/LLS.2016.2646498
3.    D. Howsmon*, J. G. Zheng*, B. Zhang, J. Hahn, D. McGuinness, J. Hendler, and H. Ji, “Entity linking forbiomedical literature,” BMC Medical Informatics and Decision Making, vol. 15, S4, Suppl 1 May 2015. doi: 10.1186/1472-6947-15-S1-S4
2.    D. Howsmon and B. W. Bequette, “Hypo- and hyperglycemic alarms: Devices and algorithms,” Journal of Diabetes Science and Technology, vol. 9, no. 5, pp. 1126–1137, Apr. 2015. doi: 10.1177/1932296815583507
1.    C. Klemashevich, C. Wu, D. Howsmon, R. C. Alaniz, K. Lee, and A. Jayaraman, “Rational identification of diet-derived postbiotics for improving intestinal microbiota function,” Current Opinion in Biotechnology, vol. 26, pp. 85–90, Apr. 2014. doi: 10.1016/j.copbio.2013.10.006