Research

Decoding and Engineering Nanoscale Dynamics in Liquid Environments

Matter in liquid environments is dynamic, heterogeneous, and often far from equilibrium, yet most high-resolution tools are designed to reveal structure and the underlying process that creates it. Our lab is driven by a central question: How can we directly measure, decode, and engineer nanoscale dynamics in complex liquid systems? We study how motion, fluctuations, interactions, and assembly pathways give rise to the behavior and function of nanomaterials, soft matter, and biomolecular systems. We integrate liquid-phase and cryogenic electron microscopy, correlative optical imaging, high-throughput synthesis, stochastic thermodynamics, and physics-informed AI to observe these processes, uncover their governing physical rules, and engineer their outcomes. We also build self-driving labs and thinking microscopes that can design experiments, interpret evolving data, coordinate measurements across instruments, and decide what experiment or measurement should be performed next.

AI-Augmented Electron Microscopy

Liquid-phase TEM produces high-dimensional, noisy data that encode rich dynamic information. We develop:

  • Generative and diffusion-based reconstruction models
  • Physics-informed inverse problem solvers for low-dose imaging
  • AI-guided acquisition and adaptive imaging strategies
  • Agentic AI for automated and closed-loop electron microscopy for discovery and reproducibility

These approaches enable quantitative inference of nanoscale structure and dynamics beyond conventional image analysis.

Diffusion-based reconstruction process visualization

Single-Particle Tracking & Stochastic Dynamics

We develop high-resolution spatiotemporal tracking and trajectory inference methods to quantify nanoscale motion in heterogeneous environments. Our work:

  • Resolves rare events and anomalous diffusion
  • Measures viscoelastic memory and confinement effects
  • Maps nanoparticle-interface interaction landscapes
  • Connects stochastic trajectories to thermodynamic models

This framework bridges nanoscale experiments with statistical mechanics and soft matter physics.

Biomolecular Phase Behavior & Soft Matter

We apply these platforms to investigate:

  • Biomolecular condensates and phase separation
  • Protein conformational fluctuations in liquid environments
  • Nanoparticle-biomolecule interactions
  • Structure–dynamics–function relationships in complex fluids

By combining real-time imaging with mechanistic modeling and AI-enabled inference, we uncover the physical principles governing the dynamics of self-organization.

Self-Driving Laboratories

We build autonomous experimental platforms that combine high-throughput synthesis, in situ characterization, and agentic AI to accelerate materials design and discovery. This includes:

  • Autonomous high-throughput synthesis and screening of nanoparticles (robotic synthesis)
  • Agentic AI for closed-loop experiment planning, execution, and adaptation
  • Transforming microscopes into self-driving labs for autonomous imaging and discovery (thinking microscopes)
  • Multi-resource allocation of samples, instrument time, and characterization measurements

The goal is to create labs and microscopes that do more than automate a fixed workflow by using real-time data to decide what experiment or measurement should come next.

High-throughput nanoparticle synthesis

Watch these videos if you want to hear more about our research:
Link to Vida's talk at NeurIPS, AI for Accelerated Material Discovery Workshop
Link to YouTube video of Vida's talk at Protochips webinar
Link to YouTube video of Vida's talk at Nano@Tech

Team

  • Principle Investigator

    • Vida Jamali (CV)
    Email: vida@gatech.edu

    Vida is an assistant professor of Chemical and Biomolecular Engineering at GeorgiaTech since Aug 2022. She is also a program faculty member of Machine Learning and Bioengineering PhD programs. She is also an affiliated faculty member of the Institute for Matter and Systems (IMS), Institute for Bioengineering and Biosciences (IBB), and Institute for Data Engineering and Sciences (IDEaS). Vida's work has been recognized by the NSF CAREER Award (2024), ACS PRF Doctoral New Investigator Award (2023), and she has been named a Scialog fellow in Automating Chemical Labs (2024), 30 voices of Chemistry of Materials (2023), Beckman Young Investigator Award Finalist (2025), and a rising star in soft and biological matter by the University of Chicago MRSEC (2021). Vida is currently one of the initiative leads of IDEaS for AI in Chemical and Materials Discovery at Georgia Tech. Before joining Georgia Tech, Vida was a postdoctoral researcher at the University of California, Berkeley and Kavli Energy Nanoscience Institute working with Paul Alivisatos where she also collaborated closely with Kranthi Mandadapu. She received her PhD in Chemical and Biomolecular Engineering from Rice University, advised by Matteo Pasquali in 2017. Prior to that, Vida did her BS in Chemical Engineering at Sharif University of Technology in 2011.


  • Graduate Students

    • Zain Shabeeb
    BEng Chemical Engineering, Newcastle University, 2018
    MSc Advanced Process Integration and Design, The University of Manchester, 2019
    Email: zshabeeb3@gatech.edu

    Zain was born and raised in Lahore, Pakistan and lived in Switzerland for four years during middle school. Zain completed his BEng in Chemical Engineering and MSc in Advanced Process Integration and Design from the UK. During his undergraduate studies at Newcastle University, Zain started developing an interest in mathematical modeling and computer programming. For this reason, he pursued a Master’s degree in Process Integration and Design, and in his free time, learned Python programming, Machine Learning and Data Science. Before starting his Ph.D., Zain worked in Fatima Group in Pakistan as a Supply Chain management associate, where he used statistical time-series forecasting methods to forecast the prices of important commodities. Zain is an avid fan of cricket, and in his free time loves to work out, play table tennis and pool.



    Isabel Panicker

    Isabel Panicker
    View full profile
    BS Chemical Engineering, Purdue University, 2023
    Email: ipanicker@gatech.edu

    Isabel was born and raised in Suburban Chicago, Illinois. She earned her Bachelor’s degree in Chemical Engineering from Purdue University in 2023. There, she worked with Dr. Rakesh Agrawal in his Solar Energy Group where her research focused on solution based synthesis of Multinary Sulfides for Photovoltaics. She has also spent time as a Quality Engineering Intern at Tesla working on the continuous improvement of the Drive Unit Manufacturing Line. Isabel joined the Jamali Lab in 2023 and is excited to be working with nanoparticles and studying their non-equilibrium behavior utilizing Liquid TEM. In her free time, she likes watching films, drawing and painting.


    Yuling Zheng
    BEng Biomedical Engineering, Sun Yat-sen University, 2023
    MSc Biomedical Engineering, Johns Hopkins University, 2025
    Email: yzheng601@gatech.edu

    Yuling was born and raised in Zhuhai, Guangdong, China. She earned her Bachelor’s degree in Biomedical Engineering from Sun Yat-sen University, 2023. During her undergraduate study, she worked with Dr. Jun Yue on developing quantum dot probes for bacterial infection diagnosis and treatment. She went on to earn her Master’s degree in Biomedical Engineering from Johns Hopkins University, where she worked with Dr. Honggang Cui, focusing on the fundamental and therapeutic application of supramolecular polymer, especially in self-assembling peptide-drug conjugates. Yuling joined the Jamali Lab in 2025. In her free time, she enjoys playing volleyball, Taekwondo, and Guzheng.

    Tianhua Zhao
    BS Chemistry, University of Southern California, 2026
    Email: tzhao362@gatech.edu

    Tianhua was born and raised in Shanghai, China. Tianhua joined the Jamali lab in Fall 2026. His research interests include machine learning, self-driving laboratories, and material discovery. He received his B.S. in Chemistry from the University of Southern California in 2026, where he worked on polymer synthesis and molecular dopants with Professor Barry Thompson and developed ion-selective membranes with Professor Luis Francisco Villalobos. Before transferring to USC, Tianhua attended Wake Forest University, where he researched chiral organic materials in Professor Cedric Schaack's research group. He also gained industrial research experience at BASF in Shanghai, working on chromium-free polymer coatings for corrosion protection. Outside of research, Tianhua is a huge video game fan and enjoys playing video games and watching movies in his spare time. He also loves traveling and exploring new places through photography.

    Lucy Liu
    BS Chemical and Biomolecular Engineering, University of California, Los Angeles, 2025
    Co-advisors: Amirali Aghazadeh (ECE), Lily Cheung (ChBE)
    Email: lliu449@gatech.edu

    Lucy Ziyi was born and raised in Beijing, China. She earned her B.S. in Chemical Engineering from UCLA in 2025. During her undergraduate studies, she conducted research in Dr. Alexander Spokoyny’s lab, focusing on the functionalization of dodecaborate clusters with fluorocarbon chains. After graduation, she took a gap year and traveled. She joined the Jamali Lab in 2026. Outside the lab, Ziyi enjoys playing piano, hanging out with her cat Bat, and catching up with friends.

  • Undergraduate Students


    • Diya Mahesh
    Email: dmahesh30@gatech.edu


    Diya is a second-year chemical engineering major at Georgia Tech from Chalfont, Pennsylvania. In the Jamali-Lab, she is eager to work with the synthesis and application of protein coacervates. In her free time, she enjoys dancing, working out, and spending time with friends and family.



    Siddarth Sreeram
    Email: ssreeram34@gatech.edu


    Siddarth is a Computer Engineering student at Georgia Tech from Chantilly, Virginia. He joined the lab to develop scientific computational skills in machine learning and artificial intelligence. Outside of school, he enjoys playing table tennis and listening to music.




    Riya Patel
    Email: rpatel806@gatech.edu


    Riya is a third-year Chemical and Biomolecular Engineering student at Georgia Tech from Newnan, Georgia. Her work in Jamali Lab focuses on high-throughput synthesis and characterization of nanoparticles. Outside of school, she enjoys playing volleyball, cooking, running, and spending time with her friends and family.




    Gabriela Briceno
    Email: gbriceno7@gatech.edu


    Gaby is a third-year Materials Science and Engineering major at Georgia Tech from Suwanee, GA. She joined the Jamali Lab to explore her interest in how chemistry, soft matter, and advanced imaging can be used to understand dynamic processes in liquid environments. In her free time, she enjoys figure skating, trying new coffee shops, and going on runs.



    Nate Glanzmann
    Email: nglanzmann3@gatech.edu


    Nathaniel is a third-year Chemical and Bimolecular Engineering at Georgia Tech from Hatboro, Pennsylvania. His work focuses on creating self-driving laboratories for nanoparticle experiments. Outside of school, he enjoys playing volleyball, baking, trying new restaurants, and hanging out with friends.



    Benjamin Brough
    Email: bbrough6@gatech.edu


    Ben is a third year Chemical and Biomolecular Engineering student at Georgia Tech from Spartanburg, South Carolina. His work in Jamali Lab focuses on high-throughput synthesis and characterization of nanoparticles. Outside of school, he enjoys going to the gym, playing chess, running, hiking, and spending time with friends and family.



    Caroline Tzur
    Email: ctzur3@gatech.edu


    Caroline is a third-year Chemical and Biomolecular Engineering student from Kenilworth, IL. She joined the Jamali lab to learn how AI may be used to automate nanoparticle characterization and synthesis. In her free time, she enjoys yoga, trying new restaurants, and reading mystery books.



    Neha Muralitharan
    Email: nmuralitharan3@gatech.edu


    Neha is a first-year Chemical and Biomolecular Engineering student at Georgia Tech from Chantilly, Virginia. Her work in the Jamali Lab focuses on high-throughput synthesis and characterization of nanoparticles. Outside of school, she enjoys playing pickleball, making coffee, watching movies, and spending time with her friends and family.



    Sardhak Boddu
    Email: sboddu37@gatech.edu


    Sardhak is a first-year Chemical and Biomolecular Engineering student at Georgia Tech from Alpharetta, Georgia. Within the Jamali Lab, he is excited to work with AI augmented electron microscopy and nanoparticle dynamics in soft matter environments. Outside of school, he enjoys playing soccer, reading, hiking, and spending time with his friends.



    Milan Barnes
    Email: mbarnes73@gatech.edu


    Milan is a second-year chemical engineering major at Georgia Tech from Smyrna, Georgia. She is passionate about mental health advocacy, values spending time with friends and family, and enjoys listening to music and baking. In the Jamali Lab, she is excited to contribute to synthesizing nanoparticles through chemical reactions and processes.



  • Group Alumni
    • Mahika Raj (2026), CS undergrad, Current Position:MS CS at Georgia Tech
    Anika Patel (2025-2026), CS undergrad, Current Position:MS CS at Georgia Tech
    Lauren Caldwell (2024-2026), CHBE undergrad, Current Position: Eli Lily
    Isabella Faciano (2024-2025), CHBE undergrad, Current Position: General Mills
    Madison Tat (2025), CHBE undergrad
    Max Xu (2025), CS undergrad, Current Position: Northwestern CS
    Alexander Wang (2025-2026), CS undergrad
    Risha Goel (2024-2025), CHBE undergrad, Current Position: PhD student at the University of Minnesota
    Cecilia Reed (2024-2025), CHBE undergrad, Current Position: Johnson & Johnson
    Laurence Lines (2024-2025), CHBE undergrad
    Matthew Abernathy (2024), CHBE undergrad
    Naisargi Goyal (2022-2024), CHBE undergrad, Current Position: PhD student at Princeton
    Gabriel Joaquim Sampaio De Almeida (2023), CHBE undergrad
    Arko Roy (2023), CHBE undergrad

    Want to join our team?

    Prospective graduate students should apply directly to the School of Chemical and Biomolecular Engineering at Georgia Tech, and Interdisciplinary Bioengineering and Machine Learning PhD programs . We always look for motivated students interested in areas including electron microscopy and machine learning/AI/agentic AI for science. Admitted graduate students, please email Vida directly to schedule a meeting to chat.


    Undergraduate students interested in a research position, please fill out this application form: https://forms.gle/dyeFPu4yERx9EHCo9 . For Fall 2026 we are particularly looking for undergrads interested in robotics and hands-on work to help build and operate automated synthesis platforms.

    Publications

    * denotes equal contribution, † denotes corresponding author

    • Multimodal LLM-Assisted Diagnosis of Cryptic Failure Modes in High-Throughput Experimentation: A Case Study in Gold Nanorod
      Synthesis, Riya Patel, Gabriela Briceno, Amirali Aghazadeh, Vida Jamali†, ChemrXiv (2026).

    • Polarity-Resolved Imaging Reveals Active Transport in Catalytic Janus Nanomotors,
      Isabel Panicker, Katherinne Requejo Roque, Ricardo Ruiz, Assaf Ben-Moshe, Carlos Bustamante, A. Paul Alivisatos, Vida Jamali†, ChemrXiv (2026).

    • SAM-EM: Segment Anything for Liquid Phase Electron Microscopy Video Segmentation,
      Zain Shabeeb*, Siddarth Sreeram*, Isabel Panicker, Alexander Wang, Max Xu, Risha Goel, Vida Jamali†, Digital Discovery (2026). website: https://jamalilab.github.io/SAM-EM/

    • Generative Priors for Cryo-EM Image Reconstruction,
      Zain Shabeeb*, Daniel Saeedi*, Darin Tsui*, Vida Jamali†, Amirali Aghazadeh†, ICML Workshop on Generative and Agentic AI for Biology (2026).

    • Modulating Nanoparticle-Surface Interactions at Liquid-Solid Interfaces via Ion Screening in Liquid-Phase TEM,
      Isabel Panicker, Zain Shabeeb, Cory Hargus, Vida Jamali†,       ACS Nano, 20, 21, 15550 (2026). (Featured on Front Cover).

    • Thinking microscopes: agentic AI and the future of electron microscopy,
      Vida Jamali†, Amirali Aghazadeh†, Josh Kacher, npj Computational Materials. (2026), 12, 149.

    • cryoSENSE: Compressive Sensing Enables High-throughput Microscopy with Sparse and Generative Priors on the Protein Cryo-EM Image Manifold,
      Zain Shabeeb*, Daniel Saeedi*, Darin Tsui*, Vida Jamali†, Amirali Aghazadeh†, IEEE/CVF, Computer Vision and Pattern Recognition (CVPR). website: https://cryosense.github.io

    • Quantifying Photochemical Propulsion in Light-powered Janus Micromotors,
      Katherinne Requejo Roque, Cristhian Cañari Chumpitaz, Vida Jamali, Ricardo Ruiz, A Paul Alivisatos, Carlos Bustamante, ACS Nano, 20, 19, 14099 (2026).

    • Tumor Agnostic Drug Delivery with Dynamic Nanohydrogels,
      Stephen N. Housley, Alisyn R. Bourque, Lilya V. Matyunina, Isabel A. Panicker, Elisa Schrader Echeverri, Marrissa Izykowicz, Olivia A. Herrmann, Sebinne Lee, Johana C. Arboleda , Vida Jamali, John F. McDonald, James E. Dahlman, and M.G. Finn, Nature Communications, (2026), 17, 184,

    • Learning the Diffusion of Nanoparticles in Liquid Phase TEM via a Physics-informed Generative AI,
      Zain Shabeeb, Naisargi Goyal, Pagnaa Attah Nantogmah, Vida Jamali†, Nature Communications, (2025). website: https://jamalilab.github.io/LEONARDO/

    • LEONARDO: A Physics-Informed Generative Model for Stochastic Nanoparticle Dynamics in Liquid-Phase TEM,
      Zain Shabeeb, Vida Jamali†, Neural Information Processing Systems Conference, AI for Science workshop (2025).

    • SAM-EM: Real-Time Segmentation for Automated Liquid Phase Transmission Electron Microscopy,
      Alexander Wang, Max Xu, Risha Goel, Zain Shabeeb, Isabel Panicker, Vida Jamali†, Neural Information Processing Systems Conference, AI for Accelerated Material Design (AI4MAT) workshop (2025).

    • Learning the Physics of Liquid Phase TEM Nanoparticle Trajectories Using Physics-Informed Generative AI .
      Zain Shabeeb, Naisargi Goyal, Pagnaa Attah Nantogmah, Vida Jamali†, Microscopy and Microanalysis, (2024), 30, S1, 1724 .

    • Determining Diffusion Characteristics of Nanoparticles in Liquid Phase TEM Using Deep Learning .
      Zain Shabeeb, Naisargi Goyal, Vida Jamali†, Microscopy and Microanalysis, (2024), 30, S1, 2074 .

    • Studying diffusion of colloidal nanoparticles in solution using liquid phase TEM and machine learning .
      Vida Jamali†, A. Paul Alivisatos†, Microscopy and Microanalysis, (2022), 28, S1 .

    • Observation of an orientational glass in a superlattice of elliptically-faceted CdSe nanocrystals .
      Abdullah S. Abbas, Emma Vargo, Vida Jamali, Peter Ercius, Priscilla F. Pieters, Rafaela M. Brinn, Assaf Ben-Moshe, Min Gee Cho, Ting Xu, A. Paul Alivisatos, ACS Nano, (2022), 16, 6 .

    • Recent advances in the study of colloidal nanocrystals enabled by in situ liquid phase transmission electron microscopy .
      Ivan Moreno-Hernandez*, Michelle Crook*, Vida Jamali*, A. Paul Alivisatos, MRS Bulletin, (2022), 47 .

    • Anomalous nanoparticle surface diffusion in liquid cell TEM is revealed by deep learning-assisted analysis .
      Vida Jamali, Cory Hargus, Assaf Ben Moshe, Amirali Aghazadeh, Hyun D. Ha, Kranthi K. Mandadapu, A. Paul Alivisatos, PNAS, (2021), 18, 10 .

    • Enhanced ordering in length-polydisperse carbon nanotube solutions at high concentrations as revealed by small angle X-ray scattering.
      Vida Jamali, Francesca Mirri, Evan G. Biggers, Robert Pinnick, Lucy Liberman, Yachin Cohen, Yeshayahu Talmon, Fred C. MacKintosh, Paul van der Schoot, Matteo Pasquali , Soft Matter, (2021), 17, 5122-5130 (Featured on the front cover of Soft Matter).

    • In situ quantification of interactions between charged nanorods in a predefined potential energy landscape.
      Hoduk Cho, Ivan A. Moreno-Hernanzdez, Vida Jamali, Myoung H. Oh, A. Paul Alivisatos, Nano Letters, (2021), 21, 1, 628-633 .

    • Perovskite-carbon nanotube fibers for light emitting fibers.
      Vida Jamali*, Farnaz Niroui*, Lauren W. Taylor, Oliver S. Dewey, Brent A. Koscher, Matteo Pasquali, A. Paul Alivisatos, Nano Letters, (2020), 20, 5, 3178-3184.

    • The effect of carbon nanotube diameter and stiffness on their phase behavior in crowded solutions.
      Lucy Liberman, Vida Jamali, Matteo Pasquali, Yeshayahu Talmon, Langmuir, (2020), 36, 242-249 .

    • Fluid phase ordering of charge-stabilized carbon nanotube solutions.
      Francesca Mirri*, Rana Ashkar*, Vida Jamali, Lucy Liberman, Robert A Pinnick, Paul van der Schoot, Yeshayahu Talmon, Paul D Butler, Matteo Pasquali, Macromolecules, (2018), 51, 17, 6892-6900.

    • Flexible and conductive fibers made from highly concentrated aqueous dispersions of carbon nanotubes.
      Laurent Maillaud, Robert J. Headrick, Vida Jamali, Julien Maillaud, Dmitri E. Tsentalovich, Wilfrid Neri, E. Amram Bengio, Francesca Mirri, Olga Kleinerman, , Yeshayahu Talmon, Philippe Poulin, Matteo Pasquali, Industrial and Engineering Chemistry Research, (2018), 57, 10, 3554-3560.

    • Purification and dissolution of carbon nanotube fibers spun from the floating catalyst method.
      Thang Q Tran, Robert J Headrick, E Amram Bengio, Sandar Myo Myint, Hamed Khoshnevis, Vida Jamali, Hai M Duong, Matteo Pasquali, ACS applied materials & interfaces, (2017), 9, 42, 37112-37119.

    • Line tension of twist-free nematic liquid crystal microdroplets on flat solid surfaces.
      Vida Jamali, Evan G Biggers, Paul van der Schoot, Matteo Pasquali, Langmuir (2017), 33, 36, 9115-9121.

    • Increased solubility and fiber spinning of graphenide dispersions aided by crown-ethers.
      Chengmin Jiang, Zhiwei Peng, Carlos de los Reyes, Colin C Young, Dmitri E Tsentalovich, Vida Jamali, Pulickel M Ajayan, James M Tour, Matteo Pasquali, Angel A Martí. Chemical Communications, (2017), 53(9), 1498-1501.

    • Experimental realization of crossover in shape and director field of nematic tactoids.
      Vida Jamali*, Natnael Behabtu*, Bohdan Senyuk, J Alex Lee, Ivan I Smalyukh, Paul van der Schoot, Matteo Pasquali, Physical Review E, (2015) 91,4, 042507.

    News

  • Sep 2026- Vida will be giving an invited talk on anomalous diffusion in LPTEM in Venice meeting on Fluctuations in small complex systems VIII.
  • Sep 2026- Welcome to the new undergrads in the group: Nate, Caroline, Ben, Neha, and Sardhak!
  • Sep 2026- Our new manuscript on Polarity-resolved imaging of active Janus nanomotors is now on ChemRxiv.
  • Jul 2026- Our SAM-EM paper is now published in Digital Discovery.
  • Jul 2026- We are awarded a grant from Foresight Institute to work on AI for molecular nanotechnology.
  • Jul 2026- Vida was selected as a 2026 Scialog awardee in automating chemical labs to develop agentic AI to coordinate multimodal instruments in autonomous materials discovery
  • May 2026- Our new active matter paper in collaboration with UC Berkeley and UChicago is published in ACS Nano.
  • Apr 2026- Isabel's work on modulating nanoparticle surface interactions in LPTEM is now accepted in ACS Nano.
  • Apr 2026- Vida will be at the AUT Scialog Meeting.
  • Apr 2026- Our new comment article in Thinking Microscopes that uses agentic AI to design and control experiments is now published in npj Computational Materials.
  • Mar 2026- Zain and Isabel will be giving several talks at the ACS Spring Meeting!
  • Feb 2026- Congratulations to Isabel for winning the GT ChBE Eckert fellowship!
  • Jan 2026- Vida and Isabel will be at the GRS/GRC on LPTEM in Ventura, CA!
  • Dec 2025- The Jamali Lab is heading to NeurIPS in San Diego, CA! Join us for our RSF talk at AI4Mat and check out our poster at the AI for Science sessions.
  • Dec 2025- Vida will be giving a talk at UCSB ChemE departmental seminar.
  • Nov 2025- Our cryoSENSE preprint and software is out, check out the website!
  • Sep 2025- Our LEONARDO paper is accepted in the Neurips AI for Science 2025 workshop!
  • Sep 2025- Our SAM-EM paper is accepted in the Neurips AI for Accelerated Material Design 2025 workshop!
  • Sep 2025- Jamali Lab welcomes Yuling Zheng, a new BioE PhD student! Welcome to the team Yuling!
  • Aug 2025- Jamali Lab welcomes the new undergrad researcher, Siddarth!
  • Jul 2025- Our new preprint on the origin of viscoelasticity of surface diffusion of NPs in LPTEM is on ChemRxiv.
  • Jul 2025- Check out the news covering our recent work.
  • Jul 2025- Our paper on physics-informed gen AI for modeling diffusion of NPs in LPTEM is out in Nature Communications
  • Jun 2025- Vida will be presenting a talk on AI for LPTEM at the ACS Colloid and Science Symposium in Edmonton, AB.
  • May 2025- Our group will be at the Soft Matter Day at Emory.
  • May 2025- Jamali Lab welcomes three new undergrads joining the group: Madison, Alexander, and Max!
  • Apr 2025- Congratulations to Isabel for receiving the NSF GRFP honorable mention.
  • Apr 2025- Vida will be presenting an invited talk on the role of AI in advancing in situ liquid phase transmission electron microscopy at the MRS Spring meeting in Seattle, WA on Apr 9th.
  • Mar 2025- The Jamali lab team is participating in the Atlanta Science Festival to showcase their research for the public
  • Mar 2025- Vida will be presenting a talk on physics-informed generative models of single particle trajectories at APS March meeting in Anaheim, CA on Thursday Mar 20th.
  • Jan 2025- Congrats to Zain for winning the School of CHBE's Eckert fellowship.
  • Dec 2024- Our new software for multiple particle tracking and analysis in in situ TEM, SAM4EM, is now on github. Checkout the preprint.
  • Dec 2024- Congrats to Risha for winning the Presidential Undergraduate Research Award (PURA).
  • Oct 2024- Vida will be presenting a talk at AIChE Fall meeting in San Diego, CA.
  • Aug 2024- Jamali Lab will have an open house for the new class of graduate students on Thursday Aug 29th, 10 am-noon in ES&T 1229.
  • Aug 2024- Jamali Lab welcomes five new undergrads joining the group: Risha, Lauren, Matthew, Isabella, and Laurence!
  • Jul 2024- Zain will be presenting two posters at the upcoming M&M conference.
  • Jun 2024- Our lab will be at the ACS colloid and surface science symposium in Seattle, WA.
  • May 2024- Congratulations to Zain for passing his thesis proposal!
  • April 2024- Vida will be at the Scialog Conference on AI for Automating Chemical Labs.
  • April 2024- We will be hosting the Soft Matter Day Symposium for the Atlanta Area at Georgia Tech on April 5th in EBB Krone building.
  • Mar 2024- Vida will be giving a seminar at the Institute for Electronics and Nanotechnology (IEN) at Georgia Tech on 26th.
  • Mar 2024- Vida will be at APS to talk about our recent advancements in developing LPTEM as a single particle tracking method.
  • Jan 2024- We are awarded the NSF CAREER Award!
  • Jan 2023- Congratulations to Isabel for passing her qual!
  • Jan 2024- We are awarded the Institute for Electronics and Nanotechnology, IEN-1000x seed grant to develop a high resolution acquisition technique in collaboration with our ECE colleague Amirali Aghazadeh ( Amir group ).
  • Nov 2023- We are awarded the ACS PRF Doctoral New Investigator Award!
  • Oct 2023- Vida, Victor Fung, Pan Li, and Amirali Aghazadeh were awarded a seed grant to establish a new initiative at Georgia Tech on AI for Chemical and Materials Discovery. The seed grant is co-sponsored by the Institute for Data Engineering and Sciences and Institute for Materials.
  • Oct 2023- Vida was named one of the Scialog fellows in Automating Chemical Labs. She will participate in the first meeting of AUT meeting series in April 2024.
  • Oct 2023- Congratulations to Naisargi for winning the GT-AIChE chapter travel award which will sponsor her travel to AIChE fall meeting this year. She will be presenting her work on ML for electron microscopy.
  • Oct 2023- Isabel Panicker, first-year PhD student in CHBE joined Jamali Lab. Welcome Isabel!
  • Sep 2023- Vida will be presenting an invited talk at the International Microscopy Congress (IMC20) in Busan, Korea on applications of deep learning in LPTEM.
  • Jul 2023- Congratulations to Naisargi for winning the President's Undergraduate Research Award (PURA). We look forward to continuing working with her in Fall 2023.
  • Mar 2023- Vida will be speaking at the 2023 Symposium on Materials Innovation hosted by the Institute for Materials at Georgia Tech on March 31st, 2023.
  • Mar 2023- Vida will be the next seminar speaker of CCMST seminar series at Georgia Tech on Mar 14th to talk about deep learning and its application in LPTEM.
  • Mar 2023- Congratulations to Naisargi for being selected as the student rep of the GT-AICHE Chapter in 2023 AIChE Southeastern Regional Conference! she will present a poster on her research in our group.
  • Jan 2023- Congratulations to Zain for passing his qual!
  • Oct 2022- Vida will be giving an invited talk at the liquid phase TEM Gordon Research Conference in Ventura, CA.
  • Oct 2022- Jamali group welcomes new team members Zain and Naisargi.
  • Aug 2022- Vida will be giving an invited talk at the Microscopy and Microanalysis conference in Portland, OR in August.
  • May 2022- Vida will be joining the school of Chemical and Biomolecular Engineering at GeorgiaTech in Fall 2022. Our lab will integrate electron microscopy, statistical mechanics, and machine learning to investigate the dynamics of soft material systems at the nanoscale.
  • May 2022- Our paper on observation of orientational glass phase in superlattices of elliptically faceted nanocrystals is now published in ACS Nano.
  • Dec 2021- Vida will be presenting a talk on my recent works at the Kavli Energy Nanoscience Institute at UC Berkeley on Tuesday December 7th.
  • Nov 2021- Vida will be presenting a talk on my recent works on liquid phase TEM and anomalous diffusion at the AIChE conference in Boston, MA on Monday November 8th, 5:15 pm (203h).
  • Sep 2021- Vida has been selected as a Rising Star in Soft and Biological Matter by the University of Chicago MRSEC. I will present a summary of my research on Sep. 23rd in this symposium.
  • Sep 2021- Vida will be giving a talk in the Nano Seminar series at UC Berkeley on September 10, 2021.
  • May 2021- Our paper is featured on the front cover of the Soft Matter journal
  • March 2021- Our paper on deep learning-assisted study of nanoparticles' surface diffusion in liquid cell TEM is accepted to PNAS
  • March 2021- Our paper on studying high concentration solutions of carbon nanotubes using small angle X-ray scattering is accepted to Soft Matter
  • January 2021- Vida was awarded the Berkeley Postdoctoral Association Professional Development award
  • December 2020- Our paper on in-situ lift off of lithographed nanorods in liquid cell TEM is accepted to Nano Letters
  • November 2020- Vida will be giving a talk on using deep neural networks for studying anomalous surface diffusion of nanoparticles in liquid cell TEM at the AIChE fall meeting. The talk is publicly available on Youtube
  • October 2020- Vida was awarded the Women in Chemical Engineering (WIC) travel award to attend the AIChE fall meeting this November
  • September 2020- Vida was spotlighted by the UC Berkeley VSPA office in the national postdoctoral appreciation week
  • September 2020- Our new paper on deep-learning assisted liquid cell TEM is now available on ChemRxiv
  • July 2020- Alivisatos and Mandadapu's group are awarded a NSF EAGER grant to work on the surface diffusion of nanoparticles using in-situ liquid cell TEM
  • April 2020- Our paper on perovskite-carbon nanotube light emitting fibers is published in Nano Letters
  • November 2019- Vida will be presenting my work on light emitting fibers at the AIChE fall meeting, Orlando, FL
  • August 2019- Vida is selected as a participant in NSF-funded Future Faculty Workshop that will be held at Princeton University, NJ.
  • July 2019- Vida is selected to participate in ACS postdoc to faculty (P2F) workshop in Atlanta, GA

    • Resources

    Career Development

  • You and your research by Richard Hamming
  • Advice by Andrea Armani for applying to PhD program and faculty position
  • Rising stars in soft and biological matter workshop by the University of Chicago MRSEC
  • NextProf Nexus by GeorgiaTech, UC Berkeley, and University of Michigan
  • How to give a talk by Borroughs Wellcome Fund
  • Scholarships for Women in STEM

    • Research Fellowships

    teaching

    CHBE 4803/8803: AI for Experimental Chemical Engineers (Spring 2025, next: Fall 2026)

    Course Description: This course has two primary objectives: (a) to introduce students to advanced deep learning and AI methods and (b) to teach students how to use such models on experimental data relevant to chemical engineers. This course links the topics of AI and data science to experimental chemical engineering applications. Chemical engineers work with experimental data of various modalities that span microscopy images, time series data, spectrophotometry data, and texts, to name a few. This course will first introduce students to the foundations of popular AI models developed in the last 10 years and their application in analyzing experimental data. In addition to covering various model architectures (e.g., CNN, VAE, LLM, etc.), we will cover foundational topics related to AI, including framing loss function, initialization, error backpropagation, gradient computation, and model fitting. The course will maintain a balance between neural network basics and application to experimental data at hand, such that the students obtain key knowledge on how to efficiently select the most suitable AI model and apply it to the data, know the mathematical principles of the model operation, test the model performance, and relevant statistical analysis. Overall, by the end of the course, the students will have a good understanding of how to apply AI models to experimental data relevant to chemical engineers and extract useful information.

    Tentative Syllabus

    CHBE 3205: Fluid Mechanics (Spring 2024, Fall 2024, Fall 2025, next: Spring 2026)

    Course Description: This course introduces the fundamental concepts of momentum transfer as well as their use in typical engineering applications. Special emphasis is put on analogies between the balance equations of fluid flow, on dimensional analysis, and on the prediction of friction losses. Applications include the analysis and design of flow models, piping networks, and packed and fluidized beds.



    CHBE 3200: Transport Phenomena (Fall 2022, Fall 2023)

    Course Description: This course introduces the fundamental concepts of momentum and heat transfer as well as their use in typical engineering applications. Special emphasis is put on analogies between the balance equations of fluid flow and heat flow, on dimensional analysis, and the prediction of friction losses. Applications include the analysis and design of flow models, piping networks, packed and fluidized beds as well as insulation and heat transfer devices.