soha hassoun

Professor

Computer Science (primary)
Chemical & Biological Engineering
Electrical & Computer Engineering
Tufts University

Info

bio
vita

Teaching

COMP166
Computational Systems
Biology


EN1
Computational
Modeling and Design


Contact Info

177 College Ave
Medford, MA 02155
soha (at) cs.tufts.edu
Follow @sohahassoun

Office Hours

See class-specific office hours

Hassoun Lab

Machine Learning + Systems Biology

about     publications     members     collaborating labs     service

Members

image credit: https://sammykatta.com/diversity
PhD Students
  • Apurva Kalia
  • Vlad Porokhin
  • Margaret Martin
  • Frederick Zhang
  • Yan Zhou Chen
  • Yinkai Wang

Current MS/BS Students
  • Haneen Abderrazzaq
  • Vickie Liu
  • Jyoti Bhardwaj
  • Leo Kaluzhny

Those who have moved on - PhDs, and last known whereabouts!
  • Xinmeng Li (Computer Science) -Developing Machine Learning Models with Heterogeneous Data for Biological Engineering Applications, May 2022, Montai, Cambridge
  • Sara Amin (Computer Science) - Advancing the Prediction of Unexpected Cellular Behavior Due to Enzyme Promiscuity and Enzyme Solubility, May 2019, Amazon
  • Neda Hassanpour (Computer Science) - Computational Methods to Advance Directed Evolution of Enzymes and Metabolomics Data Analysis, May 2018, Takadata, Cambridge, MA
  • Mona Yousofshahi (Computer Science) - Computational Methods for Pathway Synthesis and Strain Optimization, December 2014, Apple, CA
  • Ehsan Ullah (Computer Science) - Pathway Analysis of Metabolic Networks Using Graph Theoretical Approaches, August 2014, Researcher, Qatar Computing Research Institute, Qatar
  • Brad Gaynor (Electrical and Computer Engineering) - Simulation of FinFET Electrical Performance Dependence on Fin Shape and TSV and Back-Gate Noise Coupling in 3-D Integrated Circuits, May 2014, STR (Systems & Technology Research)
  • Gautham Sridharan (Chemical and Biological Engineering) (Co-advised with Kyongbum Lee) - Modularity Analysis of Metabolic Networks Based on Shortest Retroactive Distances (ShReD), May 2013, Alnylam, Cambridge, MA
  • Nauman Khan (Computer Science), Noise Analysis and Power Grids for 3D ICs, August 2011, Intel, OR
  • Brian Swahn (Electrical and Copmuter Engineering), CAD for FinFETs, August 2006, Analog Devices

Completed Masters Project or Credit, and last known whereabouts!
  • Ramtin Hosseini (Inference for metabolomics), Fall 2018-Fall 2019
  • Alex Tong (Inference for metabolomics), Spring 2017, Yale, grad school
  • Doug Weaver (Modularity analysis), Fall 2009
  • Jesse Craig (Simulation and Modeling of Neuro-Mechanical Control in Soft Material), back to IBM, Fall 2008
  • Jinhai Qiu (Delay Estimation) Master's, August 2007, at Synopsys
  • Meera Thiagarajan (regularity extraciton, timing analysis) Master's, Dec. 2002; Sr. Manager Corporate Applications at Synopsys
  • Julie Hernandez (architectural synthesis), Master's, May 2002.
  • Jiong Xie (functional customization), Master's, May 2002, at Mathworks.
  • Eduardo Calvillo G├ímez (timing analysis), Master's, May 2001
  • Basil Darwish (network processors), Master's, May 2001, MBA at Wharton
  • Christophe Cromer (timing analysis, network processors), Master's, May 2001, MBA at Wharton
  • Grace Nam (regularity extraction), Master's, May 1999.

Completed Undergraduate Projects, graduation year, and last known whereabouts!
  • Elizabeth Cucuzzella -- Data processing of BRENDA data
  • Kamil Krukowski - Machine learning for protein-molecule interaction
  • Jacob Bryan - Novel metabolic reactions for promsicous products in E. coli; REU student finishing up undergrad at UC Berekely
  • Lexi Shewchuk - Predicting Enzyme Function and Similarity Based on Fingerprints
  • Aayushma Gautam - Machine Learning to Characterize Metabolic Pathway Activities
  • Gian Marco Visani - Enzyme Classification on Molecules, May 2021, PhD at UW! Go Huskies!
  • Olivia Gillma- Using PROXIMAL to predict metabolic products of durgs, May 2023
  • Nick Sokol - Using PROXIMAL to predict metabolic products of durgs, May 2023
  • Michael Simpson - biotransformation considering chirality, May 2023
  • Tina Ma - biotransformation considering chirality, May 2023
  • Tom McNulty- perBRENDA: a tool for extracting BRENDA data in a format suitable for machine learning, May 2024
  • Caroline Vanderlee - A web interface for PROXIMAL, May 2022
  • Julie Jiang - Using Graph Embedding to Predict Enzyme Prmiscuity, May 2019, PhD at USC
  • Nicole Kennedy - Computing Chemical Derivatives, May 2020
  • Jeremy Marcus (thesis) - Mining for Functional Abortives in E. coli, May 2016
    Draper Labs; UC Berkeley
  • Andrew Li - GPU programming, May 2014, Tufts Medical School
  • Russell Stern - Model and Constraint Checking for Biochemical Networks, May 2013
  • Steven Halstead - Sytems Bio project, May 2012
  • Calvin Hopkins (thesis) - Analysis of Metabolic Pathways; Kinetic Function Estimation, May 2012 (Microsoft)
  • Sean Kelly -- Generalized Kinetic Expression Estimation, May 2012
  • Richard Mondello - Modularity Algorithms for Biochemical networks, May 2012 (Apple)
  • Marshal Moutenot - Modularity Algorithms for Biochemical networks
  • Stephen Bidwell - Modularity Algorithms for Biochemical networks
  • Michelle Ichinco - random walk for biochemical networks
  • Shilpa Nadimpalli, BS, May 2011
  • Neha Uppal, BA Child Development, May 2009
  • Laurent Lanster, BA Art History, May 2010
  • Brandon Lucia, BS, May 2007; Phd at UW; Now Prof at CMU
  • Nick Foti, BS, May 2007; PhD at Dartmouth
  • Eli Marschner, BS, May 2007
  • Alana Fu, BS, May 2003
  • Laura Weyland, VLSI Design Project, BS, May 2003
  • Lisa Lafleur, BS, May 2002, Post Doc at UW

REU Students
  • Nikki Rejai, UCSD, Summer 2022)
  • Jacob Bryan, Summer 2019
  • Elizabeth Chavez, UNC, Summer 2018
  • Emily Chicklis, Simmons, Summer 2017