Web cookies (also called HTTP cookies, browser cookies, or simply cookies) are small pieces of data that websites store on your device (computer, phone, etc.) through your web browser. They are used to remember information about you and your interactions with the site.
Purpose of Cookies:
Session Management:
Keeping you logged in
Remembering items in a shopping cart
Saving language or theme preferences
Personalization:
Tailoring content or ads based on your previous activity
Tracking & Analytics:
Monitoring browsing behavior for analytics or marketing purposes
Types of Cookies:
Session Cookies:
Temporary; deleted when you close your browser
Used for things like keeping you logged in during a single session
Persistent Cookies:
Stored on your device until they expire or are manually deleted
Used for remembering login credentials, settings, etc.
First-Party Cookies:
Set by the website you're visiting directly
Third-Party Cookies:
Set by other domains (usually advertisers) embedded in the website
Commonly used for tracking across multiple sites
Authentication cookies are a special type of web cookie used to identify and verify a user after they log in to a website or web application.
What They Do:
Once you log in to a site, the server creates an authentication cookie and sends it to your browser. This cookie:
Proves to the website that you're logged in
Prevents you from having to log in again on every page you visit
Can persist across sessions if you select "Remember me"
What's Inside an Authentication Cookie?
Typically, it contains:
A unique session ID (not your actual password)
Optional metadata (e.g., expiration time, security flags)
Analytics cookies are cookies used to collect data about how visitors interact with a website. Their primary purpose is to help website owners understand and improve user experience by analyzing things like:
How users navigate the site
Which pages are most/least visited
How long users stay on each page
What device, browser, or location the user is from
What They Track:
Some examples of data analytics cookies may collect:
Page views and time spent on pages
Click paths (how users move from page to page)
Bounce rate (users who leave without interacting)
User demographics (location, language, device)
Referring websites (how users arrived at the site)
Here’s how you can disable cookies in common browsers:
1. Google Chrome
Open Chrome and click the three vertical dots in the top-right corner.
Go to Settings > Privacy and security > Cookies and other site data.
Choose your preferred option:
Block all cookies (not recommended, can break most websites).
Block third-party cookies (can block ads and tracking cookies).
2. Mozilla Firefox
Open Firefox and click the three horizontal lines in the top-right corner.
Go to Settings > Privacy & Security.
Under the Enhanced Tracking Protection section, choose Strict to block most cookies or Custom to manually choose which cookies to block.
3. Safari
Open Safari and click Safari in the top-left corner of the screen.
Go to Preferences > Privacy.
Check Block all cookies to stop all cookies, or select options to block third-party cookies.
4. Microsoft Edge
Open Edge and click the three horizontal dots in the top-right corner.
Go to Settings > Privacy, search, and services > Cookies and site permissions.
Select your cookie settings from there, including blocking all cookies or blocking third-party cookies.
5. On Mobile (iOS/Android)
For Safari on iOS: Go to Settings > Safari > Privacy & Security > Block All Cookies.
For Chrome on Android: Open the app, tap the three dots, go to Settings > Privacy and security > Cookies.
Be Aware:
Disabling cookies can make your online experience more difficult. Some websites may not load properly, or you may be logged out frequently. Also, certain features may not work as expected.
Connecticut Research Foundation: Experiments & Simulations to Characterize Tablet Coating Process, Jun 2007 to May 2009.
NSF-Center of Pharmaceutical Processing Research: Numerical Modeling, Optimization and Scale-up of Pharmaceutical Milling in a Hammer mill, Jan 2010 to Dec 2011.
Connecticut Research Foundation: Experimentally validated numerical modeling of electrostatic effects in granular media, Jan 2010 to Dec 2010
University of Connecticut: Travel Grant, July 2009
NSF-Center for Pharmaceutical Processing and Research/Pfizer Inc.: Quantifying Drying Performance of a Filter Dryer, Experiments, and Simulation, July 2008 to Dec 2010
University of Connecticut: Travel Grant 2010
Boehringer Ingelhiem Pharmaceutical Inc. (BIPI): Computer Modeling of Pharmaceutical Manufacturing Processes, Jan 2011 – Dec 2011
PhRMA Foundation Starter Grant: Experimentally validated Modeling, Optimization, and Scale-up of High Shear Wet Granulation Process, Jan 2011 to May 2012
Boehringer Ingelhiem Pharmaceutical Inc.(BIPI): Pharmaceutical Powder Modeling and Technology, Jan 2012 – Dec 2012
US-Food and Drug Administration (FDA-NIPTE): Modeling of Aerodynamic Flow through MDI Spacer (VHC) and Characterization of Aerodynamic Particle Size Distribution using alternate methods, March 2012 to July 2013
Pfizer Inc.: Investigation of Electrostatic Behavior of Pharmaceutical Formulations, Sept 2012 to Aug 2014
Physical Sciences Incorporated (PSI) (subcontract from Phase 1 SBIR Grant from NIH): Organic Solvent Vapor Mass Flow Rate Monitor for Pharmaceutical Drying Operations, Sept 2012 to Aug 2013
NSF-Center for Pharmaceutical Processing and Research/AstraZeneca: Investigation of Mixing and Segregation in Dry Powder Inhaler (DPI) Formulations, March 2013 to February 2015
US-Food and Drug Administration (FDA-NIPTE): Young Investigator Award (YIA) – Understanding Electrostatic Behavior in Granular Materials: Multi-scale Models and Experiments, January 2013 to December 2014
NSF-Center for Pharmaceutical Processing and Research: Porous materials as excipients for solid self-nano emulsifying drug delivery systems, (PI: Lu, Co-PI: Chaudhuri) July 2014 to June 2016
NSF-Center for Pharmaceutical Processing and Research: Experimentally validated computational process models to predict the flow properties of pharmaceutical powders under different humidity conditions, August 2015 to July 2017
American Cancer Society: Activatable nanoparticles for radiotherapy of metastatic ovarian cancer, (PI: Lu, Collaborator: Chaudhuri), July 2015 to June 2019
US-Food and Drug Administration (FDA/NIPTE): A QbD approach to process development: Defining critical quality attributes, evaluating criticality across scales, and relating variation in CPPS/CQAS to product performance, (PI: Jim Drennen, CoPI: Chaudhuri), August 2015 to July 2017
NSF- I/UCRC: Science of Heterogeneous Additive Printing of 3D Materials (SHAP3D), Timeline: 1/1/2017 – 12/31/2022, PI: Anson Ma (CBE), Collaborator: Chaudhuri.
Genentech: 3D printing for solid dosage form, Timeline: 07/01/17 – 06/30/20, PI (s): Chaudhuri, , Anson Ma (CBE).
NSF-CPPR: Inkjet based 3D printing for solid oral dosage manufacturing, PI: Chaudhuri, Co-PI: Anson Ma (CBE), Aug 2017 to July 2019.
US Food and Drug Administration (FDA): Co-PI: B. Chaudhuri, PI: Diane Burgess, A continuous manufacturing platform for complex dosage form, September 2017 to August 2020.
Pfizer: PI(s): B. Chaudhuri, PI: Anson Ma (CBE), Characterization and 3D printing of placebo and modified release tablets. July 2017 to June 2018.
NSF-CPPR: PI: Chaudhuri, Co-PI: R.Bogner, T. Fan (ME), Development of a scaled down model for freeze-thaw of biologics applying a DOE approach, January 2018 to Aug 2019.
NSF-CPPR: PI: Chaudhuri, Experimentally validated CFD-DEM model of multicomponent, multiphase flow modeling of a fluidized bed dryer, January 2019 to December 2020.
Takeda Pharmaceuticals: PI: Chaudhuri, Development of a CFD-DEM model of Pharmaceutical Unit Operations, September 2019 to March 2020.
UConn- START PPOC Grant, June’2020 to May’2021.
Takeda Pharmaceuticals: PI: Chaudhuri, Development of a CFD-DEM model of Tablet Dissolution Process, April 2020 to October 2020.
Genentech: 3D printing for solid dosage forms, Timeline: 11/01/20 – 10/31/22, PI (s): Chaudhuri, , Anson Ma (CBE).
Takeda Pharmaceuticals: PI: Chaudhuri, Applicability and calibration of CFD-DEM model for pharmaceutical processes, November 2020 to October 2021.
Sarepta Therapeutics: Molecular modeling of AAV aggregation and their interaction with hydrophobic surfaces, September 2021 to May 2023.
NSF-CPPR: PI: Chaudhuri, Understanding the role of binder-excipient interaction in continuous wet granulation processes using experimentally validated computer modeling, January 2022 to December 2024.
NSF-CPPR: PI: Chaudhuri, Development of experimentally validated Machine Learning (ML) based Model to predict the thawing time of biologics during large scale Freeze-Thawing cycles, September 2022 to August 2024.
UConn OVPR : PI: B. Chaudhuri, Co-PI: Yu Lei, Yangchao Lu, Matthew Stuber, Research Excellence Program – Continuous manufacturing of drug product for pulmonary drug delivery
Sarepta Therapeutics:PI: B. Chaudhuri, Molecular Modeling of AAV Capsid-capsid interaction under different salt concentrations, surfactants, and shear stress, May’2023 to May’2024.
NSF-CPPR: PI: B. Chaudhuri, Experimentally Validated CFD-DEM Based Model Of Multiphase Mixing Of Suspensions In A HyPerforma Mixer. Jan’2024 to Dec’2025
Aerosol Society PI: B. Chaudhuri, Co-PI: T. Mehta, Effect of process parameters on Dry Powder Inhaler (DPI) Performance. Dec’2023 to Dec’2024
Sarepta Therapeutics:PI: B. Chaudhuri, Studying The Effect of Freezing and Thawing on AAV Capsids by Molecular Modeling, May’2024 to May’2025.
UConn OVPR/ Yale PI: V. Batista, Co-PI: T. Zhu, B. Chaudhuri, Quantum Machine Learning Algorithms for Drug Safety Prediction, Jan’2024 to Dec’2024.
UConn OVPR – REP PI: N. Li, Co-PI: B. Chaudhuri, A mechanistic and systems-based approach to understand PDE, Aug’2024 to July’2025.
Alexion Pharmaceuticals, PI: B. Chaudhuri, Molecular Modeling Based Prediction of the Stability of Biopharmaceutical API under Different Buffer Conditions, April’2025 to Dec’2025.
Sarepta Therapeutics:PI: B. Chaudhuri, Different strategies to study the effect of Freezing and Thawing on AAV Capsids by Molecular Modeling, May’2025 to Dec’2025.